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10,494 | https://devpost.com/software/fact-checker-nlp-bot | Inspiration
So we had been receiving several messages, especially during the lockdown, containing misinformation and fake news, including but not limited to home remedies, conspiracy theories, and fake advisories. We knew something had to be done soon, else people might hurt themselves or their loved-ones trying remedies like this or spread fake news unknowingly. What better than making it easy for people to verify the facts and make an informed decision?
What it does
Fact Check Bot can help you verify if the information in the message is true or not. All you have to do is trigger the bot with keywords from the claim you want to verify and it will provide you with links to the webpages which have reviewed the claim and provided a rating.
How we built it
Facebook has one of the largest userbases so we used Messenger integration to make the bot available to a large audience. Node.js is used for the backend, Wit.AI is used for the natural language processing capabilities of the bot, and Glitch is used for hosting the backend for the bot.
Challenges we ran into
First of all, both of us stay in different timezones and the difference wasn't negligible. We live 8500 miles apart and hence had a time difference of 12:30 hours. This was one of the biggest challenges as one of us had to stay up late or wake up early to collaborate.
Apart from this, it was challenging to find a source of truth for the bot and integrate it as most of them didn't provide APIs or proper documentation. Building a web scrapper meant overheads and increased processing time. Caching all the data and storing it in a database on your own wasn't a practical solution as well. Finding a trustworthy source and integrating it with the messenger bot, while maintaining user privacy was one of the challenges we spent a few days brainstorming about.
Accomplishments that we're proud of
Helping the community identifying fake news.
Building a bot that can understand natural language and doesn't give errors just because I had my caps lock on or I didn't write exactly what the application was expecting.
The bot can be available to the entire world, irrespective of their choice of device, and the users can get a native experience instead of using a web browser.
What we learned
How to build a bot.
How to build NLP models using Wit.AI
Best practices for hiding API Keys in the production environment & most important, GitHub.
Learning new technology isn't that complicated. Where there's a will, there's a way.
What's next for Fact Check Bot
Add support for various other languages so people can have a better experience in their native language.
Add other sources of truth.
Include other fantastic features available for the Messenger platform to improve the user experience.
Built With
facebook-messenger
glitch
javascript
node.js
wit.ai
Try it out
m.me
www.messenger.com | Fact Check Bot | Are you tired of seeing fake news in your social media feed or even in your WhatsApp chats? **Enter Fact Check Bot** Verify the claims made in the message before sharing and help reduce fake news. | ['Atin Singhal', 'Aviral Gupta'] | [] | ['facebook-messenger', 'glitch', 'javascript', 'node.js', 'wit.ai'] | 96 |
10,494 | https://devpost.com/software/testbot-1 |
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if (msg.type === 'video') {
// force a resize of the carousel
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$('[data-slick]').slick("setPosition")
}, 2500
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Sample Conversation Flow
Inspiration
This pandemic has forced us to stay in our homes, causing loneliness and depression to engulf over countless individuals. The time the spent outside earlier, laughing around, hanging out with our friends has been replaced with us being confined in the four walls of our home. Surely we can call them up, but what happens if they move on with their lives and leave you behind? This chatbot is meant to be a companion to every person who feels this way and tries to lighten up their mood, even if it is for a second, during their tea-time, because no one should face this adversity alone.
What it does
teaBot is a chatbot which upon asking, serves you tea and tells you jokes, keeping you entertained in you me-time while you're drinking tea, ultimately keeping you company.
How we built it
I trained a
wit.ai
app to identify intents like greeting, goodbye, tea or joke, send that intent to a Node.js app deployed on
heroku
. The Node.js app processes the request and generates appropriate response which is sent back to the user along with quick replies to which the user can respond to, thus simulating a conversation.
Challenges we ran into
Setting up webhooks took more time than expected due to internal server errors.
Accomplishments that we're proud of
This being my first messenger bot, even though its functionality is very limited at the time, I'm proud of the fact that I was able to complete it before the deadline.
What we learned
I learned about creating a chatbot with Node.js, how to integrate them with wit.ai apps and how to use webhooks.
What's next for teaBot
Not everyone is a fan of tea. teaBot is everyone's companion. In future, support for more drinks, more jokes, and more services like songs, quotes can be added to give it a more human-like touch.
Built With
node.js
wit.ai
Try it out
github.com
m.me | teaBot | Tea time buddy for Messenger, will serve you tea and jokes so that you're never alone. | ['Abhinav Chawla'] | [] | ['node.js', 'wit.ai'] | 97 |
10,494 | https://devpost.com/software/all-a-s-g507so | App Inter-phase
App Inter-phase
App Inter-phase
Inspiration My inspiration started when i watched the movie ..... Social Network and i am a huge fan of Mark Zuckerberg. this then led me to create a global APP which will enhance the lives of kids by providing them a solution to a better and brighter education using online technology as well as allowing all students from across the world to make contact with each other just by a simple swipe of a finger and search for active users across the globe.
What it does its a fully functional educational resource and global messaging service for every user to easily connect with others via their online profiles.
How I built it i used appy pie and my ideas put together to create this global APP
Challenges I ran into the challenges was that of many to mention but the more server ones was time and this was not on my side as i had to work and still do development after work which was becoming rather difficult. i then decided to resign from my job and focus solely on the development and it was at this point were i was able to build my APP to an amazing state
Accomplishments that I'm proud of i have been featured on a few radio stations i was also on TV and most of all the most important achievement is helping people get an education. as well as to note that ALL A's has made it onto windows, IOS and Android.
What I learned is that time is something that can never be wasted and taken for granted as i know the true value of a second, a minute and an hour.
What's next for ALL A's to become the global leader in E-Learning.
Built With
appy-pie
Try it out
play.google.com
www.allas.co.in | ALL A's | Empowering Global Communication and education. | ['Zayne Chan'] | [] | ['appy-pie'] | 98 |
10,494 | https://devpost.com/software/biz-commerce | Banner of Biz Commerce
Inspiration
Truly the story is very inspiring for me . I am a student and don't have knowledge to this type of stuffs . There is a uncle of mine who told me a few days ago that he is opening a small textile factory so, many un-employed people can get a job in this pandemic . I have a little knowledge in html and CSS he told me to create a website and told me to market this business and more than 150 people got job in 1week . I thought to make a page for this business . So, there is no technical person who will support everyone all day long so, I thought to build a chatbot and got help from all Facebook communities . And finally made a simple one and submitting it .
What it does
It is a Facebook page bot . It takes orders from it's users . Shows which products are available with price . Responds to private replies and shows contact details information about the business .
How I built it
I build it with the help of Manychat a very popular platform . And also used my Facebook page .
Challenges I ran into
It was a lot challenging than ever . I never worked in this platform using this tool . The designs were too much hard and setting up the products was too hard for me as a absolute beginner .
Accomplishments that I'm proud of
I am really proud that I can support small businesses in this pandemic situation and this will help the workers of the factory to get more orders to earn a bit more .
What I learned
The full work actually learning . I learnt how to work with small businesses and I also learnt how teamwork works actually . I learnt planning and a bit of marketing .
What's next for Biz-Commerce
Right now it is just a demo . If it works better for the business I will surely make it more user friendly and design it better that no one could imagine that a chat bot can manage a whole business .
Built With
facebook
facebook-messenger
facebookpage
manychat
messenger
Try it out
m.me
www.jarstextile.com | Biz-Commerce | Really This is the time to move from E-commerce to Biz-commerce. Stay at home, all fashion related content and outfits you need are now at your fingertips . | ['JARS Textile'] | [] | ['facebook', 'facebook-messenger', 'facebookpage', 'manychat', 'messenger'] | 99 |
10,494 | https://devpost.com/software/meet-and-greet-789xu2 | Creating session
Sending location
Done
Inspiration
Whenever we plan to meet we face problems deciding the location! Some of us favor one location while the others another and there can't be no unbiased easy solution. So we take the majority vote and ignore the rest!
What it does
Meet and Greet is an easy to use messenger bot. Just provide your location with the bot and that would be it! The bot takes the location and generates an optimum place to meet. Well you can change that to your ease. But now you have a reference right?
How I built it
I used bootbot to communicate with the messenger bot and used postgreSQL as the server and deployed it to aws.
Challenges I ran into
Working with webhook was very tough! Couldn't find many good tutorials there. At last tried reading the documentation for a bit. Reading documentation is tough.
Accomplishments that I'm proud of
Seeing the app running is obviously the most satisfying thing I could have asked for! Also positive feedback that I got are also very good!
What I learned
I learnt to use facebook developers option. Honestly I had no idea Facebook has so many cool features! NLP is just amazing. Will definitely work with that later.
What's next for Meet and Greet
I will try to add restaurant and coffee shop recommendation later!
Built With
amazon-web-services
bootbot
node.js
postgresql
Try it out
m.me
github.com | Meet and Greet | Meet and greet is a messenger bot which will take your teams locations individually and provide you with an optimum location pinpointed on map and also the location | ['MOHAMMAD TAMIMUL EHSAN', 'Sohaib .'] | [] | ['amazon-web-services', 'bootbot', 'node.js', 'postgresql'] | 100 |
10,494 | https://devpost.com/software/anger-dumpster | Facebook page
Welcome screen
Home page with Customer Chat SDK
THE ANGER DUMPSTER
Features
Take in negative comments and tell user how negative they are, send a pic/gif make the idea of speaking out those unspoken (negative) thoughts as a way to dump garbage.
Suggest fun activities: Meme, Music.
Inspiration
I dedicate this project to my very best friend who has been an outcast throughout high school and up till now. Before we met, the lack of a company to share stories became such a burden that left the guy with serious depression. Now that we are separated by distance and isolation due to pandemic, social media is the only way to connect. However, huge difference in schedule leaves us no choice but to minimize our essential chatting time. Therefore, I built this chatbot - The Anger Dumpster - so that my friend can let out everything he wishes to say and relieve his mind while I am off to study. This is for you.
What it does
The bot will serve as a listener to the user. I would initiate a process called Dumping the Trash, which prompts the user to say things that I want to say such as daily incidents, gossips, or swear words (more restrictions will be placed on this feature) that bothers their mind. Then, the bot will comment on how negative the conversation is and send a gif showing a hilarious way to throw a trash, which might lift the mood of the user. Then, if the user does not want to continue, it would suggest certain activities such as Meme and Music. Besides, the bot was designed to respond to certain words like “sad”, “cockroaches”, “Ahh” to make it more of a human-to-human conversation.
Tools
Nodejs
for JavaScript code execution
Heroku Platform
for deploying the node.js App.
Installed packages
npm install --save express dotenv ejs body-parser request
How I built it
I started with basic steps of setting up the webhook according to the documentation and used Heroku as my server to deploy the bot. I then extracted the message from the webhook event, which was handled by functions that uses Regular Expression to match certain words for response and Natural Language Processing (NLP) for identifying purposes and mainly sentiment. Quick Replies were also implemented for directing the user. To stimulate the experience of having someone listening to one’s stories, I displayed a seen-message (sender action) by sending a POST request to Send API. The source code also includes a reset function that resets all the variable for user flow control and negativity score record after the user sends a good-bye message (detected by NLP).
Challenges I ran into
It was first really challenging to set up certain feature (eg. the get-started button) since I had almost zero experience with node js. However, thanks to the help of the Messsenger documentation and online tutorials, I finally understood the basic concepts and syntax to build a demo chatbot. Furthermore, the system of grading how negative a sentence is far more dependent on the individual’s perspective, which I believe it would be a bias to base the bot on my opinion. The step to create a database to keep files such as pictures and gifs is still an issue.
What I learned
This is my first encounter with JavaScript and HTML, in which I acquired the basic logic and syntax for my study in Computer Science. Natural Language Processing was also a completely new concepts that interested my particularly and guided me towards Wit.ai. I also got used to browsing through the documentations and getting the only essential information for help.
What's next for Anger Dumpster
I am working on adding a new feature to the bot that makes it analyze the messages, then guess what the problem might be by matching with database and suggest a way to deal with it. In appropriate situation, it could potentially make a joke or pun from the content of the received message .
The bot also needs to implement a method to check whether certain message composed of words that trigger offence, discrimination or racism to inform the user to avoid such words in everyday life and guide them towards a more loving perspective.
I will also study and explore ways to establish database to save files for retrieving and storing.
Built With
git
github
heroku
html
javascript
natural-language-processing
node.js
Try it out
m.me
github.com | Anger Dumpster | Let out the unspoken! | ['Jamie Vo'] | [] | ['git', 'github', 'heroku', 'html', 'javascript', 'natural-language-processing', 'node.js'] | 101 |
10,494 | https://devpost.com/software/quick-pass-o934v0 |
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FB.init({
appId : 115745995110194,
xfbml : true,
version : 'v3.3'
});
// Get Embedded Video Player API Instance
FB.Event.subscribe('xfbml.ready', function(msg) {
if (msg.type === 'video') {
// force a resize of the carousel
setTimeout(
function() {
$('[data-slick]').slick("setPosition")
}, 2500
)
}
});
};
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var js, fjs = d.getElementsByTagName(s)[0];
if (d.getElementById(id)) return;
js = d.createElement(s);
js.id = id;
js.src = "https://connect.facebook.net/en_US/sdk.js";
fjs.parentNode.insertBefore(js, fjs);
}(document, 'script', 'facebook-jssdk'));
Inspiration
More and more businesses are resuming operations here in the Philippines after being placed on a hard lockdown for 4 months due to COVID-19 pandemic. Establishments are recommencing, public transportations such as trains and buses are back on track, and restaurants are opening their doors to their patrons with social distancing protocols in place. We all think this is the "new normal". However, despite our efforts in maintaining the "new normal" procedures, each and everyone of us are still at risk as we come in contact with people indirectly.
Customers and commuters are required to fill-up a small piece of paper referred to as "contact tracing stubs", which if you don't have a pen with you, you will be borrowing the pen that other people have used to fill the form. Not only is it risky to touch objects that are highly susceptible to spread the virus, but our lives are also at risky every second we are being exposed to prolonged precautionary measures as a result of manual contact tracing.
Many applications have been created amidst this issue of contact tracing, but these applications are not universal as people are not required to install these applications, hence making tracing inaccurate and pointless. What if people doesn't have to fill forms every time they enter a premise? What if these subjects don't have to install a new application for contact tracing? What if self-assessment is as easy as talking to a friend? What if they can get alerts that they had closed contact with a confirmed positive individuals right from the same messaging app they use for connecting to their families and friends? This is where
QuickPass
comes practical, accurate, safe and convenient.
What it does
The HQ Dashboard
- Smallest government units we call "Barangay" being the headquarters of all premises may create an account on our dashboard. They can register the premises within their terrestrial land of jurisdiction that requires monitoring or just send the registration link for these premises to have their own dashboard. HQ can also see all subjects that entered each premise, the age brackets, their statuses(
suspected, confirmed, under monitoring, etc.
), premises they entered and the duration of their stay to the establishment. As results being pass down by the Department of Health, HQ admins can tag confirmed positive subjects then all individuals who have closed contact with the positive person in a premise will be notified by the chatbot and possibly via SMS as well.
The Premise Dashboard
- each premise will be given a registration link by the HQ admins to register a premise dashboard account and generate QR codes for their establishment entrances and exits. The premise can see all individuals that scanned their QR codes and entered the establishment, status of the subjects, the trend of entries, and the prior location of subjects before entering their establishment.
The Chatbot
- the subjects refer to all individuals who are required to fill-up the form before entering a premise. The subjects shall scan the QR Codes on the entrance of the premises they wish to enter. Upon scanning the QR codes, the users will be redirected to their messaging application of choice (
directly Facebook Messenger for now
) and they will be asked by the chatbot to fill-up their information if it is the first time they scan QR codes from the platform(
for every succeeding scans on any premise, the subject doesn't need to fill-up their information again
). If the customer's device is not compatible with reading QR codes, they have an option to search the QuickPass bot name on their messenger and there will be an option to scan QR codes right from the chatbot. The same chatbot will remind the subject to do self-assessment hours after they went outside(
scan premises QR codes
) and their status will be updated depending on their response to the assessment. The HQ admin can make COVID-19 related announcements and the subject will receive those in their messenger.
What’s next for QuickPass
We believe in the impact of all contact tracing solutions to the country and people having messaging applications already on their smart phones is a major factor to the convenience of subjects and accuracy of data. With the support of the government and cooperation of both the citizens and establishments, we want all places to have QuickPass QR codes for everyone’s convenience and safety while supporting the effort of the government to stop the spread of this pandemic.
Built With
dialogflow
facebook-graph
facebook-messenger
microsoftbotframework
qr
react
serverless
Try it out
quick-pass.co
drive.google.com | Quick Pass | Paperless contact tracing and chatbot for updates, self-assessment, guidelines and recommended actions regarding the COVID 19 pandemic. | ['Mac Chicano', 'Bench Cosme', 'lanzosuarez Suarez', 'Rose Ann Gabriel'] | [] | ['dialogflow', 'facebook-graph', 'facebook-messenger', 'microsoftbotframework', 'qr', 'react', 'serverless'] | 102 |
10,494 | https://devpost.com/software/gifshop-wizard | Initial prompt from bot for GIF processing
Sample quick reply options for CycleGAN
Sample quick reply options for style transfer
More sample quick reply options for style transfer
Quick reply options for selecting an effect to apply
The bot processing the GIF as the user waits for a response
Quick reply options for selecting a source image to apply fake motion onto
Finish processing GIF
Quick reply options for next effect to apply after showing results of previous effect being applied
GIF
Our logo was inspired by the very first test image we used with the "tripping" style mask
Inspiration
We felt that modern computer vision techniques such as style transfer and object removal were only accessible to those who are well versed in machine learning and have sufficient computing resources. The average person does not have access to either of these which means that it is difficult for an average user to try out these techniques on their GIFs or images. We want to alleviate both of these problems and provide a platform for users to easily manipulate their GIFs or images using techniques from computer vision and receive instant feedback.
What it does
GIFShop Wizard is a Messenger bot that applies computer vision techniques on GIFs and images sent by users.
The bot receives images or GIFs and prompts users for an image processing technique to apply using Quick Replies. The bot processes the image according to the user's specification and returns the processed image to the user. The image processing techniques currently supported include fake motion, object removal, style transfer, GAN, and segmented style transfer. We drive the dialogue flow with Quick Replies to minimize communication errors and keep the interaction as close to GIF-to-GIF as possible.
Foreground Object Removal: Objects may appear in images that we wish to remove (i.e. photobombs). It takes long enough to photoshop objects out, but this is even more challenging for videos, where a manual process presents itself as a major obstacle. Thus we provide an object removal function, where we first detect what objects are available in the entire GIF, then return a list of detected objects for the user to selectively remove, and consecutively execute the removal of the specified object.
Fake Motion: This vision function enables users to transfer the motion in their GIF into one of our available source images. Motions can be transferred to faces or body postures using the first order of motion model. For example, if a user has a GIF of a person talking or moving their head, this motion can be transferred to images of faces that we provide. The main prerequisite from the user is that their driving image is as closely cropped to the object (e.g. the face).
Fast Style Transfer: When one GIF or meme is not enough, why not make more? To increase variations of the same content GIF, we can apply a style mask via neural style transfer. We trained on several style images to return style mask weights, such that when a user passes a GIF through, they can select from a variety of masks to apply onto their content image. To minimize latency is retrieving a stylized image, we pre-trained models rather than training on a new style each time (and thus this also means a user is not currently permitted from passing a custom style image to train on the spot).
CycleGAN: Though quick to train and perform inference, style transfer applies the style to the whole image and not selectively. Therefore a generative adversarial network comes in handy, selectively applying the style of the target object onto the source object. For example, for the mask
horse2zebra
, if a user passes in an image with a horse in it, CycleGAN would selectively stylize horses to possess stripes of a zebra. It should be noted that
horse2zebra
means that the GAN was trained on a pair of datasets (horse, zebra), but it does not mean that inference is limited to horse GIFs alone. In fact, users can pass in other images (e.g. people) and the stripes of a zebra can often be transferred as well, though just not as accurately as horse images.
Segmented Style Transfer: While CycleGAN is selective to specific objects, we use instance segmentation to target significant scene components and apply style transfer on those segments (i.e. scene-specific, not object-specific). We use FCN to detect instance segments, identify the largest one, extract that segment as an image, perform style transfer upon this image, and stitch it back onto the original image.
How we built it
We interface with the Messenger API and Webhooks using a Flask server and a custom bot interface. The models used in the various computer vision techniques are trained in PyTorch and TensorFlow.
Chatbot server
We built a convenience interface bot that takes in data from the server and automatically builds the correct POST request and sends it to the Messenger API. The actions currently supported include sending text, sending images, sending quick replies, and sending typing sender actions.
Vision functionality
GIF extraction/stitching:
When the user sends a GIF, we first parse GIF into its individual frames. We then apply the vision function selected by the user with its corresponding arguments and perform inference frame by frame. After all the frames are processed, we stitch the frames back together, compress the file to minimize latency, and send it to the user. Images are treated as a GIF with a single frame and are thus compatible with our bot.
Fast style transfer:
Based on the work of
Johnson et al.
, we implemented their real-time style transfer architecture that uses a perceptual loss function to measure model perceptual differences between the content image and the style image. The loss functions are capturing semantic differences between the original image and stylized image through image classification, based on a 16-layer VGG network pretrained on ImageNet. Stylized images are generated from in-network downsampling and upsampling, and the resulting image is passed as an argument to the perceptual loss function. We store pretrained style mask weights, and when a user selects the quick reply button to select a specific mask, we perform inference on each frame.
Segmented style transfer:
For this function, we use fast style transfer as a boilerplate to perform style transfer. The main difference is that we first perform instance segmentation using Fully-Convolutional Networks to compute whether each pixel is semantically different from another, and thus return a list of segment masks. We detect the largest mask, obtain its pixel coordinates in an array, export it as an image with a single color fill background, perform fast style transfer upon this mask image, then transpose the pixel coordinates from this stylized mask image onto the original image, thus selectively performing style transfer onto a specific mask in the image.
CycleGAN:
For this image-to-image translation architecture (
Zhu et al.
), the generator network transcribes perturbations upon the source image with features from the style image. The discriminator network evaluates the class of the stylized image; if the label is identical to the ground truth label, then the image-to-image translation is a success. This is somewhat similar to the perceptual loss function in FST, but we instead use a discriminator network to measure perceptual differences.
First order of motion:
Based on
Siarohin et al.
, our implementation of the First Order Motion architecture enables users to pass their GIF file as the driving image (image that contains the motion), and we provide the source images (images that users would want to transfer motion from their GIF into). The model works by first computing the first order motion representation by using a keypoint detector (identifying points of motion within a face/body). Using a motion network, we generate optical flow from the motion representations, and perform pixel transformations onto the source image based on the calculated flow of each pixel.
Foreground removal:
For this implementation, we remove foreground objects by performing YOLOv3 object detection, and sending the detected objects to users (objects based on those from the MSCOCO dataset). The object selected by the user via quick replies is passed as an argument to the object removal function, where we first apply a bounding box to the objects detected (if the object is equal to the one selected by the user), then remove pixels within the bounding boxes, then passing the resultant image to
pix2pix
to fill the missing pixels (supposedly with a selection of the surrounding background pixels).
Challenges we ran into
Model inference for image processing usually takes a while. Since we are processing each GIF frame by frame, this means model inference for GIFs takes even longer. Because Messenger requires a response within 20 seconds, this meant that we needed to find a way to work around the constraint. We tackle this problem by continuing to process the image on the server and keeping track of the fulfillment status of the request rather than allow Messenger to timeout our process.
Because we implement several external computer vision architectures, we pull source code from multiple different projects. This means that they could potentially use different versions of PyTorch or TensorFlow. PyTorch and TensorFlow 1 turn out to be incompatible due to TensorFlow 1 using outdated libraries. To remedy the situation, we had to migrate all the TensorFlow 1 code to TensorFlow 2 code.
When we tried sending multiple GIFs to the bot, the GPU would sometimes run out of memory. To address this issue, we allocated memory carefully for each vision function and reduced parallelism to decrease the strain on our GPU.
Trying to maintain and update the state of the user is difficult as the Messenger API uses webhooks. This was solved by creating and implementing a clear organization and structure of the user flow.
Since only one of our members had a GPU, we had to distribute tasks carefully and separate our logic accordingly so that certain features could be tested independently.
Accomplishments that we're proud of
Since the Messenger API does not have an official Python API, we had to use a bot interface to send requests to the API from Flask. Since the bot interfaces we found were insufficient for our purposes, we wrote our own.
We were able to aggregate a bunch of different computer vision models from different projects and both make them compatible with each other and integrate them together into one coherent experience. To do this, we had to modify and rewrite a good amount of the source code and train our own models with our own source images.
What we learned
We got to experiment with various Messenger API functions such as Quick Replies and Sender Actions through Flask. We also got to play around with webhooks and use localhost tunneling to test our code. We learned how to modify existing bot interfaces and deprecated wrappers/libraries in order to customize them to our needs.
Furthermore, we got the chance to play around with various different computer vision models and tinker with different image processing techniques. It was a good opportunity to bring computer vision to the chatbot space, which has traditionally been dominated by NLP literature. We explored state-of-the-art models, made modifications to improve them and generate novel functionality, and exercised proper software engineering and documentation practices with the extended time granted by the competition.
What's next for GIFShop Wizard
There are several directions that we could have taken this project if we had more time to work on it.
Additional Techniques
Some additional things we would like to see as features in our bot include super resolution of GIFs and images, increasing the resolution of each image, and frame interpolation for GIFs, creating intermediate frames in between consecutive frames.
Custom Source Images
We would like to allow users to input custom source images for various features such as fake motion and style transfer. The main concern for implementing this feature is that in order to be able to apply an effect with a source image, the model must be trained with the source image which could potentially take a long time.
Video Processing
GIFs are essentially short videos so extending our bot to videos is not too difficult. The only concern with this is that it may take a long time to render on the server. Since Messenger expects a response within 20 seconds, this could be hard to implement depending on the length of the video.
Model Improvements
Even though our features produce pretty good results, they could always be improved. Some of the things we could do include running more iterations, finding other interesting source images, and investigating other state-of-the-art models.
References
First Order of Motion
paper
Foreground Removal
paper
Fast Style Transfer
paper
CycleGAN
paper
Instance Segmentation
paper
Built With
facebook-messenger
flask
opencv
python
pytorch
tensorflow
Try it out
github.com
m.me | GIFShop Wizard | Computer vision has been left out of the hands of many photoshopping enthusiasts and chatbot users alike. Our mission is to bring automated GIF-editing functionality to the masses with GIFShop Wizard. | ['Jacky Lee'] | [] | ['facebook-messenger', 'flask', 'opencv', 'python', 'pytorch', 'tensorflow'] | 103 |
10,494 | https://devpost.com/software/inest | Inspiration
Facebook
What it does
Create a virtual world which has local and world section
How I build
Hard work ,and lot of hardwork on databases
Challenges I ran into
Designing the best and efficient data base,and even i was not good at ui design so I learnt all that
Accomplishments that I'm proud of
As a one man army I have completed the project since everyone was busy chilling
What I learned
Everything is possible
What's next for Inest
Launching in my city
Built With
adobe
android
firebase
java
k20pro
xd
xml
Try it out
github.com
drive.google.com | Inest | An indian social media platform,which is more optimistic as compared to other | ['zubair shareef Shareef'] | [] | ['adobe', 'android', 'firebase', 'java', 'k20pro', 'xd', 'xml'] | 104 |
10,494 | https://devpost.com/software/newzery | the article2video messenger bot
image : imagery : : news : newzery!
Inspiration
Assuming that advertising revenue is a reasonable proxy for attention, it turns out that humans like pictures more than text, and moving pictures most of all; so it has gone on the Internet.[
source
].
What it does
This bot takes the URL of a web-based content article and automatically generates a motion-video out of it.
How I built it
Newzery uses
moviepy
for making a video out of text, images, and sound. The article of content is scrapped using
newspaper
. The sound effects are determined by the sentiment analysis of the content, which is done using
nltk
. The bot is made using
flask
. Facebook messaging API is integrated with the bot using
pymessenger
. The bot is hosted on
Heroku
free tier.
Challenges I ran into
Compression of video to match the attachment file limit of messenger API
Handling requests to avoid exceeding of memory quota on Heroku free tier
Setting up the production environment for moviepy: installing ImageMagick on Heroku
Accomplishments that I'm proud of
automated delivery of personalized media over messenger
enhanced retention of article content in users' memory
a major step towards an end-to-end pipeline for on-demand article2video generation
What I learned
messenger webhook callbacks
garbage collection in python
meeting production server constraints
What's next for Newzery
Iterations for getting the product market-ready
Expand to more platforms including Whatsapp, Instagram
Built With
flask
heroku
moviepy
newspaper
nltk
pymessenger
python
Try it out
m.me
github.com | Newzery | The article2video messenger bot | ['Rohit Ner'] | [] | ['flask', 'heroku', 'moviepy', 'newspaper', 'nltk', 'pymessenger', 'python'] | 105 |
10,494 | https://devpost.com/software/covinger | Icon
Plasma Donor Notifying Message
Data Collection
Multiple potential plasma recipient matches while submitting request
Another Plasma Donor Notifying Message
Inspiration
Plasma is critical for COVID-19 patients, but finding appropriate match is not that easy, but when connectivity is there, it's not difficult anymore, we want to take the concept of connectivity and social media to the next stage so that the planet gets benefited in this difficult time.
What it does
Covinger is a chatbot for sharing and notifying plasma donors and recipients with each other's information and contact so that they can find their matching donor(s)/recipient(s) easily. First we take information from an individual , we validate his/her information (if he/she is capable of donating/receiving or not) and provide him/her with the image,name, details, address and contact of his/her potential donor(s)/recipient(s), and if he/she wants to directly inform any of the matches, he/she just needs to click on the INFORM button and that person will immediately get message from Covinger having the details of the informer.
How we built it
=> For webhook endpoint.
=> We used nodeJS+bootbot.
=> For storing data, we used postGreSql and the whole system is hosted on AWS elastic beanstalk for high scalability and availability.
Challenges we ran into
=> Validating information.
=> Setting up the conversation flow in both organic but informative way.
Accomplishments that we're proud of
=> This app is being used by our class-mates.
=> This initiation is quite appreciated and regarded as appropriate (considering current situation) by the users.
What we learned
=> Validating data for medical requirements.
=> Setting the backend in such way so that it ensures almost 100% availability and very high scalability
What's next for Covinger
=> Taking the app live and serve the humanity.
Built With
aws-elastic-beanstalk
bootbot
node.js
postgresql
Try it out
messenger.com
github.com
www.linkedin.com
web.facebook.com
mehrab.netlify.app | Covinger | Covid+Messenger=>Covinger , a bot that connects plasma donors and recipients so that they can find their matching donor(s)/recipient(s) easily. | ['Md. Mehrab Haque', 'Tamim Ehsan'] | [] | ['aws-elastic-beanstalk', 'bootbot', 'node.js', 'postgresql'] | 106 |
10,494 | https://devpost.com/software/jobotic-find-a-new-job | Meet Jobotic
Find your next job
Inspiration
In the past few months, the coronavirus pandemic has put millions of
people out of work
. Unemployment rates have reached a level never seen before. This context has brought many uncertainties.
Thinking about it, Jobotic has come to life. He is a virtual assistant to
search for jobs
and helps people. Jobotic also has intelligent searches using user historic to find the best jobs!
What it does
Jobotic helps people to find a new job with a smart search. Jobotic is integrated with many job search APIs to find the ideal job.
How I built it
Chatbot/Backend - I created the Chatbot using Kotlin and Spring also I've used Wit.ai and Microsoft Recognize Services to provide a better experience.
Website - I built a website and support chatbot (using Messenger Extension)
Challenges I ran into
In my opinion, the main challenge was to offer a search experience with several APIs in a chatbot interface and also to be correct in the suggestions
Accomplishments that I'm proud of
Through technology, we can make people's lives better and create new experiences to solve problems. I'm happy and proud of helping people to overcome this difficult moment.
I'm also glad to create a nice system using step forward technologies prepared for the next steps
What I learned
Messenger API details
Wit.ai integration
Microsoft Recognize Services API
What's next for Jobotic - Find a new job
Expand to new locations (For now is only US and Brazil)
Job and Tips alerts
Integration for recruiters
Built With
azure
bootstrap
careerjet-api
digitalocean
facebook-messenger
gitlab
go-daddy
graph-api
helm
indeed-api
javascript
jquery
k8s
k8s-helm
kotlin
nginx
open-street-map-api
postgresql
spring
viacep-api
wit.ai
zippopotam-api
Try it out
m.me
jobotic.me | Jobotic - Find a new job | Jobotic is a virtual job-seeking assistant. Coronavirus pandemic has put millions of people out of work. Thinking about it, Jobotic has come to life. | ['André Silva'] | [] | ['azure', 'bootstrap', 'careerjet-api', 'digitalocean', 'facebook-messenger', 'gitlab', 'go-daddy', 'graph-api', 'helm', 'indeed-api', 'javascript', 'jquery', 'k8s', 'k8s-helm', 'kotlin', 'nginx', 'open-street-map-api', 'postgresql', 'spring', 'viacep-api', 'wit.ai', 'zippopotam-api'] | 107 |
10,494 | https://devpost.com/software/rubberduck | Inspiration
Sometimes, programmers may feel lonely, wanting to explain their technical issues step by step to someone else with a hope for an idea to strike their minds. At these situations, Rubberduck debuggig is actually a saviour.
rubber duck debugging
, But I wish to improvise this technique. Because how nice it would be when someone listens to your problem, motivates you and gives some relevant suggestions. Here comes
RubberDuck
for this.
Bot is made for you which is more than a friend.
What it does
It listens to your approach or problem
You can chat casually with this bot
It gives you relevant suggestions
It motivates you while explaining
It tells you some nice programming jokes
It has Quick reply feature
Challenges I ran into
I really faced very meagre amount of challenges as Facebook's documentation is very well scripted with good examples, that helped me build this bot very quick, but one crucial challenge was to give train the bot. Yet the dialog flow mitigated the difficulties.
Accomplishments that I'm proud of
This will be helpful for programmers community as they will not feel lonely anymore while programming.
What I learned
Learnt a lot about Facebook's messaging API, dialog flow
What's next for RubberDuck
-Reminders
-Try to give solution for the problem
-Indication for programmer's mood
-To share the solution found for a problem by someone else to the person actually facing the problem.
-Attachment support
-Voice messaging
adding more fire and fun *
Built With
adobexd
dialog-flow
dialogue-flow
heroku
kapwing
messaging-api
node.js
powerdirector
Try it out
www.messenger.com
rubberduck.herokuapp.com | RubberDuck | RubberDuck is chatbot, which helps programmers to debug their codes by rubber duck debugging method (https://en.wikipedia.org/wiki/Rubber_duck_debugging) | ['praveen kumar', 'Vishnu Priya'] | [] | ['adobexd', 'dialog-flow', 'dialogue-flow', 'heroku', 'kapwing', 'messaging-api', 'node.js', 'powerdirector'] | 108 |
10,494 | https://devpost.com/software/covid-o-bot | You can talk to Covid-O-Bot through the website
Equip the information armor to withstand the adversary
Order medicines without any hassle.
Get reliable information
Get Immediate help
Multiple options present.
Get updates on COVID-19 instantly
Get notified about updates.
Get Address to the Nearest Hospital treating COVID-19 patients.
Find nearest places to donate plasma
Talk to a reliable agent to get answers to your questions
Inspiration
In the time of the COVID pandemic, a lack of reliable information can cause many avoidable fatalities. With India being the most massive audience to Facebook, Covid-O-Bot can spread trustworthy words simply and quickly.
During this pandemic, many people are confused and with the overload of information cannot assess options rationally. Covid-O-Bot acts as One Stop Solution for all the problems they can face ranging from social distancing to ordering medicines online.
What it does
Covid-O-Bot is a chatbot that uses multiple features to answer our questions about COVID 19.
It uses quick replies to answer many questions about COVID 19 with information taken from reliable sources.
It also uses one-time notifications to notify people about news updates they select. One can also talk to our chatbot by commenting. It also makes use of the Handover Protocol so you can talk to an agent if required.
Apart from general information and news updates, it can be used to track vaccines, look for plasma donors, and even buy medicines and sanitizers.
It uses one-time notifications to notify people, so they do not have to look for the same information again.
Covid-O-Bot can also be accessed via our website for people who do not use Facebook.
How I built it
We used Manychat, a platform to create a chat flow and Facebook Messenger to interact with the chatbot.
Challenges I ran into
Being beginners to both hackathons and Messengers, it was exhausting to manage college classes and communication with team members.
It was a challenge to find accurate information. Apart from this, it was challenging to implement one-time notification and private replies. Another challenge was to add Messenger to our website.
Managing the database of medicines proved to be another cumbersome task.
Accomplishments that I'm proud of
We were able to create a chatbot that could provide reliable information about the pandemic simply.
We were able to give real-time information about ICMR centers and hospitals nearby in case of emergency.
What I learned
Being a beginner in all the required skills, we were able to garner experience in building a chatbot and linking it to Facebook.
Apart from this, we were also able to expand our knowledge about COVID 19 in the process.
What's next for Covid-O-Bot
Keep it live to help people who need this information at the time of this pandemic. Should all go well, add a database for plasma donors and patients in need of plasma. Also, we wish to add a private chatroom for doctors and patients.
We also want to extend the medicine ordering services to other countries, as currently, it is operational only in India.
Another feature we would like to add is multiple languages and NLP. We are also currently trying to add a voice recognition feature in Covid-O-Bot.
Built With
css3
facebook-messenger
html5
javascript
manychat
node.js
react
Try it out
m.me
fuchsia-creative-basket.glitch.me | Covid-O-Bot | Equip the information armor to withstand the adversary | ['Bharat Soni', 'Manvi Goel'] | [] | ['css3', 'facebook-messenger', 'html5', 'javascript', 'manychat', 'node.js', 'react'] | 109 |
10,494 | https://devpost.com/software/smith-bwfvah | Smith, The Chatbot that can teach you.
Inspiration
Across the world, learning computer science is very hard for students. My team, therefore, decided to change this by creating a chatbot that helps you learn computer science, and if the chatbot can't help you with your problem you can receive human help with the help of handover protocol.
What it does
A chatbot for helping computer science aspirants learn technology.
How I built it
I built it using wit.ai.
Challenges I ran into
Implementing the handover protocol.
Accomplishments that I'm proud of
We got to have hands-on experience with Wit.ai and Facebook APIs.
What I learned
How to train a model with Wit.ai
What's next for Smith
We want to make smith better trained for helping students with learning and also create an Android Application with morse code to help the blind, deaf and dumb use our application.
Built With
ai
wit.ai
Try it out
github.com | Smith | The Chatbot that help to teach you. | ['Nachiketa Chakraborty', 'designerarj2001', 'souravdas3804'] | [] | ['ai', 'wit.ai'] | 110 |
10,494 | https://devpost.com/software/chatapp-yw2nle | I just wanted to learn and explore more of android development
It just a simple messaging and photo-sharing app
I used java for backend and XML for frontend
I first had to learn to use Firebase and there were lots of build error for which I had to search alot
It really works
Good coding practice and Firebase
I am looking to add group features and something similar to Facebook friends
Built With
android
android-studio
firebase
java
xms
Try it out
github.com | ChatApp | It just a simple messaging and photo sharing app | ['Priyandubey Dubey'] | [] | ['android', 'android-studio', 'firebase', 'java', 'xms'] | 111 |
10,494 | https://devpost.com/software/universal-travel-assistant | Inspiration
Due to the pandemic, people don't physically go to business to purchase goods and services
What it does
I allow a traveler to purchase a ticket, book room and book car for their trip to their destination
How I built it
It was built using api.ai.
Challenges I ran into
I run through a lot of challenges because it was my second time creating a bot.
Accomplishments that I'm proud of
I am proud that I am able to build a functional bot
What I learned
I learn how to use api.ai and moreover working with fulfillment.
What's next for Universal Travel Assistant
Built With
api.ai | Universal Travel Assistant | Universal Travel Assistant is a bot that plan your trip. | ['Mark Gbalazeh'] | [] | ['api.ai'] | 112 |
10,494 | https://devpost.com/software/covid-19-support | Inspiration
In Vietnam, the Covid-19 anti-epidemic is entering in a second phase, which is more dangerous and harsher, after the previous successful phase. The number of infections has increased dramatically and the first deaths occurred in this country. Because of the success of the previous anti-epidemic phase, along with fake news about the disease, people are being subjective, underestimate the disease. Along with that is the flood of information on the Internet with different contents and explanations about the disease, making it difficult for people to know exactly how to prevent this disease.
What it does
Chatbot will provide all the most accurate and up-to-date information about Covid-19 along with an update on disease situation and number of cases taken from the WHO website. Accurate and complete knowledge of Covid-19 will increase public awareness of the epidemic and facilitate the government's social isolation in its campaign to prevent the spread of the epidemic. Chatbot on the facebook platform - the most used social network in Vietnam, will make it easy for people to access information easily and fastest amid countless information on the internet.
How I built it
I used Chatfuel to create a chat flow and Facebook Massager to interact with the chatbot.
Challenges I ran into
There are still limitations on the API that provide information about the disease or the number of cases as well as tracking the disease in Vietnam (the API only support much for the US and European countries).
Accomplishments that I'm proud of
Provide accurate, fast and concise information about Covid-19 and create something useful for the community
What I learned
I learned for the first time how to build a chatbot messenger as well as taking part in a hackathon contest on facebook.
What's next for COVID-19 Support
Research and develop some features or API about epidemics in Vietnam. I will try to improve the FAQ feature so that chatbot can answer more specific questions in more detail.
Built With
chatfuel
Try it out
m.me | COVID-19 Support | Provide information about covid-19 | ['Nguyen Minh'] | [] | ['chatfuel'] | 113 |
10,494 | https://devpost.com/software/healthcare-advertising-platform | Inspiration
When HealthCare.gov was created the government was giving $7.7 million to all the states that came up with a plan to direct people to HealthCare.gov. Our Governor Chris Christie seemed like he was dragging his feet on this so I decided to take up the challenge. Also, at the same time, the teachers in New Jersey were fighting with the state over a 7 million shortfall in their budget, and because my sister was a teacher I knew they really needed this money.
What it does
Directs people to HealthCare.gov in their state by using Facebook keyword business pages which are basically the terms they would use to search for healthcare online in their state.
How I built it
I just found out what terms people were using the most to search for healthcare and then I multiplied each one by all the states and its territories.
Challenges I ran into
It took way longer then I thought to create. (About 10 hours a day for 6 months) Also, I haven't been able to sign onto Facebook for over 10 months. Everything I created is still there and I still get alerts and message but Facebook will not let me log in.
Accomplishments that I'm proud of
The number of people I directed to HealthCare.gov. I don't know the number but I know it a lot. Also, when this finally gets integrated with AI and messaging it's going to save the government hundreds of billions of dollars in future advertising and customer support costs.
What I learned
That politics in America is so toxic that when you send this platform to the governor's house by UPS and all he has to do is hand it in to collect $7.7 million he will just throw it in the trash if it's going to help another political party. He could care less about how much it would have helped his state's taxpayers.
What's next for HealthCare Advertising Platform
I have no idea. I can't log in to Facebook. But, this Nationwide Navigation & Advertising Platform for HealthCare.gov will save the USA hundreds of billions of dollars in future advertising and customer service costs with the help of artificial intelligence (AI) and machine learning and could be used with HealthCare services like telemedicine as well. It also could be used to help direct people to all the nationwide insurance agents and brokers licensed with the Small Business Health Options (SHOP) that are available throughout the year to help people enroll in and manage their SHOP coverage
Built With
english
facebook | HealthCare Advertising Platform | Nationwide Navigation & Advertising Platform for HealthCare.gov | ['Jack Kurz'] | [] | ['english', 'facebook'] | 114 |
10,494 | https://devpost.com/software/vang | Inspiration
We witnessed the gold heist recently, and found people around struggle to get to the information.
What it does
We decided to make a chatbot that gives information about gold in Vietnam, especially in the SJC brand
How we built it
We place a script that scrape data on the web, running with pymessenger and flask inside heroku, and connect it to the facebook apps
Challenges we ran into
Debugging locally with ngrok
We started initially with nodejs but turn to python to challenge ourselves
For some issues we couldnt use mongodb or mysql, therefore we choose sqlite
Accomplishments that we're proud of
Me, Phat Tran was in a middle of the essay application while my Long Vu was preparing for his study in France.
What we learned
How to use python, flask, pymessenger
Tunnel with ngrok, serveo, localtunnel
Scraping data with soup
Using sqlite
What's next for Vang ++
We might use panda to create fast graph visualization bot
Built With
beautiful-soup
flask
heroku
pymessenger
python
Try it out
m.me | Vangpp | Provides info about gold for people | ['Long Vu', 'Phat Tran', 'Hung Tran'] | [] | ['beautiful-soup', 'flask', 'heroku', 'pymessenger', 'python'] | 115 |
10,494 | https://devpost.com/software/flimbun | Inspiration
Facebook messenger, and all messaging apps
Built With
django
django-channels
python
Try it out
github.com | Flimbun | A Chatting app | ['Itech Indrustries'] | [] | ['django', 'django-channels', 'python'] | 116 |
10,494 | https://devpost.com/software/covid-19-ch7d94 | messenger,telegram,line
Inspiration
This is an open-source multi-channel (Messenger, Telegram, and LINE) bot for querying and subscribing information and data about Novel Coronavirus (COVID-19).
What it does
sends direct messages to the patients who are suffering from COVID-19
How I built it
by using javascript, typescript.
install the dependencies
cd COVID-19-bot
yarn
Accomplishments that I'm proud of
useful for people around the world who are suffering from COVID to ensure their position in COVID scare.
What's next for COVID-19
.
Russia is currently developing vaccine fro COVID-19 after that it comes to normal life
Built With
dockerfile
javascript
typescript
Try it out
github.com | covid Helpline | donate plasma save life | ['Hemanth Varma'] | [] | ['dockerfile', 'javascript', 'typescript'] | 117 |
10,494 | https://devpost.com/software/bookmyappointment-bot | Getting Started
Choosing a Therapist
One Time Notification for Confirmation
Confirming with Phone Number
Introduction
As an avid fitness enthusiast, I am a regular at my preferred physiotherapy clinic. However, I've noticed that the booking workflow is overly complicated. For this project, I imagined a simple & easy to use booking system using Facebook Messenger. I found that the available API's, such as quick replies and one-time notifications, made it much easier to create a booking process that was easy to use.
Implementation
The appointment booking bot is implemented using a simple Express.js server that listens to Messenger API webhook events. The server is hosted on Heroku.
To enable easy booking functionality, we utilize Facebook Messenger quick replies to choose an available physiotherapist, booking time, and phone number to confirm the appointment request.
We then leverage the one-time notification API to allow the bot to notify the client when the booking is confirmed. Although we ask for this permission, we do not yet use the generated token to send a confirmation.
Future Steps
As we are not currently using production availability data, we are currently mocking the available therapists and time data. We would love to work with a clinic to bring this to reality.
Built With
express.js
heroku
javascript
Try it out
github.com | BookMyAppointment Bot | A streamlined physiotherapy booking workflow using Facebook Messenger API's. | ['Frank Jia'] | [] | ['express.js', 'heroku', 'javascript'] | 118 |
10,494 | https://devpost.com/software/shahajjo-bot | Inspiration
In this Covid-19 pandemic, there are many people in our country facing a financial crisis right now. Cause at this time, many people are lost their job due to the COVID-19 pandemic. That's why many of them not able to bear their minimum daily medical cost. I saw that some of them even didn't able to buy their regular needed medicine. So I thought that if I make a bot that helps to save millions of people life, that will be great.
What it does
Shahajjo bot helps people to donate their unused medicine to people who needed those medicines. On the other hand, if anyone needs any kind of medicine, they can also search for their medicine, which was donated by other peoples using the shahajjo bot. Doctors can also voluntarily help patients by using this bot. This will help them to submit their info into the database so that when anyone needs help from the doctor, they can also easily find doctors without any cost by using our bot. This bot will help them get consultancy about their health problems in both emergency and typical cases.
How I built it
Technologies had I used in this bot
Chatfuel
Google SpreadSheets
JSON
Facebook Page integration
Challenges I ran into
I invited some of our health officials to check this bot for getting their feedback. After using this, they had told me that this bot is so much impressive. They said that it's a great example of how technology can help us to survive together in our modern society. They also told me that they want to use this bot in nationwide. Also, suggest me to use more frontier technologies in this bot which will help us to scale up this bot.
Accomplishments that I'm proud of
I hope that in this uncertain situation this bot will help many people to save their lives also their family members. With the help of this bot, anyone can quickly get access to the medicine without any cost and also they can get health advice from the doctors from anywhere. This bot is creating a bridge between the people who wanted to help and those who need help. I am really so much proud cause I think this bot may help many people to save their life also anyone can get access the health advice from anywhere.
What I learned
How to create integration between google spreadsheets and Facebook bot
How to use JSON API
How to create a gallery card in messenger bot
How to solving problem in healthcare by using technology.
What's next for Shahajjo Bot
In the future, I want to add a feature where users can automatically search medicine by only uploading the medicine picture
I also want to add another feature where bot can suggest medicine based on analyzing their symptoms
Built With
chatfuel
google-spreadsheets
json
Try it out
www.facebook.com | Shahajjo Bot | Shahajjo Bot helps people donate their unused medicine to the right person, and also it helps the patient find a doctor on their emergency basis so that they can get help. | ['Sawrav Chowdhury'] | [] | ['chatfuel', 'google-spreadsheets', 'json'] | 119 |
10,494 | https://devpost.com/software/bot-seller | Starting of the conversation with the page
Middle of the conversation
Ordering/buying products .
Inspiration
This project is fully inspirational because, for the first time I've build a business type messaging bot .
What it does
It integrates with you customers take orders give private replies also .
How I built it
I built it using Chat-fuel it is a great and popular platform for building messenger bots .
Challenges I ran into
This time i can really say it was easy because Chat-fuel team made this platform very user friendly . Thanks to them i didn't faced that much challenges or problems .
Accomplishments that I'm proud of
Really proud that now i can build business managing bots for free of cost and easy anyone have never thought of .
What I learned
The full thing i worked here was learning and building .
What's next for Mr Bot
I am gonna make it better and thinking of to make more like this one .
Built With
chatfuel
facebook-messenger
Try it out
www.facebook.com
www.msaevan.xyz | Mr Bot | Bot for every business on Facebook | ['tasnima azad tisha', 'Abu Azad Mia', 'JARS Textile'] | [] | ['chatfuel', 'facebook-messenger'] | 120 |
10,494 | https://devpost.com/software/covid19-assistant | Screen capture of how it works
Inspiration
I am an international student who completed his first year in college just this past May. I spoke to my friends in Ghana just a few months ago, and among many other things, we spoke about the current pandemic. I was shocked at how uninformed they were regarding the causes, symptoms, and preventive measures for Covid-19. I, therefore, decided to build this to help not only my friends but anybody around the world also get free information, help, and support on Covid-19.
What it does
This assistant basically provides COVID-19 statistics, help, and resources information to everyone from any part of the world.
How I built it
I used node.js for backend webhook management.
Challenges I ran into
I think my biggest challenge was finding credible sources of information on the pandemic. The internet is filled with so much information that it is sometimes difficult to decipher what is right and wrong information.
Accomplishments that I'm proud of
The fact that I am able to make something that my friends have found useful in understanding the pandemic is largely a proud feat.
What I learned
This was my first time coding in node.js, and it turned out to be a pleasant and worthwhile experience.
What's next for COVID19 Assistant.
I hope to expand this to be able to provide statistics on every disease and to also be able to offer people important and helpful healthcare solutions, including, but not limited to, medical reports, and in the very distant future ability to book appointments and get diagnosis from Medical personnel.
Built With
node.js | COVID19 Assistant. | Find Country specific Covid19 help and support resources | ['Ebenezer Obiri'] | [] | ['node.js'] | 121 |
10,494 | https://devpost.com/software/wit-chat-messenger | Inspiration
What it does
It could let a user know about the current time at any location and the distance between two locations.
How I built it
I use node.js as my backend to handle requests and train Wit.ai to extract information from text.
Challenges I ran into
I encounter some problems when I register the app for my facebook page.
Accomplishments that I'm proud of
What I learned
What's next for Wit chat messenger
Built With
node.js
wit.ai
Try it out
www.messenger.com | Wit chat messenger | A chatbot messenger with Wit that can let user know information about time and distance | ['Tung Luu'] | [] | ['node.js', 'wit.ai'] | 122 |
10,494 | https://devpost.com/software/banktutor | GIF
Account open workflow
Inspiration
When we go to bank, for most of the non trivial work, I see the employees asking their seniors or call people in other branches/head office for the process. Though most of these are documented, finding them is pretty difficult. Also, searching for relevant documentation is another pain
What it does
Banks, being one of the consumer heavy industry, with most of the customer facing employees not very well verse with handling software technology, a messenger kind of chat with nlp integrated, eases lives of many bankers.
What we have presented is a chatbot for the employees, which employees can interact using natural language. We have presented 2 kinds of workflows.
Account creation workflow, where a BPMN (Business Process Modelling Notation) diagram is showed to the employee. As bank or other businesses are more familiar with BPMN diagrams, this is displayed to the user
Interest rate inquiry workflow, where there is not much people interactions are involved. This is displayed as QA session, where employee keeps on entering the details for which information is required and information displayed gets narrower and narrower
The workflows, that are implemented in this prototype are:
Account creation
Amount transfer
Loan grant process
Interest rate inquiry
First 3 workflows displays corresponding BPMN diagrams and 4th one is a series of message interactions
How we built it
We used Facebook's messaging infrastructure to implement this. For NLP based queries, we used defaults queries. We also added few entities in wit.ai to support custom NLP queries. The web hook in hosted in
Heroku
.
Accomplishments that we're proud of
For the message interactions, we created a workflow diagram, using which we created a config file implementing the workflow. Hence, in order to add new workflows, one need not know how the code is implemented. Just create a tree in our format, if new wit.ai training is required, create and train an entity there. In this way, minimal code changes are required for any workflow addition. We could also externalize this workflow creation, so that the core code is not touched
What we learned
Basics of wit.ai
Messenger creation and interaction with a Facebook page
We got to know that once we understood how this works, writing an application is pretty easy with minimal code
What's next for BankTutor
We are planning to create a full blown application, where addition of different workflows is made as easy as possible, so that any admin in a bank can use it with ease
Links:
Code in Github:
https://github.com/ksholla20/bankTutor-messenger-webhook
Webhook on Heroku:
https://pure-cliffs-78206.herokuapp.com/
Messenger Link:
https://www.facebook.com/messages/t/575336899760839
Built With
facebook-messenger
heroku
wit.ai
Try it out
www.facebook.com
github.com | BankTutor | Messenger bot to help bank employees with all the Business process workflows for their complex banking operations | ['Sharath Holla', 'Keerthana R.V', 'Bharath HK'] | [] | ['facebook-messenger', 'heroku', 'wit.ai'] | 123 |
10,494 | https://devpost.com/software/business-elp | BusinessElpLogo
Note: We create this new BusinessElp bot to meet with the Facebook July, 2020 hackathon.
Inspiration
Few years ago I helped a client out to build a Nodejs platform that creates custom bots for his clients Facebook pages. There are of course many online services that does that nicely, but Edwards wants to save money by not subscribing monthly for this services as none of them were free. So Edwards paid me one time to code this out, and then just gets the bots running for any new client in just some click and configuration.
Now to make things even more easier, We thought about creating something of such for all Facebook users inside Facebook. Here comes Business Elp, a messenger bot that helps create a messenger bot for your business and to generate leads!
What it does
Business Elp is a messenger bot that helps you build a fully working messenger bot which helps you engage customers about your service and generate leads.
How We built it
Business Elp is built with Nodejs platform, along with the Facebook Graph API that empowers the action.
Challenges We ran into
The toughest challenge is Facebook graph's permission, it wasn't actually easy to get permissions to some features, which we later come through.
Accomplishments that We're proud of
The accomplishment We are proud of is simply solving the problems of paying to get a simple bot working, with this solution, every Facebook user can create bots for their page for free and without leaving Facebook.
What We learned
This gives us chance to explore more about the Facebook Graph API. To know actually how the Facebook Graph API works and we also explored the Facebook Developers community to learn more about the behavior. We also learned about about graph nodes, page scoped IDs and how Graph could be used totally from Graph Explorer with call API requests manually.
What's next for Business Elp
For now, is just a simple chat flow that has an option to remove (SKIP), the next big thing on Business Elp is to allow users to customize chat flows by:
adding more blocks
customizing lead title messages
adding rooms for conditional chat flow.
Built With
facebook-graph
facebook-messenger
node.js
Try it out
m.me | Business Elp | Facebook Messenger Bot for creating bots for customer support and lead generation. | ['Hakeem Erisan', 'erisan akorede'] | [] | ['facebook-graph', 'facebook-messenger', 'node.js'] | 124 |
10,494 | https://devpost.com/software/covid-19-chatbot-1gxjnf | COVID 19 New Cases Notifications
Inspiration
Currently COVID-19 is a worldwide problem. I designed this COVID-19 chatbot to provide information as quickly as possible to everyone in order to combat the disease
What it does
Chatbot can support providing information 24/7. The updated information includes: number of cases, patient's status, medical report and other updates to support users. In addition, the chatbot automatically sends messages when there are new cases, new details.
How I built it
I built it base on RASA framework with Facebook Messenger.
Challenges I ran into
I face a lot of chanllges when try to develope auto
Accomplishments that I'm proud of
I had a lot of difficulties developing a module that automatically sent messages to customers when there were new cases because RASA and Facebook Messegner did not support this part.
What I learned
I learned a lot from this project, such as: facebook messenger api, rasa framework and nodejs.
What's next for COVID-19 Chatbot
I plan to develop more features and develop multiple languages to support citizens of many countries around the world.
Try it out
m.me | COVID-19 Chatbot | Currently COVID-19 is a worldwide problem. I designed this COVID-19 chatbot to provide information as quickly as possible to everyone in order to combat the disease. | ['Thang Nguyen'] | [] | [] | 125 |
10,498 | https://devpost.com/software/knoxup | Main site
KnoxUp
In Knoxville and Knox County, the Payment-In-Lieu-Of-Taxes (PILOT) program is targeted at the development of property for either jobs creating economic development projects or economic-catalyst projects. In both cases, the goal is to appropriately incentivize business owners and developers to create an economic activity where there was none before.
https://github.com/swest4/KnoxUp
Team
This team shares skills in UX and front-end development with a hint of back-end. Hence the Name "shortStack", they first met while working at Regal Cinemas.
Team Name: shortStack
Team Table: 13
Available Scripts
In the project directory, you can run:
yarn start
Runs the app in the development mode.
Open
http://localhost:3000
to view it in the browser.
The page will reload if you make edits.
You will also see any lint errors in the console.
yarn build
Builds the app for production to the
build
folder.
It correctly bundles React in production mode and optimizes the build for the best performance.
The build is minified and the filenames include the hashes.
Your app is ready to be deployed!
See the section about
deployment
for more information.
Built With
css
html
javascript
react
Try it out
knoxup.net
github.com | KnoxUp | KnoxUp is an archive of projects related to the Pilot program. There are three different ways to view the data on each project. You can choose between list, timeline and map view. | ['Shane West', 'helloidevthings Hirst', 'Lance Jernigan'] | ['Data Challenge: City of Knoxville', 'Fans Favorite', '1st Place'] | ['css', 'html', 'javascript', 'react'] | 0 |
10,498 | https://devpost.com/software/scootlib | Inspiration
The inspiration for this application stems from the use of the team's frequent use of scooters. We had many problems with our commutes as well as finding adequate parking areas due to restricted infrastructure. We hope that this application can help the City of Knoxville direct their efforts in helping those who frequent the use of scooters in the Scruffy City.
What it does
ScootLib comes with the feature to display scooter transit routes via a heat map as well as a feature to view clusters of endpoints that display areas of high-volume destinations. Conclusions that can be drawn from the maps include:
What routes do knoxvillians enjoy scooting the most
What routes are dead spots for scooter traffic and why that might be
What areas could we implement more for scooter safety
Mappings to solve issues of scooter parking locations
Points of interest that contain high scooter traffic
Area where scooters should likely be moved to for optimal use
How we built it
Heroku -> Node.js + Express.js -> Map API’s -> Website (HTML, CSS, JavaScript)
To host the website for free, we used Heroku to service a web app. We decided on Heroku because Heroku provided many out-of-the-box solutions and also has the capability for full-stack development with Node.js. For the frontend, we decided to use Twitter Bootstrap for ready-to-use CSS classes. For the backend we used express.js to help communicate with our backend to provide database accessibility. Lastly, we used the Google Web API paired with the given Knoxville Dataset to help populate and provide meaningful information to our web application.
Challenges we ran into
Some of the problems that forced our team to stretch further than expected was trying to render and configure the Google Maps API on our website, but we overcame that through spending copious amounts of time analyzing the documentation. Also as students, we never experienced such a high volume of data so it did take a lot of learning to be able to manage the data.
Accomplishments that we're proud of
Our team delivered more than a minimum viable product that was able to clearly and efficiently portray the City of Knoxville’s scooter data in an easily digestible manner. Moreover, we were able to analyze the data into nodes and points of interest to help draw conclusions that otherwise would not be evident. Furthermore, my group was able to manage data that was well over what we would consider in our comfort zone. Lastly, we were also proud of the fact that we built an application that has the potential to solve some of the problems that we have on a daily basis.
What we learned
We learned a variety of skills relating to front-end and back-end development such as html/css, Bootstrap and Express. Furthermore we learned more about API work, as well as more advanced javascript. We also learned a lot about managing large data sets. Furthermore, we learned a lot about how to use the Google Maps API as well as working with GeoJSON data.
What's next for ScootLib
Scootlib looks to expand upon and draw more conclusions from the data currently available. We look to add algorithms that expand upon where scooter users were intending to visit as well as increasing the data capacity of our website while maintaining its efficiency. A potential idea would be to use the Google Places API to find the most popular point of interest for every cluster of scooter parkings.
Built With
bootstrap
css
express.js
google-cloud
google-maps
heroku
html
javascript
node.js
Try it out
lendingteamutk.herokuapp.com | ScootLib | ScootLib is designed to offer the City of Knoxville a simple, yet elegant solution to viewing their scooter transit data. | ['Rephael Congmon', 'Kishan Tailor', 'Tyler T Nguyen', 'Abhi Ravi'] | ['2nd Place'] | ['bootstrap', 'css', 'express.js', 'google-cloud', 'google-maps', 'heroku', 'html', 'javascript', 'node.js'] | 1 |
10,498 | https://devpost.com/software/c19 | State overview of C-19 with local news below
State demographic data visualization
Trending news regarding Covid-19
County view
Our logo!
Inspiration
We have always wanted to take on a data visualization project and now seems like the right time and place with
Covid-19
. Especially so, since there are so many different lenses that we can apply, analyze, and learn from.
What it does
C-19
is a data aggregation and analysis tool that provides insights into the evolution of Covid-19 within the state of Tennessee. It utilizes many different lenses such as: news sources, demographics, mobility reports, and time series data. Not only is it a great place to learn more about Covid-19 and how it is spreading within the state of Tennessee but also it may be used as a tool for potential policy-related decisions.
How we built it
We used many tools to build
C-19
. The dashboard was built using Angular framework with a back-end consisting of Firebase and Express.js. An integral part of our website’s functionality comes from many useful APIs. One such API was the RDS API, which allowed us to interact with a multitude of datasets (Google Mobility Reports, Tennessee Health Department data, and Knoxville Health Department data) with ease. Furthermore, Google Maps API combined with the power of OpenStreetMaps allowed us to construct a custom GIS experience. Last but not least, we utilized News API to easily query Covid-19 related data in JSON.
Other than the tools -- a restless night with a steady supply of caffeine helped us pull through!
Challenges we ran into
When developing the Angular frontend, we ran into problems regarding connecting to our Firebase databases and dealing with concepts such as Promises and Observables. In addition to problems on the frontend, when we attempted to use the official RDS Javascript SDK in a Node.JS environment, we faced many errors. Discussing our issues with one of the actual SDK developers showed us that it was just not possible to use it in a Node.JS environment. Instead, we had to craft our own rudimentary HTTP functions to get our RDS data.
Accomplishments that we're proud of
Ankush:
Personally, my proudest moment during the whole experience was converting over 100,000 geographic coordinates into polygons and sticking it onto a map! It was really satisfying being able to design county boundaries with a fine granularity and to be able to interact with each individual county.
Vijay:
The proudest moment for me would be when all of the database we had been requesting from RDS seamlessly flowed into our Firebase database. It was made
even
better by the fact that we formatted the data in a way so it was incredibly easy to visualize the data with the graphing library we were using (Chart.js)!
What we learned
Ankush:
More than I wanted to about handling asynchronous data.
Vijay:
I learned a lot about Express.js as well as how to deal with Angular imports (struggled to install Chart.js)
What's next for C-19
After the competition is over, we want to go back and polish up C-19 because the insights and experiences that we gained from designing this tool were invaluable. Hopefully, we can keep our tool running for others to see and use!
Built With
angular.js
express.js
firebase
google-maps
javascript
json
material-ui
openstreetmap
python
rds-api
typescript
Try it out
knoxcov-401fd.web.app | C19 | An all in one experience for tracking Covid-19 through demographics, mobility, news, and time. | ['Ankush Patel', 'Vijaysrinivas Rajagopal'] | ['3rd Place'] | ['angular.js', 'express.js', 'firebase', 'google-maps', 'javascript', 'json', 'material-ui', 'openstreetmap', 'python', 'rds-api', 'typescript'] | 2 |
10,498 | https://devpost.com/software/covid-19-mobility-tracking | Inspiration
With modern times requiring new social norms due to Covid-19, one major issue today is maintaining social distancing, limiting spread of the virus, while still supporting local businesses. Today due to the large number of mobile devices there is plenty of time specific information on the amount of foot traffic that an individual location receives, however this information is usually hidden away in major applications such as Google Maps. Therefore, we thought to build an app that would make it easier to look at what times are certain locations within knoxville are popular to foster a decision make process centered around encouraging travel to these locations during less popular times in order to avoid congregation of large crowds and potential spread of the virus.
What it does
Covid-19 Mobility Tracker is a way to plan trips out for groceries or restaurants while making conscious decisions to avoid peaks. The app is designed so that people can see at what times locations are busy and make a conscious decision to go out at times that they are less busy.
How we built it
Our project is built on a Flask web server to handle all the data processing and formatting to be useful for the frontend. The backend is service-oriented so the only 2 functions are: send the index.html to the browser, and respond to API requests. The frontend uses VueJS.
Challenges we ran into
The largest challenges we ran into was getting the mapbox API's working. Data processing and formatting were also a challenge as it pulled from many online data sources that required separate formatting processes.
Accomplishments that we are proud of
The individual mobility data is represented on the map and easily viewable.
What we learned
We realized that there is a treasure trove of data online involving the ongoing COVID-19 pandemic that is largely hidden and difficult for the public to see. We realized that large data sets are only a few goggle searches away and that there are many tools available to present this data.
What's next for Covid-19 Mobility Tracking
The hope would be to add in better data analytics and to use the data here to predict future trends to allow people to make better decisions on when it is the best time to head out while avoiding the crowds.
Built With
leaflet.js
mapbox
python
vuejs
Try it out
knxhx.is.mediocreatbest.xyz | Covid-19 Mobility Tracking | Know where to go to avoid the crowds | ['Tanner Hobson', 'Michael Haines'] | ['Data Challenge: COVID-19'] | ['leaflet.js', 'mapbox', 'python', 'vuejs'] | 3 |
10,498 | https://devpost.com/software/sweet-16-scooter-traffic-analytics | Just all trips on one map
Why trips are in the building? again data quality?
This where people ride scooter!!
Usage of different hours in total and broken down by day of the week
Weekday vs. Weekend Usage, in general weedays > weekends
More longer trips in midnight! - trajectory length vs hour in the day
Wednesday trips
Saturday trips
Trips are centered around
That where scooters are missing!
10 clusters for start points for the entire data
Leisure or utility?
Inspiration
Micromobility is a new global trend empowered with locational technologies.
What it does
Help analyst to draw actionable insights from the automatically collected data.
How we built it
Opensource
Cloud
Data Science
Challenges we ran into
data formats
software bugs
Accomplishments that we're proud of
Data processing pipeline capable of assimilating large data volumes.
What we learned
Getting usable local high-resolution infrastructure data is hard
but you can compensate with advanced analysis for the lack of the data
What's next for Sweet 16: Scooter Traffic Analytics
some sleep and debriefing
Built With
docker
geopandas
jupyter
pandas
postgis
python
qgis
Try it out
gitlab.com | Sweet 16: Scooter Traffic Analytics | Where can a scooter go? | ['Alexandre Sorokine', 'Forrest Shriver', 'Fan Zhang', 'Mark Coletti'] | ['Data Challenge: Shared Micromobility and Infrastructure'] | ['docker', 'geopandas', 'jupyter', 'pandas', 'postgis', 'python', 'qgis'] | 4 |
10,498 | https://devpost.com/software/r-agamuffin-municipal-scooter-data | Map view of most popular scooter pickup areas
Hourly Usage in a bar graph view
Scooter distances cross referencing distance travelled with place where scooter was found
Scooter distances cross referencing distance travelled with place where scooter was left
Inspiration
Our goal was to learn more about how these scooters are used, and when and where they are in most demand.
What it does
It analyzes data about scooter time and location
How I built it
In R studio, using data analysis based on the provided Excel spreadsheet
Challenges I ran into
We started with three people who didn't know R very well, and ended with four people who are ok at it.
Accomplishments that I'm proud of
Learned a new language and got some interesting graphs in a short period of time.
What I learned
R
What's next for R-agamuffin Municipal Scooter Data
Lunch
Built With
r
shiny
Try it out
shermtech.shinyapps.io | R-agamuffin Municipal Scooter Data | Scooter Analytics | ['Thomas Morgan Jr.'] | [] | ['r', 'shiny'] | 5 |
10,498 | https://devpost.com/software/tinus-lorvalds-38gjhd | As part of their efforts to build community involvement and highlight involved citizenship, the Office of Neighborhoods is working to compile an online database of Neighborhood organizations and their contact information. Team Tinus Lorvalds has attempted to address this need by creating a public-facing form that allows a visitor to search for relevant neighborhood groups as well as an "employee-facing" admin application that provides for the easy and convenient adding, editing, removal, and focused searching of contacts via private contact information.
Try it out
github.com | Tinus Lorvalds | Public-facing form that allows visitors to search for neighborhood groups and "employee-facing" admin app that provides for adding, editing, removal, and searching of contacts via private contact info | ['Soofi Punjani'] | [] | [] | 6 |
10,498 | https://devpost.com/software/ourcorona | Inspiration
Data overload is common when it comes to looking at COVID-19 statistics. We noticed that COVID-19 data is somewhat imperfect and has already been sliced and diced a multitude of different ways by various sources, but that depicting the data on such grand scales often diminishes the importance of what each number represents and even numb people to the severity of the situation. We want to help personalize this data and bring a humanized aspect to it.
What it does
In our application an avatar is generated to represent each statistical demographic category as a person who has been directly impacted by COVID-19. To relate a face to statistics, the application displays some simple data that pertains to that sex and age group, hopefully helping the user to empathize with the data and encouraging them to do their part to reduce the spread of COVID-19.
While the interface and statistics are simple they allow a user to quickly understand how people like them or their loved ones are affected rather than overloading them with big and un-relatable numbers.
How we built it
We chose to build our project in Framer Web, a design and code hybrid tool that integrates React components to produce functioning code prototypes capable of data fetching and user interaction. Our team has experience with Framer’s desktop app, but we wanted to try a new approach with the new Framer Web technology because it gave us an interesting way to collaborate live on code and design. As a team with a designer, Framer gave us a way to work better together since it included design and code in a way that was manageable for both the people familiar with code and our designer. Framer web also gave us the benefit of easily allowing us to collaborate remotely, something especially important during a pandemic.
Challenges we ran into
One of the biggest challenges was diving into new technologies that we weren't as familiar with. While Framer is a great prototyping tool, we ran occasional code sharing conflicts in their workflow.
Accomplishments that we're proud of
Researching and building a useful tool - entirely remotely. We really hope that this can be a useful tool to help people evaluate the world around them.
What we learned
That there are a lot of factors that impact Covid-19 spread.
What's next for OurCORONA
The next steps for our application would be to increase empathy by generating a name for the face and relating the stats to the name since a name is more personal than just a face.
Many COVID-19 charts gloss over projections making users look more into “What are my chances of getting COVID today?” instead of “What are my chances of getting COVID in in the next few if we continue on this path?” When overloaded with data, it is easy to overlook that the rates will compound if preventative efforts are not made to slow the virus. We believe giving them a forecast of their risks will increase their determination to take the proper safety measures.
Another track we want to explore is estimating how likely community spread might impact us through the people that we care about. This approach is explored in an ObservableHQ notebook that we developed while exploring the data.
Built With
framer-web
javascript
react
richdataservices
Try it out
framer.com
observablehq.com | OurCORONA | To better understand the risks of Covid-19 the data needs to be humanized | ['Jesse Vomfell', 'Janna Curtis', 'Thad Thompson', 'Kayleigh Bray'] | [] | ['framer-web', 'javascript', 'react', 'richdataservices'] | 7 |
10,498 | https://devpost.com/software/noronago | main interface
showing that monday is better than saturday
Inspiration
I still need to go grocery shopping, or want to go out with friends, but I don't want to be there with a crowd. When should I go to minimize crowd contact?
What it does
You have a schedule, we don't need to know it all, but you tell us where you need to go and what times you're available, and our service tries to pick out the least popular times to suggest in order to minimize contact risk.
How we built it
The backend is written in Python, using various APIs such as Google Maps data and python data projects like pandas.
The webserver is written in Flask for ease of integration, which serves a bootstrap frontend with a simple interface for searching for a time and place.
Challenges I ran into
Google Maps popularity data is not a native API endpoint from google
Accomplishments that I'm proud of
What I learned
What's next for NoRonaGo
If the project sees demand, we plan to incorporate the most requested features first.
Including other APIs and data sources is a high priority since "popularity trends" may not always be a good metric for gaining insight about currently happening events. Additional APIs could provide information like:
Reported cases of workers at X, in order to avoid X for N days after to allow sanitization
Events attracting in-person crowds, in order to avoid nearby affected locations
Traffic flow patterns, potentially in realtime, in order to react to more up-to-date crowd trends
Expected user facing feature requests include:
Ability to plan multiple destinations in one trip (fairly advanced)
Ability to filter places based on accommodations like "dine-in outdoors only" or "senior hours"
Built With
bootstrap
flask
google-maps
python | NoRonaGo | When do you go out to avoid contact risk as effectively as possible? | ['Ben Klein', 'Aiden Rutter', 'Jonathan Bryan', 'Cameron Adkins'] | [] | ['bootstrap', 'flask', 'google-maps', 'python'] | 8 |
10,498 | https://devpost.com/software/knoxville-neighborhood-portal | Neighborhood Directory View
Neighborhood Organization Detail View
Add a Neighborhood
Search
Search Results
Resident Directory View
Newsletter Mailing List
Resident Detail View
Add a Resident
Inspiration
We chose this project because we were excited about the chance to build our own database and improve our skills in creating an interactive full stack application.
What it does
The Neighborhood Portal is an app that allows users from the Knoxville Office of Neighborhoods to manage and view data related to neighborhood organizations and their resident members. The public can also use the app to view basic information on neighborhood organizations.
How we built it
We created our application using the Django framework for Python. We used Django ORMs to query our SQLite database, and team members built out front end templates as well as back end views. The app is styled with CSS.
Challenges we ran into
Our team is comprised of juniors who are fairly new to coding, and we weren't initially prepared to handle the extreme time constraints. We spent too much time early on discussing possible directions that ultimately could have been used more wisely on feature implementation.
Accomplishments that we're proud of
This is our first hackathon, and we're all really proud to have a finished, fully functional app to show.
What we learned
Better time management, how to incorporate JavaScript into Django templates, how to build a search feature in Django, that there is a rewarding feeling on the other side of powering through moments where you feel lost, and that we are capable of more than we think sometimes
What's next for Knoxville Neighborhood Portal
Full CRUD with editing and deleting for neighborhood organizations and residents, more styling, and a map feature
Built With
css3
django
html
javascript
python
sqlite
tableplus
Try it out
github.com | Knoxville Neighborhood Portal | A portal for city neighborhood officials to manage their database | ['Matt Kroeger', 'Cooper Nichols', 'Katie Wohl', 'Alyssa Nycum'] | [] | ['css3', 'django', 'html', 'javascript', 'python', 'sqlite', 'tableplus'] | 9 |
10,498 | https://devpost.com/software/pincity | Inspiration
Allowing the city to communicate with it's residents in a location-based medium.
What it does
Allows visitors to anonymously post messages on particular locations to be viewed by tourist, residents, or city officials.
How I built it
This is a simple website using the google maps api. I hacked up what I could to add a hud, text box, means for posting pins and a running feed on top of the map.
Challenges I ran into
Recieving coordinates from the mouse's position.
Creating a custom cursor.
Doing everything I wanted.
Accomplishments that I'm proud of
I think the confirm post interface looks pretty slick.
What I learned
More of what's possible via the GoogleMaps API and cursor styles.
What's next for pincity
This is the essence of pincity. Scaling and adding more information is incredibly possible. With city-official users, they have the chance to include any data they deem necessary for enjoying a day downtown.
Built With
javascript
Try it out
pincity.herokuapp.com | pincity | A location-based social network for communicating about points in the city while providing the means for city official feedback. | ['Jacob Sides'] | [] | ['javascript'] | 10 |
10,498 | https://devpost.com/software/knoxville-hazards | KNX NBHD
KNX NBHD is your new way to know what is going on in Knoxville! Use the maps to learn what hazards there are around town, crimes that have occurred, fun community events, and, relevant to current times, information on covid in the Knoxville area! With our easy to use crowdsourced interface, the Knoxville community can kept up-to-date in real time!
link
Inspiration
It is important to stay in touch with your local area and be aware of what is going on in your community. With 50% of our team growing up in Knoxville, we know how difficult it can be to find out what is happening in the area, especially finding all the information you need in one place. Occurrences such as cable and internet issues can be difficult to pin point. Is it just you? Or are your neighbors having the same issue? Maybe there is black ice on the roadway in the winter. Let others know they may not want to go that route! Or even want to encourage your children's young entrepreneurial spirits? Wouldn't it be great to have a way to spread the word about their lemonade stand? KNX NBHD would be a solution to get information quickly to the community and have all information grouped in one place.
Learning Experiences and Challenges
As a team we learned the ins and outs of web-development, java script, and use of multiple API platforms. 3/4 of our team did not have previous experience with this type of project. This posed a great challenge for trying to learn the necessary tools and create a functional, presentable project in the time given. Specific challenges we faced were integrating the database platform to the website, as well as, manipulating embedded maps to perform in the specified manner.
Future
If we were to continue to develop this website, then there are a few different things that we would do to improve it. Firstly, we would add a way for users to ask for help from others in the Knoxville community. From simple things like tech trouble or even tutors to bigger things like tearing down houses, it would be a great way to find help from your fellow Knoxvillians. Another thing we would implement is location services. This would allow users to submit a post without having to specify their location.
Built With
bootstrap
css
firebase
google-maps
html
javascript
leaflet.js
raspberry-pi
Try it out
github.com
raspi.servebeer.com | KNX NBHD | KNX NBHD is your new way to know what is going on in Knoxville through our user-friendly, community-sourced platform! | ['Cristian Romo', 'Heather Haynie', 'Braxton Haynie', 'BranchManager'] | [] | ['bootstrap', 'css', 'firebase', 'google-maps', 'html', 'javascript', 'leaflet.js', 'raspberry-pi'] | 11 |
10,498 | https://devpost.com/software/city-stream | Event List Page - see upcoming and current live events
The livestream page - view current livestreams or add your own!
About
City Stream 865
is a React web app developed for the KNXHX 2020 Knoxville City Hackathon.
City Stream 865
allows users to see a list of events currently happening in the city of Knoxville. Users can then either select an event to see live streams provided by individuals at the event, or add their own stream for others to watch. The user can easily swap between different streams for the same event to get a full picture of the event as it happens.
This app was developed by Sai Thatigotla, Spencer Howell, Manny Bhidya, and Fatima Bhidya.
What We Learned
Most of the team had not used React JS to build a website before, and others of us have not had experience using MongoDB and other backend services. We were able to experience full-stack web development and learn a lot.
Technology Used
The UI for the site was developed using React JS, and the backend uses MongoDB. We do some parsing with the Knoxville Event Calendar's
.csv
file to import events to the website.
Build and Run
This project was bootstrapped with
Create React App
.
You will need
npm
as well as
React JS
.
To build this app, first run
npm install
to get dependencies.
Next, run
npm start
to launch the app on localhost.
You should be up and running!
Built With
css
csv
html
javascript
mongodb
react
Try it out
github.com | CityStream 865 | Live in your area - See live events happening in your area through the lens of local live-streamers. Swap streams at any moment to get a full picture of the event. | ['Spencer Howell', 'Sai Thatigotla', 'Manny Bhidya'] | [] | ['css', 'csv', 'html', 'javascript', 'mongodb', 'react'] | 12 |
10,498 | https://devpost.com/software/hackathon2020-whmvzd | TrashBandit
Player with camera and weapon
Current environment
Hackathon2020
Trash Bandit is a game that brings awareness about recycling.
The Trash Bandit website acts like a community leaderboard to support recycling in your community.
The more your community recycles, the more points every player from that community obtains monthly.
These points can be used to get cosmetic items for your character in-game.
Built With
css
html
javascript
tsql
Try it out
github.com | Trash Bandit | Trash Bandit is a game that brings awareness about recycling. | ['James Hooven', 'Blake Childress', 'Brett Willett'] | [] | ['css', 'html', 'javascript', 'tsql'] | 13 |
10,501 | https://devpost.com/software/stampyboi | The home page of Stampyboi. In the bottom right are the options to filter by specific sources, including YouTube, Netflix, or video uploads.
The auto suggest feature.
The results page for the search "eleanor" with results from YouTube and Netflix.
The timestamp selection page. Each time stamp on the right links to the instance of the quote in the video.
What is Stampyboi?
Stampyboi is a tool to help you quickly and easily find the timestamped video clips you're looking for.
Inspiration
Many people, including us, often send funny clips from shows and videos they watch to their friends. But this is normally done by just sending a link to the entire video or clicking around randomly to figure out where exactly the moment you want to share came from. We decided that we wanted to solve this with Stampyboi. Stampyboi takes out all of the difficulty in sharing clips by searching YouTube and Netflix for that target moment.
Features
Easy file uploads
Easy conversion to .gif format
Easy sharing to Facebook, Twitter, Reddit, and other social media
Autosuggester: generated from the Stampyboi's index so that suggestions are guaranteed to return results
Spellcheck: also generated from Stampyboi's index
Word stemmer:
Porter Stemming Algorithm
Stop word filter:
List of stampyboi stopwords
Phonetic matching filter:
Double metaphone algorithm
Usage
Quick Start
Simply type a quote from a YouTube video or Netflix show you're looking for and hit "Search".
Details
Quote search bar: Takes in a quote to query. Includes autosuggest functionality.
"Options" button: Toggles options menu
"About" button: Links to this repository
Options menu: Allows user to narrow your search based on video type.
YouTube source (optional): Allows user to paste in a link to a YouTube video to search. If left blank, the query will be searched against all YouTube videos in Stampyboi's index.
Netflix source (optional): Same as YouTube source.
File upload: Allows user to upload one or more audio/video files to be searched using
speech-to-text
. Can select from file explorer or drag and drop. Currently supported file-formats: wav, ogv, mp4, avi, mov, mpeg.
Stampyboi logo: Returns user to search page.
Quote search bar (top right): Allows user to submit a new general query.
Video result: Shows thumbnail, title, and list of timestamps that match the query. The user can jump to a specific part of the video by selecting the desired timestamp. Selecting the right-hand tab will link directly to the source video.
List of timestamps: Selecting the desired timestamp allows the user to seek to a specific part of the video.
Share this boi (Netflix or YouTube videos only): Allows user to copy the currently selected timestamped link or share the currently selected timestamped link to Facebook, Twitter, or Reddit. YouTube videos also have the option of being converted into gifs.
How Stampyboi works
Stampyboi indexes videos by extracting and storing their timestamped transcripts. When a query is submitted to Stampyboi, it searches its expansive index of over 330,000 videos to find transcripts containing the queried phrase. When a video link is specified, Stampyboi first checks to see if that video is stored in its index. If the video is found, Stampyboi will filter the results to only show that specific video. If not, the video is transcribed, indexed, then searched for the queried phrase (user-uploaded video/audio files are searched and then immediately deleted from the server). That video will now show up in the results when future users make general queries.
Core Technologies
Apache Solr
Flask
YouTube Transcript API
DeepSpeech
MoviePy
Data Sources
YouTube8M
Netflix ID Dataset
Challenges
Above all else, we faced the challenge of learning to work entirely virtually as opposed to being able to meet and work together in person. On previous projects, we would often meet in person to brainstorm ideas and to help each other solve issues in our projects, but this wasn't possible due to the pandemic. This shift was a challenge for all of us.
As far as technical challenges, we had many when it came to collecting the information we needed to fill our Solr index. One of the most important challenges we had was finding a way to store the transcripts so that each word would be associated with a corresponding timestamp without storing a lot of redundant data. It was also very daunting to go through all of the documentation for Solr and figure out which features had the functionality that we were looking for. Even then, it took a lot of work for us to correctly process the response objects from Solr into a usable format.
For Netflix videos, we originally used 8flix, a database of free transcripts for Netflix shows and movies, but its reach was very shallow and it only contained a small number of videos. Midway through the project, we had to scrap this idea and shift to addic7ed, which came with its own problems as it had limits to the number of transcripts that could be downloaded per user per day. For YouTube, we used web-crawlers to access YouTube's transcripts, but these had to go through many iterations before being able to get us the information we needed in a timely manner.
What We Learned
Before this project, none of us had any experience with CSS and designing a website. Stampyboi challenged us to learn this quickly in order to make Stampyboi function exactly how we imagined.
On top of this, we learned how to set up a Solr index and link it to Stampyboi so that Stampyboi would run quickly and smoothly. We learned how to interact with difficult interfaces to get the results we wanted. And most of all, we learned how to work as a group in a completely virtual environment due to the current state of the world.
Roadmap
Moving forward, we hope to expand Stampyboi's searching capabilities to even more platforms, including Hulu, Prime Video, Disney+ and more. On top of that, we will be adding support for languages besides English, whether translated or native. This will expand the database to greatly diversify the quotes our users can find.
Built With
css
flask
html
javascript
python
solr
Try it out
github.com | stampyboi | Stampyboi is a tool to help you painlessly find the timestamped video clips you're looking for. | ['Harrison Jin', 'Michael Cao', 'Tristan A Blake', 'Aimery Methena'] | ['Category Prize: Education'] | ['css', 'flask', 'html', 'javascript', 'python', 'solr'] | 0 |
10,501 | https://devpost.com/software/copcam | Inspiration
On May 25th, an infamous day where an unarmed, nonresisting African American was forcefully murdered by police in Minneapolis sparked both a nationwide protest and our determination to help the social justice cause.
We did more research and learned that roughly 90% of court cases involving police and civilians lack video evidence. This is usually because it was unrecorded, lost, or tampered with. We also learned that the police who killed Philando Castile was not convicted because there was not video recording from inside the car that proved the shooting was completely unprovoked.
This made us convinced we needed to build an app that makes it easier to record police.
What it does
Our app allows users to live-stream video and audio evidence to a secure cloud database with simple click of a button.
Copcam then automatically notifies emergency contacts that their loved ones are encountering police via SMS. It includes their location and a link to view the livestream in real time.
The app logs the location and time when the recording was started to our backend analytics tool. This effectively allows civilians and researchers to create crowdsourced policing data.
How we built it
We used Android Studios, java, and xml to build the app. Youtube’s databases store the videos our users livestream. We use firebase analytics to log user data in our Google cloud accounts.
We utilized the YouTubeApi to create the livestreams, Geocoder and LocationManager to access the user’s location for logging purposes, SmsManager to send automatic messages to emergency contacts, GoogleAccount authentication APIs.
Challenges we ran into
The main issue was where to host the live stream videos. Since this project is not meant to make any money, we needed to have a way to store it with no cost to us. Luckily, by implementing YouTube live streaming we were able to find the perfect solution, that’s both accessible and free.
There were also a host of coding issues that popped up when trying to implement the increasing number of features we had, including: instant text messaging, location saving, retrieving emergency contacts, adding a custom message, and dimming the screen.
On top of this we had to add numerous redundancies to the app so it would be able to handle different situational errors, including: poor internet connection, errors connecting to YouTube, incomplete or inaccurate set-up, or disruptions mid-stream.
Accomplishments that we're proud of
First-of-its-kind app that allows people to have evidence BEFORE the incident. Unlike other apps, with one touch, users can have full functionality. This way, even if the worst happens to the user, their loved ones will already know where they are and what’s happening to them, as well as have the evidence to act on it.
We are also proud to have figured out a sustainable model that allows us to freely make the live streaming accessible to everyone through hosting on YouTube.
We are also proud to say we have reached out to members of numerous social justice organizations and universities, including the ACLU, NAACP, and Harvard University, and received their positive feedback for the app we have built.
What we learned
In this process, we got to become more familiar with android studios and building mobile applications. We gained more experience with using third party APIs to build more complex apps. We also learned how to utilize analytics tools to perform useful tasks.
We also learned about the problem of police brutality itself through talking to various employees of social justice organizations and university professors.
What's next for Copcam
We are working on publishing the beta version of the app to the Google play store.
We are also seeking to get more target users as beta testers to get their feedback. Afterwards, we will start a mass-marketing campaign through leveraging our connections to the ACLU, NAACP, and various universities.
We are also working on building a digital map that interactively displays all of the crowdsource data that we’ve already begun to collect on police encounters.
Built With
firebase
java
xml
youtube
Try it out
github.com | Copcam | Livestream tamper-proof video of police encounters | Loved ones view the encounter in real time | Crowdsource data to better understand policing | Increase police accountability and civilian safety | ['Derek He', 'Ian P.', 'officialrcdevs'] | ['Category Prize: Social Good'] | ['firebase', 'java', 'xml', 'youtube'] | 1 |
10,501 | https://devpost.com/software/dungeon-addventure | Title Screen
Level Select
Tutorial
Lackey Battle
Inspiration
Kids often feel overwhelmed or unmotivated when learning math, partly due to dull, dry pedagogies. Additionally, video game and social media addiction pervades our society, with the pandemic intensifying the problem as people are stuck at home with nothing to do. With these issues in mind, our team, self-dubbed 'WaffCakes', built a mobile app game that seeks to use one problem to solve the other: make math education fun, while also satisfying kids’ need for entertainment in a productive way.
What It Does
Our app can be described as a mix of a dungeon-crawling and flashcard-style game. The goal of the game is to navigate to the bottom of a dungeon-like tunnel blocked at intervals by locked doors.
Secret Tunnel, Secret Tunnel, Through the Mountain
The user starts his or her journey by going through the first door (level), which is addition-based. Within the level, the user’s sprite must decide which doors to enter based on the answer to a randomized addition problem. If the wrong door is entered, look out! A monster appears, shooting fireballs with math problems that the user must solve to defeat it. To beat the level, the user must win a final boss battle.
You beat the boss!
Balance has been partially restored to the world! Now the next door gets unlocked and you can proceed on to harder math problems- namely, multiplication and division. At the end, a mega boss waits, armed with fireballs containing a mix of all the math problems as the ultimate test of kNoWlEdGe.
About the Art
All credit for the backgrounds, boss character animations, doors, and button art go to our uber-talented team member Kelly! We found open source images for the following pieces: the flying enemy, the fireball, and the character.
What We Learned
None of us were familiar with JavaScript or React at the start of the summer. We learned about navigating between stack frames, using hooks to implement state changes, designing a game loop, and more. It was awesome to go through the learning process together! We also learned how to integrate a Firebase authentication and database system into our project. Finally, we leveled up on our Git skills, learning how to properly branch, submit pull request, and resolve merge conflicts.
Challenges We Faced
The main challenge we faced was implementing game play functionality with React Native. We found a great package called react-native-game-engine that helped us with the dynamic parts of the game, but we realized as we were building it that React is not the best framework to use for game design.
Additionally, it was difficult at times to build an app for ios and Android simultaneously; sometimes, style choices looked strange, components didn’t work correctly, or the code would straight up not compile for one of the operating systems.
What’s Next for Dungeon ADDventure
We’d like to expand our game to include more levels and higher-level math concepts, like algebra or geometry. The levels might have to be restructured for this to be done to account for the increased complexity of these subjects.
A feature we really wanted to include but ran out of time for is multiplayer game play, where opponents can compete against each other in speed runs or fireball battles.
Ability of each user to customize his or her character.
Built With
android
expo.io
firebase
ios
javascript
react-native
Try it out
github.com | Dungeon ADDventure | Teaching kids math through games | ['Kelly Shen', 'Esther Yoon', 'Joshua Brown', 'MrZmann'] | ['Category Prize: COVID Relief'] | ['android', 'expo.io', 'firebase', 'ios', 'javascript', 'react-native'] | 2 |
10,501 | https://devpost.com/software/tech-space | Inspiration
There is a lot of underrepresentation and lack of diversity within the tech industry and that is keeping it from reaching its maximum potential which can be achieved by providing equitable opportunities.
What it does
Provides an anonymized way without personal identifying information to screen candidate profiles along with the inclusion levels to maintain a sense of accountability for the companies.
How I built it
I built it using Angular and Firebase.
Challenges I ran into
Learning the entire Angular Framework from scratch was definitely challenging, however it taught me a lot about components and good design fundamentals due to the structure of how angular operates.
Accomplishments that I'm proud of
Building a professional look on the platform
Enabling CRUD functions
Creating a reliable and successful connection to the firebase cloud firestore database
What I learned
Connecting with Database
Building a front-end web application.
What's next for Tech-Space
Live matching portal for mutually expressed interest between recruiters and candidates
Individual dashboards for each of the users with different account permissions.
Built With
angular.js
bootstrap
css
firebase
html
Try it out
github.com | Tech-Space | An Inclusive Job Search Portal | ['Tabreek Somani'] | ['Category Prize: Economic Relief'] | ['angular.js', 'bootstrap', 'css', 'firebase', 'html'] | 3 |
10,501 | https://devpost.com/software/chromecomments-9d6ou4 | Inspiration
We wanted our project to make users’ internet experience more convenient. While some websites have places for users to make comments, most do not, so we decided to create a common forum that works on any website.
What it does
ChromeComments allows users to make comments on any webpage, even ones where users would not usually be able to make any comments or remarks. Users will be able to communicate with others on important events and issues.
How I built it
HTML and CSS for the popup
Javascript for frontend development
NodeJS used for backend development
MongoDB used to store user data, including user comments, user friends, etc.
AWS used to host backend server
Challenges I ran into
Lack of knowledge of the languages used to build the product solved by learning through the internet and our assigned mentor, Mr. Gullo.
Lack of knowledge on how frontend and backend teams interact solved by our assigned mentor teaching us about his experience heading coding teams.
Accomplishments that I'm proud of
We’ve been able to connect users on the internet in places where they normally would not be connected
We were able to accomplish the goals that we set for our project at the beginning of the project
What I learned
Some of our members learned Javascript, HTML, CSS, and Python. We also learned how coding teams work together from front to backend. In addition, we learned how to integrate AWS into our project, so that it did not have to run on a localhost.
What's next for ChromeComments
We’d like to add more functionality to the extension popup, including allowing a user to comment on a specific part of the webpage similar to Google Docs.
Polishing up the styling so that the extension is consistent across all its pages.
Adding a homepage
Built With
amazon-web-services
css
html
javascript
mongodb
node.js
Try it out
github.com | ChromeComments | A way for users to make comments on any webpage of their choosing and have discussion anywhere on the internet. | ['Ishaan Guha', 'Shrenik Porwal'] | ['Category Prize: Entertainment/Social Media'] | ['amazon-web-services', 'css', 'html', 'javascript', 'mongodb', 'node.js'] | 4 |
10,501 | https://devpost.com/software/jarvis-2-0-i1b8vo | Inspiration
Iron Man’s AI assistant, Jarvis, in the Marvel Cinematic Universe (MCU) was the main inspiration for our product. We wanted to create a way for users to easily access and interact with their favorite applications in one dashboard without having to touch their mouse. We hoped Jarvis 2.0 would increase accessibility to technology, as well as change the way we interact with our machines.
What it does
Jarvis acts primarily as a personal assistant! Jarvis can be used to access the modern day necessities: emails, music, time, and calendar. Given the current pandemic, we included a COVID-19 widget to inform users about cases and trends in counties and countries. Jarvis allows its users easy access to these necessities through mouseless control.
How we built it
For our hand motion detection, we used a Leap Motion Controller. With UltraLeap’s built in library, we were able to track the coordinate information of various joints, fingers, etc. Taking these coordinates, we created an LSTM model in PyTorch to act as a classifier for various hand gestures.
For the backend of our apps, we used APIs to retrieve data necessary for Jarvis’ operation. Specifically, the APIs obtained data from Spotify, Gmail, Google Calendar and OpenWeatherMap. To create the Corona app, we used Pandas to pull data from .csv files provided by Johns Hopkins, New York Times and Data Package Core Datasets on Github*. Our time app required the Python time library. In addition, we used various Python libraries such as BeautifulSoup and PySpellChecker to create an auto-corrector for the Corona app.
Jarvis’ GUI was made primarily in QML, due to the language’s compatibility with a Python library, PySide2, a Python wrapper for the C++ Library Qt. We used Figma to design all of Jarvis’s buttons and frames. We also used Blender to render a 3D video loop of blue electricity to serve as the background.
Due to the nature of Jarvis, many API requests are needed to initialize Jarvis. To optimize our initialization time, we used the Python threading library.
Link for Core Datasets
Link for Johns Hopkins datasets
Link for NYT COVID-19 datasets
Challenges we ran into
Our first major challenge was determining which programming language we should use for the front end. After a few weeks of research, we decided on QML for two reasons. One, QML can run as an app, independent from an internet browser. Secondly, Python and Leap Motion can be easily integrated into QML. Since UltraLeap required Python 2.7 and GUI required Python 3.7, we used a Flask server to act as an intermediary between the two. From a broad perspective, the coordinate information and ML features would be sent to the server via POST request, the server would process and store the necessary gesture and hand position coordinates, and finally the GUI would use a GET request to receive the necessary information.
While implementing our apps, we dealt with lag issues caused by large API requests. In order to decrease the lag in our front end, we optimized our initial requests to retrieve only the data that the user sees, and allowed the user to further choose what specific information they want to see inside of an app. We added threading for the initialization in order to reduce startup times.
The LeapMotion controller itself also had its own set of issues. For example, if I closed my fist, sometimes not all fingers would be placed down and thus throw off the model and therefore the corresponding action as well. This problem tended to magnify as more processes were running. As a result, we reduced our number of gestures to reduce the scope of this issue. Though the problem still remains, it was more manageable to work with.
Accomplishments that we are proud of
One of our most important steps was actually bringing together individual widgets to create a single user interface. One really big moment that we were happy with was finally creating a dashboard that encapsulated all the widgets. By bringing everything together, we’d finally created one of the most important parts of our minimum viable product, and from there, we could work on editing and adding to our prototype.
Our teams’ collective skills were mostly focused on the backend. Another particularly great moment was creating and implementing the electricity video (the animated dashboard background) using Blender.
Finally, another of our favorite moments was when the LeapMotion controller manipulated the GUI successfully the first time. At the time, the model was a bit shaky, and though the interface was coming together, the hand tracking portion had some eccentric behavior. Nevertheless, this culminated into a better sense of accomplishment when everything was getting put together.
What we learned
Going into SummerHacks, several members of the Jarvis 2.0 team were fairly new to coding, so there was a significant learning curve. As a result, a lot was learned. First, several APIs were implemented into the creation of the widgets on the user interface. To do this, we had to learn the APIs and how to handle queries and format the received data. Furthermore, our team’s experience was mostly in the backend. Because we had a display interface, many of us worked seriously in the frontend for the first time. As part of this, we spent a lot of time familiarizing ourselves with Figma for the static elements and Blender for the 3D animations.
Our team spent a lot of time working, both on Jarvis 2.0 and on our individual projects, research, classes, and internships. We wanted to use this SummerHacks to learn and work on a fun project we’d be proud of. In these last few months, we’ve gotten better at balancing our work, and incorporating fun into the process. While we learned a lot of important coding skills, and improved many more, the soft skills we developed were just as important. As a team, we’ve gotten stronger at communicating our needs and our processes, and sustaining team morale. I’m really proud at how we continued to power through such an extended project.
What's next for Jarvis 2.0?
The broad goal for Jarvis 2.0 is to provide a highly accessible daily aid. First, gesture tracking is an extremely powerful tool, and it would be amazing to be able to incorporate sign language to allow for even greater accessibility in interaction. It would challenge the way we interact with technology in our spaces, using language and movement in place of touch. We would like to consolidate the gesture tracking model and the LeapMotion into a small, portable device separate from the user’s local machine so that the quality of gesture prediction is not dependent on the user’s computational power. Implementing NLP would also further this goal for a number of reasons. It would allow for a truly hands free experience, not only increasing accessibility but also ease of use. Furthermore, integrating an audio visualizer along with NLP would create another dimension for visualizing this function and bringing more life to Jarvis 2.0.
We would also like to expand the number of Jarvis 2.0’s widgets and add extra functionality to the widgets. For example, we could take advantage of the Spotify API’s more advanced features to allow our client to search for songs with a specific beat, feel, or timbre. For the Coronavirus widget, we plan on adding geographical information about the nearest testing centers and (in the future) vaccination facilities. We especially want to incorporate educational tools such as a digital whiteboard and slide presentation widget. With Jarvis 2.0’s hand tracking capabilities, educators would have the freedom to move around the classroom and engage on a more personal and dynamic level with students rather than remain confined to a single and generally distant location.
Built With
blender
flask
google
leap-motion
pyside2
pytorch
qml
spotipy
werkzeug
Try it out
github.com | Jarvis 2.0 | An Iron Man inspired mouseless dashboard. | ['Sahil Jain', 'Sunny Li', 'Conrad F Li', 'Matthew Alain De Guzman'] | ['Category Prize: Health/Medicine'] | ['blender', 'flask', 'google', 'leap-motion', 'pyside2', 'pytorch', 'qml', 'spotipy', 'werkzeug'] | 5 |
10,501 | https://devpost.com/software/learning-alliances | Homepage Design Mockup
Mood-board Inspiration
Inspiration
The cancellation of summer schools as a result of COVID-19 has impacted the learning for children in middle school. This situation is exacerbated for parents that have been laid-off, making it difficult for them to afford private tutoring for their kids. COVID-19 has also resulted in loss of community service hours for high schoolers which form an essential component of their college applications.
What it does
Learn Inplace provides a platform to connect middle schoolers that are in need of free/low-cost tutoring with high schoolers that are available to provide that low cost tutoring service in exchange for being credited volunteer hours to bolster their college applications.
How we built it
The frontend was done with HTML, CSS, and JavaScript. Then after the students and tutors register, their information is stored in a MongoDB database with the help of mongoose. We also used Node.js as a server and Express.js to handle our requests and routing.
Challenges we ran into
Some technical issues we had were sending the pdf and image along the routes because those are special cases that must be accounted for, and the POST request must be set specifically. In addition, connecting the tutor and student information to the backend was an issue as well.
Other issues that we faced were that we were all based in different time zones and had our own schedules, so sometimes communication and syncing up our schedules were difficult. Furthermore, we worked with technologies that we were not familiar with, such as OAuth. We had to teach ourselves and research how to work with things we were unfamiliar with. We also faced an efficiency issue with oAuth sign in, where we originally iterated through 2 databases before completing sign in to verify. This was resolved by creating two separate sign in routes and passing parameterized information to the call in order to determine user type for a single database access.
Accomplishments that we're proud of
We were happy that we could learn new technologies and have a project that works during these trying times, in addition to working with a nonprofit!
What we learned
We learned about different databases and hosting platforms in our research. We also learned how to use MongoDB as our chosen database and Google OAuth for user login.
What's next for Learn InPlace
We have some UI/UX designers on our team from our nonprofit, so we want to integrate her designs that she just gave us. We attached some of the images to scroll through too!
Built With
ajax
css
express.js
google
handlebars.js
html5
javascript
jquery
mailgun
mongodb
mongoose
node.js
Try it out
github.com | Learn Inplace | COVID-19 has impacted students as some struggle with learning online, and others can't volunteer for their college applications anymore. Learn Inplace will connect these students together. | ['Michelle Van', 'Sameer V Haniyur', 'Prakruthi DR'] | [] | ['ajax', 'css', 'express.js', 'google', 'handlebars.js', 'html5', 'javascript', 'jquery', 'mailgun', 'mongodb', 'mongoose', 'node.js'] | 6 |
10,501 | https://devpost.com/software/opengd | Inspiration
We’ve identified an important issue where in situations that have potential gun violence or armed gunmen like mass shootings in schools, first responders aren’t notified quickly enough and are slowed down by a lack of information on the exact location of the threat. For example, where a gunman is located somewhere in a large building or campus. To address this problem, we propose a fast, accurate, and inexpensive automatic gun detection system using computer vision that is capable of being hooked into existing CCTV security systems. This way, when the system detects a gun, security personnel can be quickly notified to verify the potential threat.
What it does
Currently, we can achieve gun-detection at around 82 FPS on a standard NVIDIA 2080TI which means that a single consumer level GPU is currently capable of processing 8 simultaneous video streams at around 10 FPS which is perfectly adequate for detection purposes. We provide audio and visual warnings for any security personnel who are monitoring the feeds and we also provide a large degree of customizability on how detections are recorded, how video feeds and detections are displayed, and where the detections are streamed to or shown. We also packaged the product into a Docker image that can be easily deployed to systems with support for IP camera sources.
How we built it
Using YOLOv4, we started by training with around 3000 handgun images annotated by a team at the University of Granada. From here, we realized that the model detected far too many false positives, so we used a bootstrapping technique to add over 5000 hard negative images. Essentially, we would run our model on large and diverse datasets of non-gun images and add to our training dataset the images that our model predicted as containing guns with high confidence. Next, we added in around 2000 synthetic images from Edgecase.ai to further improve our model. These images were made up of 3D models of people holding guns in a wide variety of environments and lighting conditions. However, this led to an issue of reality gap where the model is trained on images that don’t exactly reflect reality. To mitigate this, we pretrained on the synthetic data first and selected the weights with the highest performance before continuing to train on purely real data. We then annotated and trained on additional real-world images from Google Open Images and random video clips online that contained people holding guns. Through the process of around 30 training/testing rounds with different data combinations, hyperparameters like network resolution and batch size, as well as different types of data augmentations like mosaic and cutout, acceptable real world performance was achieved with a mAP of 98.53% on a validation dataset of 299 gun images and 935 hard negative images.
Challenges we ran into
In terms of ongoing challenges, our model still struggles with guns that are farther away. While this can be mitigated by increasing the resolution at which the feeds are processed. We found that this wasn’t worth the performance trade off as it would make more sense to just add more cameras for greater coverage as cameras are relatively cheap. The small increase in accuracy would simply not be worth the cost in processing speed. While we succeeded in reducing false positives a great deal and a mAP of 98.53% may sound impressive on paper, in the real world, since guns are an infrequent occurrence, the percentage of false positives to true positives will remain quite high. To mitigate this, we proposed the red-alert system. In our testing, we found that in most cases, false positives only occur for one frame or so. Therefore, by only generating a red alert when there are multiple positive detections in a short period of time, we can significantly reduce the percentage of false positives. Additionally, there are some issues on privacy where questions of who can access these security streams and associated data need to be addressed. Finally, there’s an issue where a system like this may cause security guards to be more lax much like people sleeping in a self-driving Tesla on a highway. We mitigate this somewhat with our auditory alert feature.
Accomplishments that we're proud of
We succeeded in achieving our goal of creating a performant real-time gun detection system that can help lower the response time to potential gun violence and affordably increase the security of soft targets. In our research, we did find a few other companies trying to solve this problem as well. However, we found that these companies charge a great deal of money for these kinds of systems which is self-defeating as oftentimes the people who need more security the most are the ones who can’t pay the expensive prices. Therefore, by creating an open source solution, we can hopefully bring affordable security to a much larger audience.
What's next for OpenGD
A GUI to replace the configuration file for better usability
A companion app or system to notify a security company or police when a gun is detected.
Multi-GPU support for running this software on servers with more than one GPU is also a desired feature.
Support for other firearms like assault rifles which simply requires an addition of more training images as our dataset was primarily handguns,
TKDNN support which is a kind of neural network optimizer compatible with our system that can allow for 2 times the processing speed.
Explore secondary processing methods such as detecting arms/hands and doing a more targeted detection pass on the surrounding area
Built With
c++
darknet
opencv
speech-dispatcher
yolov4
Try it out
github.com | OpenGD | A performant FOSS real-time gun detection security system aimed to help lower the response time to mass shootings and affordably increase the security of soft targets. | ['Jimmy Chen', 'Daniel Deng'] | [] | ['c++', 'darknet', 'opencv', 'speech-dispatcher', 'yolov4'] | 7 |
10,501 | https://devpost.com/software/maskindex | Homepage of MaskIndex
Example of Viewing Map
GIF
OpenCV Algorithm Testing
Inspiration
Nowadays during this “new normal”, it’s hard to tell whether a certain location poses a heavy risk of contracting the COVID-19 virus. Certain locations throughout the day have different amounts of people visiting, and it’s not guaranteed that everyone will be wearing masks. Masks are scientifically proven to significantly lower the risk of receiving and transmitting the virus. It would be nice to tell what percentage of people at a certain location at a given time are wearing masks.
What it does
Our web app delivers a simple, easy-to-use interface that allows users to view how many people are wearing masks at locations around the world. Videos of public spaces can be processed by our computer vision algorithm, which calculates an average of the amount of people wearing masks. The camera can upload this data and its location to our database. Our website then pulls this data and displays it on a Google Maps page on our website.
How we built it
We created a computer vision algorithm using OpenCV, Darknet, and the YOLOv4 framework. This model was trained on Google Colab using datasets from Kaggle and blogs. The algorithm then calculates an index based on how many people are wearing masks
The algorithm uploads data to our Google Firebase Realtime Database via the pyrebase API
Our website then pulls data from Firebase and displays it in a user-friendly format using the Google Maps API and Javascript
Challenges we ran into
Time taken to train CV models. Creating robust data pipeline from the CV algorithm to Firebase to the website
Such an ambitious idea is hard to realize without its challenges. Some roadblocks and difficulties encountered during implementation included the various package and dependencies involved, causing a web of interrelated errors in installation and execution. Finding reliable images to annotate and incorporate was also required for accurate and precise recognition of masked and maskless individuals. Getting all the components - the website, the firebase database, the openCV algorithm, and much more - to synchronize and work with one other in real-time was a challenge on all levels of abstraction.
Accomplishments that we're proud of
Computer vision algorithm that detects masks with high accuracy. User-friendly, intuitive web format that lets people easily see mask-wearing at areas.
What we learned
Machine Learning, Computer vision, full-stack web design
What's next for MaskIndex
Incorporating with AWS Cloud Computing to speed up the computer vision algorithm processing rate
Integrating with local businesses so customers can know a list of “Top 10 Places” near them that are best following mask-wearing guidelines
Built With
bootstrap
css
darknet
firebase
google-colab
google-maps
html
javascript
opencv
python
yolov4
Try it out
github.com
michellewen3.github.io | MaskIndex | Real-Time Mask Detection and Map Powered by Computer Vision to Combat Pandemics and Save Lives | ['Shreyas Kudari', 'Austin Tsao', 'Michelle Wen', 'Isaac Lee'] | [] | ['bootstrap', 'css', 'darknet', 'firebase', 'google-colab', 'google-maps', 'html', 'javascript', 'opencv', 'python', 'yolov4'] | 8 |
10,501 | https://devpost.com/software/productivitree | logo
Feed
Create post categories
Global leaderboard
Profile settings page
Statistics page
Inspiration
Most people often find it difficult to stay motivated and productive, and quarantine has only served to exacerbate this issue. Now, more than ever, it’s easy to lose track of time watching youtube videos or scrolling aimlessly through social media.
Many of our peers feel lost and isolated, and this can be very damaging to mental health. With ProductiviTree, we aim to change that by incentivizing and sharing your productivity with your friends, creating an encouraging, supportive environment.
What it does
ProductiviTree is a mobile application where users can share ways that they stay healthy and productive during and after quarantine with their friends while also gaining points towards daily goals.
Why do we want to share our productivity with others? Well, when we have to do homework by ourselves it can be hard to stay on task. But when we're in a study group, we support one another and keep each other accountable. In a survey of our peers, 63% stated that they are more productive when they’re with others. Our group wants to recreate this kind of effect with more things, and on a bigger scale.
On top of that, to further incentivize productivity, the user can gain points for doing tasks in the categories of self-care, community, fitness, and productivity. The accumulated points will automatically be redeemed to plant trees, so users can help the environment while helping themselves.
How we built it
Here is our high level design diagram. We constructed the front end of our application with React Native on Expo to facilitate cross-environment development along with built-in APIs, and the backend using Node.js and Express. We utilized MongoDB to manage user data. For the accompanying website for our app, we used React.
We understand that user security is an important issue, hence to ensure user privacy and data security, we used Google Authorization for account creation and sign-in. DevOps are handled with GCP App Engine and Firebase.
We do not anticipate any issues with handling the expected load of users. However, if we receive many more users, our application architecture can be easily scaled for many more users by simply sharding our databases and scaling our servers.
As a team, we spent a long time discussing each of our current strengths and weaknesses, and used this tech stack because it is a combination of technologies that we are familiar with, along with some technologies that we had less experience with. Through this project, we have branched out and learned more while still maintaining and using the skills we had prior.
Challenges we ran into
Over the course of this hackathon, we came across multiple roadblocks and learned a lot while facing them. The main issues we faced were some backend issues and connectivity, but we did also have some front end issues.
We have a complex backend with entities that have multiple relationships with other tables and even their own tables. This is the first time that we’ve dealt with database relativity and it took us a while to figure out the most optimal way to structure our database to maximize efficiency.
For some of our screens, we had to make several API calls where the parameters for one was dependent on the other, or handling data from several APIs based on user selection to create custom states. This would at times slow down our app rendering. To fix this, we learned how to hook handling and state management works and created placeholder components.
We realized that some of our parts for the user profile and friends profile were very similar. To optimize app size and take full advantage of React’s reusability, we decided to create reusable components and call them at the appropriate screen using conditional rendering.
Marketing
Onboarding with our app is as easy as logging in through your Google account. From there, you can set your daily goal, find other users to follow, and start making your own posts!
For marketing, we can incentivize users to invite their friends by giving them points for each friend they refer with a referral link. We have created an accompanying website that includes app details, demo videos, and links to the listing on the app store.
Though the idea was inspired by our current situation with social distancing, users will still be able to use the app post-quarantine, to keep them productive, motivated, and connected to friends.
What's next for ProductiviTree
As we continue to work on our app, we would like to add daily notifications to remind you to be productive and help the environment. We want to add more interactions for friends, such as challenging each other to do tasks and add “teams” for groups to encourage more friendly competition, and of course, by extension, more productivity.
We would love to partner with environmental organizations to help us plant trees or help the environment in any other ways, because we are all very passionate about creating things that make the world a better place.
Built With
expo.io
express.js
firebase
google-app-engine
javascript
mongodb
node.js
react-native
typescript
Try it out
github.com
productivitree.web.app | ProductiviTree | Planting happiness in our community! | ['Megan Tran', 'Reshmi Ranjith', 'Saloni S', 'Vincent Vu', 'Medha Jonnada'] | [] | ['expo.io', 'express.js', 'firebase', 'google-app-engine', 'javascript', 'mongodb', 'node.js', 'react-native', 'typescript'] | 9 |
10,501 | https://devpost.com/software/stepitup-y71bnh | Inspiration
Over the past few months, we have been faced with a worldwide pandemic that no one could ever see coming. As a result, our day to day lives have been altered drastically. Whether it be being under lockdown, taking a prolonged break from work, or being home from school, staying active has been a common problem we have seen people encountering.
What it does
Hoping to reverse this slump we have recently found ourselves engaged in, seemingly unable to crawl out of it, we have created an app called StepItUp, which is primarily focused on motivating users to get up and walking by competing with fellow friends to see who can walk the most at the end of each week. Coins are earned for each step users walk which can later be used to purchase items to design their own personalized avatars, ultimately providing a fun and competitive experience to encourage users during this pandemic to remain healthy and active.
How we built it
We used Amazon Web Services to manage our back end resources. Using the EC2 cloud compute service that they offer to host an instance of our REST API server that we coded in Python in tandem with the provided Relational Database Service to host our MySQL database. On the front end, we used Apple’s Xcode to code our UI design in Swift, using a blend of Storyboard and Programmatic implementation for the visual layout, and a series of web requests for the frontend-backend connection.
Challenges we ran into
We had many challenges working on our MySQL database because we weren't familiar with back end resources. This was also our first time creating a fully-functioning app, making it difficult to figure out what we could realistically put out.
Accomplishments that we are proud of
We are proud of being able to learn how to code in Swift, but also how to connect the front end and back end with each other. We are glad that we were able to design and create an app that can keep us connected during quarantine.
What we learned
We learned how to split tasks and how to work together on certain things that needed more research and YouTube tutorial watching.
What's next for StepItUp
We want to continue polishing this app so that we can publish it on the App Store. We hope that this app will inspire people to stay in touch with friends and to take daily walks.
Built With
amazon-web-services
healthkit
mysql
swift
xcode | StepItUp | StepItUp is an app that was created to motivate people to compete with fellow friends to see who can walk the most number of steps by the end of each week. | ['chiukelly Chiu'] | [] | ['amazon-web-services', 'healthkit', 'mysql', 'swift', 'xcode'] | 10 |
10,501 | https://devpost.com/software/coderconnect | Landing Page
A tutor's profile
Scheduling a meeting
Shared code editor during a tutoring session
Post Lesson feedback to ensure tutor's quality
Inspiration
Ever since universities and schools across the United States suspended due to the COVID-19 pandemic, the sudden change to online learning has severely impacted the learning experience for many students. Using the extra time at home to learn to code, we realized that it was harder to understand many programming topics without the aid of a teacher or professor. Many online learning websites require the student to rely on their own in order to understand concepts, while online tutoring websites require an expensive subscription service. After struggling to find a perfect method of remote learning, we decided to create our own tutoring service. Completely free of charge and built with all the functionalities required for the complete learning experience, CoderConnect is prepared to improve student’s programming skills - whenever, wherever.
What it does
As a free online tutoring service, CoderConnect allows students interested in Computer Science to learn from a wide variety of programming skills. Our tutors are highly qualified individuals that have the necessary skills to teach anything our students are interested in learning. The process is made extremely easy. Simply connect with any tutor and communicate through live chat to secure meeting times. Students are able to work in real time with video chat, a collaborative code editor, and a whiteboard - the perfect learning environment.
How we built it
Technologies Used: NodeJS, ExpressJS, React, MongoDB, WebSockets (Socket.io), WebRTC, Axios, Nodemailer, Multer (File Upload), and Heroku.
Challenges we ran into
One significant challenge we ran into was setting up the live video chat and collaborative code editor environment, as well as Syncing the sessions between two users to ensure they start and end at the same time. We were able to eventually implement these features through researching more about WebSockets and WebRTC and using Socket.io and Simple Peer.
What we learned
This was our first experience with Web Development and learning the MERN Stack, and was definitely a valuable experience.
What's next for Coderconnect
We plan to add in-browser code execution and live screen sharing.
Built With
css3
express.js
heroku
html5
javascript
mongodb
multer
node.js
nodemailer
react.js
socket.io
webrtc
websockets
Try it out
coderconnect.herokuapp.com
github.com | CoderConnect | Many tutoring websites exist for those who want to learn to code. What do they all have in common? They're expensive. CoderConnect brings you the same learning experience at no cost. | ['Satya Suravaram', 'Andrew Shang', 'Ajata Reddy', 'Karthik Menon'] | [] | ['css3', 'express.js', 'heroku', 'html5', 'javascript', 'mongodb', 'multer', 'node.js', 'nodemailer', 'react.js', 'socket.io', 'webrtc', 'websockets'] | 11 |
10,501 | https://devpost.com/software/healthyhabits-ai | Inspiration
As college students, all four of us shared the concern that our sedentary lifestyle, which was magnified by the lockdown would lead to bad habits that affect us long term. In particular, we were concerned that us as well as many of our peers would often slouch and sit back instead of sitting up straight. In addition, with the pandemic, we were aware that many people were afraid of catching Covid. We realized that one of the most common avenues of transmission was having one’s hand in close proximity with their face. As Computer Science and Data Science majors, all of us recognized that technology could help address our concerns and because we were all interested in machine learning, we figured that implementing a machine learning algorithm to track one’s hand and one’s posture would be a great way to further our knowledge and address our concerns.
What it does
Healthy Habits.ai connects to your webcam and takes a picture of you every minute. You can either choose an algorithm that checks your hands to make sure they are away from your face or checks your posture to make sure that you are not slouching. If you are either having your hands close to your face or slouching, depending on the option you chose, the web server will give you a vocal warning as well as keep track of the total warnings it has given you so far.
How we built it
We started off with the machine learning algorithms where we found templates off of Github. After understanding what they did, we decided to use CVLib for the framework behind the algorithms. The good news was that it already came with the training data so we did not have to provide our own, especially for the posture detection part. However, for the hand detection part, we did have to take some selfies with our hands in a variety of positions. After finishing the machine learning algorithms we ran our server on Heroku to give it accessibility. The next part was frontend where we used HTML to make a website that would display our model for visitors. We also implemented buttons which we managed via Javascript. For our counter, we represented with a Javascript variable which we would display through HTML.
Challenges we ran into
Overall, a challenge we faced from the start was our inexperience in developing a web application. However, through the help of our mentor Anish and our eagerness to learn, we quickly beat this obstacle and were able to accomplish our initial goal. Furthermore, with everything virtual and all members based in different timezones, collaboration was a lot more challenging than in person. However, we didn’t let this slow our progress and we were still able to meet regularly to maintain this essential component of collaboration.
On the technical side, we had issues with our face-hand detection. Originally, we had trained a yolov4 model with a custom dataset of 1500 hand and face images. Although the results of this training was wonderful (mean average precision of almost 98%), we could not use this approach because deploying an ML model that required a GPU to run properly was too tricky for us to set up.
Furthermore, a challenge we ran into was the struggle of deploying our application to Heroku. While deploying our web application, we ran into a memory issue as the size of the Tensorflow package was too large for Heroku to process, which slowed down our web application extremely. In addition, we also encountered a memory leak, so we spent a lot of time trying to find the cause. Because of these challenges with Heroku, our web application can only run locally.
Accomplishments that we're proud of
We are proud of building a web server and implementing machine learning algorithms all in our first hackathon. In particular, many of us were new to Javascript and HTML so we are surprised at how quick we picked up the new language. In addition, having never worked on a project as complex, we are proud of how we managed the numerous branches of this project. Finally, as 4 individuals from all over the nation that haven’t known each other prior, we are proud of how we gelled as a team.
What we learned
We are extremely proud that we were able to develop a web application with no prior experience. Furthermore, we also learned how to implement flask and deploy Heroku.
Finally, as first-time participants of a hackathon, we learned how to collaborate as a team to build a project from start to finish, and jump over the hurdle of doing everything virtually.
What's next for Healthy Habits.ai
We hope to be able to deploy the app through Heroku and further improve the accuracy of the detection models. In addition, we hope to improve our face-hand detection by utilizing the yolov4 model with a custom dataset of 1500 hand and face images.
Built With
css
cvlib
flask
html
javascript
python
tensorflow
Try it out
github.com | Healthy Habits.ai | A web application that promotes healthy habits through encouraging good posture and preventing any touching of the face. | ['Grace Gao', 'awesomezhnathan', 'Claire McGonigle', 'Keerthi Srilakshmidaran'] | [] | ['css', 'cvlib', 'flask', 'html', 'javascript', 'python', 'tensorflow'] | 12 |
10,501 | https://devpost.com/software/drfit-6hocwa | Opening screen on Watch
Flowchart
Logo
Inspiration
A potential challenge during the pandemic outbreak like COVID19 is overwhelming hospitals. Due to the increase in the number of COVID patients, doctors are giving less attention to a non-COVID patient. Right now, hospitals don't have the capacity for the large number of incoming patients. There is a need for a technology platform which is capable of remote-monitoring and allowing for the engagement of patients in their homes. The capabilities also facilitate communication between quarantined people and the healthcare service and maintain visibility of those recently discharged. This problem is what inspired us to make this user-friendly interface.
What it does
The DrFit platform offers an ideal way to monitor patients while they are in quarantine. The device hub include those that measure vital body temperature, heart rate, blood pressure, SPO2 level in the blood. The information of the vital signs will be updated via web to the doctors.
How we built it
We used the Google Cloud Platform along with Firebase for this project.
Firebase
User Authentication
Realtime Database
Store Vital Data and User Information
Store Information if the user is a Doctor
Cloud Functions
Other GCP
Google Maps API
Bootstrap HTML/CSS/JS
Bootstrap Framework
Use of JQuery
Use of SmartForm for Contact
Frontend Framework
GitHub
File Management
Hosting
Node Js
Firebase Modules
Alan - Alan is a Smart Assistant that we have built for users to ask simple questions.
You can ask it I have a Cough
and it will respond
Challenges we ran into
There were many challenges we ran into, but that's what programming's all about. One of the difficult challenges we ran into was making sure the UI worked. Another challenge was figuring out how to to extract information from the JSON file to the website.
Accomplishments that we're proud of
We are proud of so many things. We made use of this project to the best of our abilities in this 24 Hours of time. We got to use the Google Cloud Platform, which is a first for all of us, we had never used GCP before and now we will continue to use this platform. Additionally, we combined all of our skills to create a website that use multiple frameworks and we are proud of this website. We love the UI/UX and we love the Backend, it was our first time as well using these frameworks. Finally, we are proud of the amount of work we pulled of in 24 hours. We would have never thought we could accmplish this much in such a small amount of time.
What we learned
Creating realtime databases
Firebase
User Authentication
What's next for DrFit
Implement Google Assistant instead of Alan (Wider range of possibilites)
Create a Watch Application (Apple watch and Galaxy Watch) to have realtime data about Vitals
Implement more Google Cloud Features including Tensorflow AI for medical classification and image classificatin to find various conditions
Implement a TeleHealth API platform for virtual doctor visits
Implement Echo AR for human body modeling
Implement a Covid-19 screener questionaire for the workplace and schools
Built With
alan
bootstrap
css
firebase
github
google-cloud
google-maps
html
javascript
Try it out
mohinishteja.github.io
projects.invisionapp.com
github.com | DrFit | Empowering the non-COVID population | ['Mohinish Teja', 'RHEA S', 'Arnav Shah', 'Srikar Kusumanchi'] | ['Runner Up Productivity Hack'] | ['alan', 'bootstrap', 'css', 'firebase', 'github', 'google-cloud', 'google-maps', 'html', 'javascript'] | 13 |
10,501 | https://devpost.com/software/trefle | Inspiration
We noticed a distinct lack of voter participation at the collegiate level. This is often because potential voters aren't aware of leadership candidates in their respective clubs and sometimes, don't even know when elections are taking place. For candidates, this can be very discouraging and ultimately defeats the purpose of student government. Clubs also face the challenge of member communication, especially with their leaders, as it's very hard to get contact information or even know anything beyond the surface level about these students. Even if a club has all this information present, it can sometimes be tedious finding all this information as it might be buried deep within its website. Keeping track of all the different club elections and candidates can be a pain, and students, more often than not, choose to not get into it in general. Having all this information in one place would greatly increase voter turnout and enthusiasm about elections at the recreational club level, which will hopefully translate to public office elections in the future.
What it does
Our app displays the current leadership candidates of all the various clubs that a person might be in. It will also display the elections and the candidates in the election, along with an option to actually vote. At its core, it is a platform for voting. However, the application also includes essential utilities, such as an event calendar, announcements, and we plan to implement in-app communication with all of a club's members in the future
How we built it
We used react-native for the front-end and Django with Python for the back-end. We chose Django as it has more documentation than competing back-end technologies such as flask and because it is commonly used in the industry. We used MongoDB for the database and deployed it using an EC2 server.
Challenges we ran into
Learning all the technologies from scratch
Connecting different tools in the environment (Front-end and Back-end)
Outdated versions in the documentation
Time-management
Addressing all the complexities of the voting process
Accomplishments that we're proud of
Learning the tech stack that we were previously unfamiliar and applying it into a technological service
Addressing an issue that we all faced
What we learned
We learned, to a simplified extent, the process of creating and deploying an app
We learned how to brainstorm and wireframe for a creative project
We learned our respective tech stacks
We got better at reading documentation
We learned to better manage our time and expectations given a 14 week time period
What's next for Trefle
Implement in-app communication
Implement an application form
Implement popular features such as a Dark Mode
Make a corresponding website
Scale this app to encompass public office elections as well as just collegiate ones
Built With
django
mongodb
react-native
Try it out
github.com | Trefle | An app that streamlines the voting process in colleges and high school elections | ['Gautham Raju', 'Dhruv Sethi', 'Dhruv Thoutireddy', 'Raju Kakarlapudi'] | [] | ['django', 'mongodb', 'react-native'] | 14 |
10,501 | https://devpost.com/software/bundlr-wptc96 | Inspiration
With CoVid-19 cancelling many summer jobs and internships, students struggle to maximize their summer's productivity and potential. After researching and interviewing how to mitigate some of the trials students go through, our team determined that we can develop a web application designed to quickly pitch and share passion projects and get connected with other determined individuals.
What it does & Technologies used
Our application allows users to post basic pitches for the projects. Other users can view these posts and can reach out via email to the original poster. Bundlr was developed using the MERN (Mongo DB, Express, React, and Node.JS) stack!
What we learned, and the challenges along the way
None of us had web development skills prior to this event! We came in with different backgrounds from business, to visual arts, informatics, and computer science. Once we had scoped and defined the problem, we moved to designing mockups in Figma, then worked on developing! It took many weeks to learn the nuances of web development, from building raw HTML & CSS, to designing and building databases that would be robust enough to handle our project.
What's next for bundlr
We aim to continue building bundlr and build our research by testing new features! Thanks for reading, watching, and enjoying ~ Stay Tuned!
Built With
express.js
mongoose
node.js
react | bundlr | A project posting board to share project ideas and recruit team members! | ['Schawnery Lin'] | [] | ['express.js', 'mongoose', 'node.js', 'react'] | 15 |
10,501 | https://devpost.com/software/productivity-tracker-summerhacks2020 | Logo
Website Monitor
Inspiration
Our original goal for this summerhacks was just to learn HTML, CSS, and Javascript and create a project out of these tools. Building a website monitor was a very project to help us learn these skills because it's a useful Chrome extension that can help us be more productive when we're using our computers.
How We Built Project
Since our goal was to track and block websites, we figured a Chrome Extension was the best way to achieve our goals. How did we build the Chrome Extension? Stackoverflow, Youtube tutorials, and a lot of trial and error.
What We Learned
We not only ended up learning HTML, CSS, and Javascript, but we also learned the basics of the Bootstrap framework and how to make a basic Chrome Extension. This was also the first time we learned to use API functions (specifically the Chrome API).
Challenges We Faced
Probably the biggest challenge we faced was the transition from tutorials to starting the project. We had little/no prior experience, so we had to learn from tutorials in the beginning. However, even when we had finished the tutorials, we were afraid we still weren't "ready" to start the project. We learned to conquer our inferiority complex and just embrace the fact that one doesn't have to be an expert before starting a new project.
On a technical side, one of the more technical challenges we faced was learning how to use an API. We had to learn about callbacks, asynchronous vs. synchronous events, and message passing between scripts.
Built With
bootstrap
css
html
javascript
Try it out
github.com | Website Monitor | The Website Monitor is a chrome extension that can block distracting websites of your choice and track how long you use websites in general. | ['Zile Zhu', 'Andrew Wu'] | [] | ['bootstrap', 'css', 'html', 'javascript'] | 16 |
10,501 | https://devpost.com/software/busy-beagles-activity-app-for-kids | Inspiration
Our team consists of Tess Van Daele, Olivia Morkved, Derex Wangmang, and Jorge Tomaylla. We created an activities app targeted at kids ages 5-12. We call it Busy Beagles! It’s inspired by the fact that in quarantine, kids are the ones with the most unspent energy as they are stuck at home with little to do. We wanted to develop an app that provides them with activities to do during quarantine and even after in order to get them active and focused.
What it does
Our mobile app provides activities in five categories: Indoors, Outdoors, Health, Learning, and Fun. Kids can scroll through the activities, read descriptions, and add them to their to-do list. Kids can view their progress, complete tasks, or remove them from the to-do list. They can also use the Surprise page to quickly generate activity suggestions.
The app interface is simple enough that we anticipate young kids to be able to use it, so long as a parent helps with initial account creation and authorization. We store info on a cloud-based service so that the kids can log in on multiple devices or retain their acount if their device is stolen.
How we built it
We built our app through React Native, an open source Javascript framework. Originally, we considered alternatives such as Swift. However, we realized that first, not all of us have Macs, but second, through React Native we’d be able to deploy our app on both iOS and Android. This would allow us to reach a larger audience! We used Firebase for authentication and as a cloud database, and we used Expo as a framework which runs on top of React Native.
Challenges we ran into
Initially, we had a hard time choosing a name! We wanted something fun and catchy to communicate the fact that the app was for kids. At the same time, we wanted to convey the app's function, which was to provide activities and, hopefully, to temporarily cure quarantine-induced boredom. We decided that "Busy Beagles" convey a sense of fun and -- anyone with a dog knows they can entertain themselves for hours!
(Curious about our runner-up name? It was Lion Learning App :) )
Another challenge was developing a kid-specific app, because we wanted to be sensitive about protecting kids' privacy. This was especially pertinent as we were using a cloud database. We decided to neither ask for nor store personal identifying info, other than the email used for account creation and first name. It would have been fun to add an "Age" or "Date of birth" -- but we considered the trade-off between additional features and privacy and decided to err on the side of privacy protection.
On the technical side of things, we were new to the languages and technologies that we used, which we talk about more below. While this was a challenge, we all felt like the purpose of the hackathon was to learn, and so we embraced it!
Accomplishments that we're proud of
Everyone on the team either had zero or only a little bit of knowledge of Javascript. So, we did a ton of learning-on-the-go when it came to Javascript syntax and best practices, React Native features, and the Firebase API. In addition to this, only 1 out of the 4 teammates had prior experience with version control. We spent time learning how to navigate Git (commands, pull requests, and all that good stuff).
Furthermore, none of us knew each other before the start of the hackathon! Despite this, we had a lot of fun planning the idea for the app (which was inspired by a teammate's younger brother.) We are proud of how much we gelled as a team and of how we learned to work together.
What's next:
We will definitely be adding more activity ideas in each of the five categories (Indoors, Outdoors, Health, Learning, and Fun). (email us activity suggestions at:
busybeaglesapp@gmail.com
)
On the maintainance side of things, we also have some tweaks to make and Android-specific debugging to do to allow the app to be truly cross-platform.
In the future, we hope to make a parent-facing side of the app. Parents can link to their kids account and track their kid's progress in the app.
Built With
expo.io
firebase
javascript
react-native
Try it out
github.com | Busy Beagles (Activity App for Kids) | In COVID quarantine, kids get bored easily! This mobile app provides inspiration for staying busy with fun and entertaining activities. | ['Olivia M', 'Tess Van Daele', 'jorgetomaylla', 'Derex Wangmang'] | [] | ['expo.io', 'firebase', 'javascript', 'react-native'] | 17 |
10,501 | https://devpost.com/software/venti-cook | SOLID WORKS ANIMATION
Inspiration
According to WHO.INT 2 Billion people around the globe are still dependent on burning biomass fuel such as wood in (mud Chula/Clay stove) for cooking food. But the downside is that it is very harmful to health and environment as the smoke created for these biomass fuels are an outcome of incomplete combustion and inhalation of these harmful smoke leads to 2 million premature deaths every year in around the world. So this huge issue inspired me to create a Stove which gives better combustion than primitive Clay stoves, emit less smoke, and also very cheap to buy, helping the Poor people.
What it does
Our project Venti-cook is a metallic Stove with two fans in opposite sides, one rotates clockwise (used to pull air inside) and anther rotates anti-clockwise (to push smoke outside) and works with peddling system, with this mechanism the user only has to use the peddle which will act both as an exhaust fan and an air blower making it a cleaner and safer options as there user doesn’t have to go near the flame-like in case of the pipe air blower. And the user has full control over the flame. we also have a metallic welded under the stove so that the burnt ash can escape and doesn't require much cleaning.
specification
Air Blower fan: - to supply air for complete combustion.
Exhaust fan: - Emit our smoke to avoid inhalation by the user.
Easy to use: - similar to mud Chula making it easy to use for rural people.
Full-metal Body: - made of full metal making to strong and durable.
Pedal system: making cooking comfortable and regulate flame according to the user.
Exit ring: to avoid any spill of liquid like milk or water into the flame.
Metal net:- ashes of firewood easily escapes out.
Challenges we ran into
1.) For making the animated image we have to learn the SOLID WORKS from the beginning.
2.) Calculating the actual measurement us hard for us as physical laws don't work properly in solid works.
3.) Due to lockdown, it was hard for us to get the desirable parts from the shops
4.) The welding worker being unfamiliar to this type of complex works so we have to stays there for hours to see
whether they work is going in the right directions
5.) Transportation was also an issue as it was heavy to be carried by single person on a bike so we have to hire a
tempo to deliver it to our home.
Accomplishments that we're proud of
we’re proud of how we’ve dealt with time pressure and worked cohesively as a team to actualize our start-up goals, which we believe would have a genuinely positive impact on saving many lives once implemented properly.
What we learned
Team members of VENTI-COOK were able to grow their area of competence by participating in the whole process of idea definition, market research, validation, prototyping, and presentation. Through different challenges we faced, we learned that problems could be approached by many means, but most importantly our mission should be clear.
What's next for VENTI - COOK
Our product has a huge market potential Because 2 billion people still use Clay stove, we can replace them with our product, the manufacturing cost will be nearly $6.5 dollars and the retail price will be nearly $ 9.4 dollars with $ 2.9 as profit. So approximately we have a market of $ 2 billion. Our main target will be rural households across India and Africa where clay stove still used in abundance.
Built With
hardware
solidworks
Try it out
github.com | VENTI - COOK | An Innovative Stove for a global cause | ['Anup Paikaray', 'Arnab Paikaray'] | [] | ['hardware', 'solidworks'] | 18 |
10,501 | https://devpost.com/software/discord-deception | This SummerHacks Hackathon project is a Discord bot that hosts deception games.
Problem
As a friend group, deception games are our favorite pastime because of how intense and bonding they are.
And when COVID hit, it was the first thing we started missing about hanging out in person.
Solution
We realized that technically an extra person could help host the game over discord instead of playing... but better yet, that extra person could be a bot! That way, the tedious parts like picking roles and relaying messages can happen automatically, and everybody gets to play.
We considered the full list of deception games we knew, and decided to narrow it down to starting with two classics: mafia (for its simple secret role-based collaboration) and coup (for its use of cards and currency).
Mafia
Traditionally, at night the mafia members secretly decide who to kill by mouthing words and pointing. On discord, this process text-based by forwarding messages between players in the bot's DMs, and using a ?kill command. For cops, we did the same thing with ?inspect.
Both of these actions only work at night and if you have the correct role.
At the beginning of the game, the bot creates a Town Hall voice channel, and automatically moves all players into it, removing an extra step for the players. At night, the bot mutes everyone so that the mafia and cops can type without being caught.
Normally, accusing and voting happens by pointing and raising your hand publicly. On discord, the player uses the ?accuse and ?vote commands, and once everyone has submitted their votes, the results are displayed for all to see. The bot also handles tie votes.
Coup
Because of the sheer number of actions in Coup, we decided to make the actions entirely button-based instead of text-based, reducing the learning curve for the players.
We also made sure that the display is unique to each player, like only showing buttons for actions they can afford, and only showing the values of their own cards and the cards that other players have flipped over.
The underlying logic of the game gets really complex, but ultimately comes down to interacting with simple objects: the influence cards and players' currency.
A big part of coup is challenging players on whether they have the card to back up their action, a bit like in the card game BS. This game element allows for complex deceptive strategy and mind-blowing plot twists.
The Future of Discord Deception
The best part about starting with these two games is that together, they cover huge parts of the code for other games. This means that this project is scalable not only for coding more of our favorite games for discord, but also for designing and implementing brand new deception games.
Playing deception games is a great and easy way to connect with people, and now, connecting with people just got a little easier.
Built With
discord.js
node.js
Try it out
github.com | Discord Deception | A Discord bot that hosts deception games. | ['Parker Bedlan', 'Justin Liu', 'PiyushMewada Mewada', 'Kevin Wang'] | [] | ['discord.js', 'node.js'] | 19 |
10,501 | https://devpost.com/software/tuduo | I'm going to cook a shark!
I'm going to log in.
I don't want to be a bear anymore!
Inspiration
You can't always get the same kind of motivation to do things on your own like you do when at work, school, or in a team, and given the current situation, there are even less opportunities to work with others. We wanted to create an app that allows folks from around the world to pair up and keep each other on track.
What it does
By creating an account, you can match with other people that also want to get something done but would just looove the extra push that comes from working with others. Accounta-buddies can either work together or have their own individual goals and just provide that "I'm here for you" support. Chat with your accounta-buddy and plan out milestones to organize your goals. Have your own to-do lists for each goal. The simplistic design allows accounta-buddies to do anything from trying to recover from substance abuse to maxing out their bench (320 btw) to mastering the pikachu programming language.
How we built it
We used React-Native for the front-end as it let us deploy on both iOS and Android devices. For the back-end, we used Firebase.
Challenges we ran into
Learning to make our first app from scratch was quite a hustle. With Firebase as an emerging technology there was a good amount of sifting through stack exchange threads with only 5 views. In addition, we were sorely lacking in motivation to meet deadlines. Woe was us! If only there was a convenient app to bolster our productivity...
Accomplishments that we're proud of
Being able to complete a mobile app through completely new technologies (to us) gave a lot of confidence in what we could do in the future. We're happy with what we did on the design and functionality but the real app we created was the friends we made along the way.
What we learned
React-Native. Firebase. Most of us used Git before but really got to know proper etiquette due to the current remote situation.
What's next for TuDuo
We plan for an improved buddy matching algorithm, AI bots to provide motivation similar to Replika, a leaderboard for added competitive motivation, and other encouraging factors to bring goals to their completion.
Built With
firebase
react-native
Try it out
github.com | ToDuo | Two heads are better than one when you're trying to get things done! | ['Jesse Huang', 'Andrew Deng', 'Bea Litonjua', 'Olimjon Nematov'] | [] | ['firebase', 'react-native'] | 20 |
10,501 | https://devpost.com/software/covidrisk | Inspiration
After the COVID-19 pandemic hit, new regulations and recommendations were constantly being released. It quickly became difficult to distinguish between safe and dangerous. While trying to evaluate the risk of going to parks and grocery stores, we realized that current maps and charts do not provide a holistic risk value that not only takes into account the number of COVID-19 cases in the area, but also how busy the location is and the type of place. So, we decided to develop an app that provides that holistic risk value to help users make the most informed decisions possible when leaving the house.
What it does
The main function of the CovidRisk mobile application is to calculate the risk of visiting a specific location. The app gathers information on the number of new COVID-19 cases per 100 thousand people, the average time spent at the location, the busyness of the location - based on data from Google Places that accounts for day of the week and time- and the risk associated with the activity according to informed medical institutions to formulate a consolidated risk value.
These four factors are factored into a percentage risk value. We classify risk percentages as such:
0%-25%: Low Risk
25%-50% Medium-Low Risk
50-75% Medium-High Risk
75%+: High Risk.
Our app also prompts the user with additional questions based on place type. For example, if the location is a cafe, bakery, or restaurant, the user is prompted with a question about whether they plan to take out or dine in, which is factored into the risk value. In addition, if the place is a city or other type of locality, the user is not prompted with any additional questions, and risk is calculated based solely on the number of new COVID-19 cases per 100 thousand residents.
How I built it
We started the build process by designing an overall layout of our application. We knew we wanted to build a cross platform app using React-Native and Python and that we needed a backend API that would gather and analyze data. We started by researching existing open source COVID-19 APIs and data sources, and came across this Coronavirus API Tracker:
https://github.com/ExpDev07/coronavirus-tracker-api
.
We proceeded by using the Python wrapper for this API and created our own functions in Python that calculated the average number of new COVID-19 cases per hundred thousand people over a period of three days in the county of a location. We then used the Google Places API to find the county of the inputted location, and also the following Python “populartimes” wrapper to factor in the busyness of a location at any time:
https://github.com/m-wrzr/populartimes
.
After creating these Python functions that calculated a risk in the backend, we used Flask to create an API of our risk analysis information. Flask allowed us to send data from the user input in the fronted to the backend. We incorporated various components in React-Native to simplify the user experience such as the Google Autocomplete tool for location input, a loading page, and a risk slider display:
Slider:
https://github.com/react-native-community/react-native-slider
React Elements:
https://react-native-elements.github.io/react-native-elements/
Challenges I ran into
The biggest challenge we faced was working with network requests. Since we had no prior experience with API calls, we spent a few weeks researching the concept and running post requests tests in React Native. We also originally planned to use Django to create our own API, but after a few trials, we felt Django overcomplicated the process and instead, proceeded with Flask.
Accomplishments that I'm proud of
Before this Hack-A-Thon, our computer science experience largely consisted of backend development. The CovidRisk project was not only our first time creating an application, but also our first experience with full-stack development from scratch. We are proud that we were able to accomplish a milestone project in such a short time and we will continue to work to make our app fulfill its potential impact.
What I learned
As we entered this Hack-A-Thon, our goal was simple: create a tool to help people during a global pandemic. We started out with Python experience but no experience in app development and, over the past 12 weeks, we developed a cross-platform application using React-Native and Flask. With the help of our mentor, we learned about APIs, how to make network requests, and version control in GitHub. We hope to further develop these skills and improve our app in the future. Extensive work with adding fundamental UI components allowed us to become proficient in React Native.
What's next for CovidRisk
Moving forward, we plan to implement a map view populated with markers that would allow the user to see risk values associated with nearby locations. For example, if the user wishes to visit a busy Starbucks that has a high-risk value, they could quickly find a local coffee shop with a lower risk. Additionally, we plan to add a risk graph that displays predicted risk values and alternate times and days for a desired location, allowing users to choose an alternate time and day with a lower risk value.
Built With
flask
python
react-native
Try it out
github.com | CovidRisk | CovidRisk allows users to make informed decisions about leaving their home by calculating the risk of a location through factors such as the number of cases, busyness of the location, and more. | ['Ameya Rao', 'Ananya Seelam', 'Kathleen Trang', 'Namya Kodali'] | [] | ['flask', 'python', 'react-native'] | 21 |
10,501 | https://devpost.com/software/zard | Splash screen
Sign-In / Register
Set-up
Dark mode
Orders (Seller view)
Customers (Seller view)
Transactions (Customer view)
Purchase (Customer view)
Inspiration
We built Zard to mitigate the impact that small businesses have had due to the pandemic.
What it does
The app allows three different user roles: customers, sellers, and manufacturers. Depending on the user role, a user can either sell products or view products posted by local businesses. The app also allows additional functionality like the ability to view reviews and view previous interactions.
How we built it
Zard is built with Flutter, a UI Software Development Kit. We choose Flutter to maximize the number of people that can access and experience our app. Because we used Flutter, our app is compatible on both Android devices and iPhones.
Challenges we ran into
The biggest challenges we faced involved converting our project from design into a viable product and setting up authentication. Collectively, we have minimal prior knowledge with Flutter, so there was definitely a lot of learning involved.
Accomplishments that we're proud of
We are proud of closely converting the design into code. Another feature we're proud of is incorporating system dark mode in our app in both IOS and Android.
What we learned
We are a lot more proficient in Flutter as a result of this project and it's rather unique requirements. Additionally, we better learned how to use tools to maximize efficiency when working in a project in a group.
What's next for Zard
In the future, we plan on adding Zard on new platforms, like the web, along with better integration with back-end services.
Built With
adobe-xd
flutter
Try it out
github.com | Zard | A platform to facilitate, catalyze, and stimulate market flow at the local level as well as provide relief and convenience economically | ['Davis Tran', 'Ruthvik Ananthula'] | [] | ['adobe-xd', 'flutter'] | 22 |
10,501 | https://devpost.com/software/elm-educate-learn-motivate | Inspiration
We realized many students lack access to quality education, and the situation with Covid-19 compounds that even further by cutting off access to in-person classrooms and help. We then decided that we wanted to provide free tutoring services to help students learn. We also realized during Covid-19 that it is sometimes incredibly difficult to stay motivated and to keep learning, so we've added a motivational page where students can share their journey, their thoughts, and their advice to encourage others to keep going and learning no matter how they feel.
What it does
In our platform, you can create
learn
requests in which you can request specific tutors (or make a request to the public) for a certain topic and provide details about what you need help with. Another user can then go to
educate
and tutor that user for that subject, which will redirect users to a video call. Of course, users can feel free to reject a request at any given time! In our
motivate
page, users can create posts with advice or encouraging thoughts and share them, and users like other posts as well.
How we built it
We built our website with JavaScript using NodeJs and the Express framework, as well as HTML and CSS. We also have an app counterpart which was built with Android Studio and Java.
Challenges we ran into
Since we had little to no experience with app development and web development, we had to learn on the go and familiarize ourselves with the technologies associated with this.
Accomplishments that we are proud of and what we've learned
We are incredibly proud that we've learned so much about the different technologies needed for web and app development and create our website and mobile app! We've learned JavaScript, how to navigate Android Studio, and how to design a SQL database.
What's next for ELM: Educate, Learn, Motivate
We intend to rebuild the website with frameworks such as React or Angular as well as redesign the UI/UX experience, which currently, is not the most friendly thing. We intend to reinvent the database as well and provide more features for the motivational page such as comments.
Built With
android-studio
azure
css
express.js
html
java
javascript
node.js
sql
webrtc
Try it out
github.com
github.com | ELM: Educate, Learn, Motivate | An educational platform intended to provide free peer-tutoring services to those who need help as well as encourage students to keep learning no matter their situation or struggles. | ['ry3879 Yuan', 'annielia', 'Isabel Gan', 'Emmaline Mai'] | [] | ['android-studio', 'azure', 'css', 'express.js', 'html', 'java', 'javascript', 'node.js', 'sql', 'webrtc'] | 23 |
10,501 | https://devpost.com/software/thrifty-69fay0 | Thrifty Logo
Inspiration
Lost track of expenditure easily and always wanted to know how much was being spent on food, entertainment, electronics, etc.
What it does
Thrifty allows you to manage user expenses, capture photos of receipts, divide the expenses into categories, and display local businesses that provide cheaper options and help support them during the pandemic.
How we built it
We used React Native for the mobile app development; Tessaract and Python for receipt parser; Flask for backend; Google Natural Language API to classify items into categories
Challenges we ran into
Lesser team members than we started with, working with specific APIs
Accomplishments that we're proud of
We're beginners in Mobile App Dev and Machine Learning, super proud of what we could develop and learn despite all the challenges
What we learned
Project Management, almost all the technologies, working over 12-weeks, and demoing!
What's next for Thrifty
More efficient classification of items, location-based businesses, a database of businesses
Built With
firebase
natural-language-processing
python
react-native
tesseract
Try it out
github.com | Thrifty | Never lose track of your expenses | ['Madhurima Dutta', 'Soumya Khanna', 'Advaya Gupta'] | [] | ['firebase', 'natural-language-processing', 'python', 'react-native', 'tesseract'] | 24 |
10,501 | https://devpost.com/software/goalbuddies | Some screenshots of GoalBuddies
Inspiration
Life gets busy, things get hard, and so goals become difficult to attain as we lose our motivation. With everything 2020 has brought us, it has been increasingly difficult to receive encouragement and support from others when we want to improve ourselves. GoalBuddies was created around the idea that as "buddies," we can set out to achieve goals with one another and keep each other accountable. With groups, we can support each other and provide the motivation needed to accomplish more tasks. You'll never feel like you're on your own journey anymore!
What it does
GoalBuddies allows users to create and track personal goals, with the added feature of group goals. Members within the same group share the same goals and work together towards completing them, which encourages a supportive and growth-oriented environment. Users may also follow other users with whom they share similar goals and hobbies.
How we built it
The front-end was built entirely using React Native and its libraries. The back-end was built using Node.js and MYSQL. Express.js was used to facilitate the development of the RESTful API, AWS was used for database hosting, and Heroku for back-end hosting.
Challenges we ran into
React Native and MySQL were completely new technologies to us, so they presented a bit of a learning curve. In addition, the remote nature of the hackathon also made it difficult for synchronous development to occur, additional communication and planning was needed to develop in an asynchronous manner.
Accomplishments that we're proud of
For most of us, this was the first mobile application that we have built. Although it was a difficult start, the final product is something that we are all proud of creating. We also attempted to develop a more complex back-end, and with the time allocated for this hackathon, we are able to serve our time effectively on both the front-end and back-end of the application.
What we learned
We were able to learn about mobile applications and the tools used to build them. More specifically, we learned how to utilize React Native and Redux to create the front-end of our application, and how to build a back-end with MySQL and Node.js.
What's next for GoalBuddies
The next steps we can take for GoalBuddies is adding more features such as an interactive feed to see goals completed by you and your friends, increased social features, and gamification features to further increase incentive for achieving goals.
We also hope to publish the app to the Apple App Store and Google Play Store soon!
Built With
expo.io
express.js
heroku
javascript
node.js
react-native
redux | GoalBuddies | Get motivated as you track goals alongside your friends! | ['Thuy Nguyen', 'Jennifer Suriadinata', 'Jefferson Ye', 'Matthew O'] | [] | ['expo.io', 'express.js', 'heroku', 'javascript', 'node.js', 'react-native', 'redux'] | 25 |
10,501 | https://devpost.com/software/3d-education-tool | Inspiration
It is a well known researched fact that visual learning is much superior compared to the conventional methods.Hence we provide a means of importing 3D models into the normal whiteboard config
What it does
Our project is basically a whiteboard combined with the ability to spawn 3D models by typing the name of the object we need.The teacher can screenshare this application and show the students online any type of 3D model.There is also annotation capability so teacher/presenter can mark various parts on the given 3d model
How I built it
Unity3D
Challenges I ran into
Calling the google poly api
Accomplishments that I'm proud of
Calling the google poly api
What I learned
A lot about RestAPI
What's next for 3D Education Tool
More refining and better annotations abilities
Built With
c#
unity
Try it out
drive.google.com | 3D Education Tool using Google Poly | an educational tool with the ability to spawn any 3d model | ['Vaibhav Suri', 'Ashit Mehta'] | [] | ['c#', 'unity'] | 26 |
10,501 | https://devpost.com/software/occupansee | Real-time graph for current day
Last Week's Data
Graphs of each day last week
Distribution of Occupancy by Location
Overall Flow of Information
People detection
GIF
People Tracking
People Detection 2
Car Detection
The Process
Inspiration
Overcrowding and waiting in lines is always a pain - it might even be dangerous in light of the current pandemic. If people could know the occupancy of buildings in real-time, they would be able to make smarter decisions about where to go, avoiding crowds, lines, and frustration. In addition, with past data about the occupancy of buildings, people could also identify trends to help them plan ahead for ideal times and/or locations to visit.
What it does
Given a video feed (usually from a security camera), Occupansee calculates the number of people inside a building and then displays the current occupancy and other related statistics on a webpage in real-time.
How I built it
Backend
To detect people in the video feed, I used the YOLO Convolutional Neural Network algorithm trained on CoCo datasets, and OpenCV for image processing and other computer vision related tasks. I devised a method to calculate occupancy for larger buildings by taking the difference between the number of people entering and exiting. Then, I created an algorithm to determine which side of the frame a person exits from by tracking their previous locations and calculating which side they are closest to using their coordinates.
Database
I stored the data in a Firebase Realtime Database. I chose to use the date and time of when the data was created as keys so that I could efficiently query the data by time later.
Server
I created a server with python that queried data from the database and sent it to the front end via websockets. Additionally, I created functions to calculate hourly, daily, and weekly statistics as well as search and retrieve data by time frame.
Front End
I built the front end using React to handle components and synchronization, and Chart.js for plotting the data on graphs. There is a little bit of CSS sprinkled in as well.
Challenges I ran into
• I had to configure python virtual environments, download computer vision and machine learning packages, and install libraries for the database, server, websockets, and React. Ensuring that everything was coordinated and working properly was difficult, confusing, and frustrating at times.
• My original prototypes for the people counting algorithm were unbelievably slow, nowhere near real-time. I optimized it in many ways, including reducing the number of times people were being detected, skipping frames, and experimenting with different object detection methods.
• Conditionally and synchronously rendering different instances of the same class component in React gave me a lot of trouble, but I solved it by using a special keyword for the passed in props and then putting the time-based function in a larger container component.
• I had to figure out how to pack the data (originating from python) into a format so that the React frontend could unpack and display it.
• I initially tried to make the server in Node, but I was running into a lot of issues with both the front end and the database, so I reverted back to python.
• In the beginning, I wasn’t able to grasp what the overall structure of the project should look like. My mentor helped me a lot with understanding it.
Accomplishments that I'm proud of
I am extremely proud of my resilience through the many pitfalls and obstacles I faced when creating Occupansee. I'm also proud that I genuinely became a better programmer, engineer, and innovator through this project. But more than anything else, I am proud of the fact that I was able to turn my vision into something tangible.
What I learned
• How neural networks (including convolutional) work, especially in the context of computer vision.
• How backends, frontends, and databases communicate with one another, and the different types of frameworks for doing so.
• How to use React on top of HTML, CSS, and vanilla JavaScript.
• Different ways to design and implement the flow of information, both in algorithms and between parts of an app.
• The overall structure of an application from top to bottom, and the functions and interactions each part.
• How to configure environments and utilize different types of computer tools for specific tasks.
What's next for Occupansee
• Obtain access to more security cameras, perhaps with cooperation with companies.
• Develop geographic and mapping features to provide further insight into traffic and congestion.
• Implement different object types (animals, vehicles, etc.) to enlarge the scope of Occupansee’s possible uses.
• Optimize the performance of the detection algorithm with CUDA (requires a NVIDIA Gpu).
• Expand to outdoor areas such as parks, sports fields, roads, etc.
Built With
chart.js
coco
css3
firebase
javascript
json
node.js
opencv
python
react
websockets
yarn
yolo
Try it out
occupansee.web.app
github.com | Occupansee | AI powered information for your next destination. | ['Richard E Liu', 'Eric Li', 'Christopher W Chen'] | [] | ['chart.js', 'coco', 'css3', 'firebase', 'javascript', 'json', 'node.js', 'opencv', 'python', 'react', 'websockets', 'yarn', 'yolo'] | 27 |
10,501 | https://devpost.com/software/covidtexas | Inspiration
Our inspiration for creating this IOS app was to inform the public of Texas COVID-19 and its current state to help spread awareness.
What it does
The app is three paged app which each share COVID-19 data in a different way. There is also a signup feature for users to receive daily notifications on the status of COVID-19 in Texas.
How I built it
The front end of the app was built using Swift and Xcode using various storyboards and tableviews to display the data. The backend of the application was implemented through Google Firebase, where the data was stored in Cloud Firestore and the notification feature was implemented through google cloud functions. Along with this, we have a python script running on a cloud server that web scrapes the data into the firestore database.
Challenges I ran into
Our biggest challenge was figuring out how we were going to get the Texas COVID data. At the start of the project, we couldn't find an API for COVID specifically in the state of Texas so we resulted to web scraping certain pages for our data.
Accomplishments that I'm proud of
We are proud of everything about this app and hackathon! We have never built any type of full-stack app so coming in not knowing much and coming out with a finished product is something we are very happy about and we are grateful for this opportunity.
What I learned
We've learned IOS development, many backend technologies, and other things that come with working on a group project.
What's next for COVIDTexas
Since we have a basic functional app, we hope to implement additional features that would make the application more unique!
Built With
node.js
python
swift
xcode
Try it out
github.com | COVIDTexas | The purpose of creating this project was to help users understand the current status of the global pandemic occurring through the illustration of COVID-19 data within the state of Texas. | ['Brandon Pham', 'Aarish 13'] | [] | ['node.js', 'python', 'swift', 'xcode'] | 28 |
10,501 | https://devpost.com/software/chess-chefs-3b148n | Homepage
Creating a new game
Gameplay with default skin
Selecting your skin
Gameplay with "Texas Fight" skin
Move indicator customization
What it does
Play Chess with your friends within 3 keystrokes!
How We built it
We built it using React as our frontend, Firebase API as our backend, and Firebase's Realtime Database (NoSQL) as our database. Most every graphic on the site was constructed with Photoshop.
Built With
css3
firebase
github
heroku
html5
javascript
jsx
photoshop
react
Try it out
www.chesschefs.com | Chess Chefs | Play Chess with your friends. No sign up, no ads. | ['randyyu13 Yu', 'stevenrsun'] | [] | ['css3', 'firebase', 'github', 'heroku', 'html5', 'javascript', 'jsx', 'photoshop', 'react'] | 29 |
10,501 | https://devpost.com/software/faction | Inspiration
As a result of COVID-19, billions of people are forced to stay at home. One of the affected groups that resonated with us was students. As current college students ourselves, we understand how difficult it is to build a community of learners in the present environment. Yet we also know firsthand how important such a community is in order to succeed in online courses.
At its core, Faction is really about connecting people. We believe that the best learning occurs when it’s done along with others.
What it does
Faction works by bringing together students taking Massive Open Online Courses who might otherwise be studying alone. We match these students into small, virtual study groups. Within each study group, we provide a feature-rich educational environment so that learners can support and encourage each other as they progress through the course.
How we built it
We began by designing the application in Figma. Then, we implemented the frontend using React and the Material UI component library. At the same time, we designed and implemented the API routes using Node.js and Express.js and connected our backend application to MongoDB.
Challenges we ran into
The first major challenge was creating the design documents for the application. We realized that simply starting with coding will lead us nowhere. So instead, we started by defining the use cases for Faction and writing design documents. For frontend it was layouts and UI Research. Backend was focused more on System Design, OOAD, DB Schema.
The second challenge which we faced was the first time we tried to deploy the application. We used different domains for hosting backend and frontend on Heroku, so we ran into errors such as Cross-origin resource sharing.
Accomplishments that I'm proud of
We are especially proud of all the new technologies that we learned such as the MERN (MongoDB, Express.js, React.js and Node.js). It is a very sturdy and modern tech stack for creating easily scalable and robust web applications. We also learned a lot about Software Development Life Cycle and the importance of Agile.
Most importantly we are really proud of creating and hosting a web application from scratch even though we were not familiar with the technologies being used. We learned a lot about the different aspects of application deployment and the importance of having multiple environments (Testing and Production).
What's next for Faction
Our web application is a great boilerplate for Faction’s future potential. We want to add more functionality in our product so that students can have access to more features such as a discussion forum and live office hours with verified mentors. We also hope to more easily integrate MOOCs data to automate group creation on Faction using a simple browser extension. Lastly, we aim to increase fluid interaction between students through a forum chat feature.
Built With
css
express.js
javascript
mongodb
mongoose
node.js
react
Try it out
faction-front-end.herokuapp.com | Faction | An online learning platform that brings together students to collectively support each other | ['J Y', 'Kristy Wu', 'Gaurav Thapliyal'] | [] | ['css', 'express.js', 'javascript', 'mongodb', 'mongoose', 'node.js', 'react'] | 30 |
10,501 | https://devpost.com/software/covid-19-wise | Inspiration
With the onset of COVID-19, it is harder for people to do everyday tasks such as going to the grocery store, going outdoors to exercise, and going to restaurants. We wanted to create an iOS application that allowed people to see areas of high population density so they could make more informed decisions on which locations are safer to visit. With the privacy concerns currently facing contact-tracing apps, we wanted to allow users to have the option of keeping a private log of their location history. We think that by targeting population density and contact-tracing with features of our app, we can help the community reduce the number of COVID-19 cases.
What it does
Our application has two modes--Guest and Logged-in User--that allows users to choose whether or not they want to create an account with our application. For Logged-in users, our application allows them to mark their location, view a population density map (created from data from other users who have marked their locations), and view a personal history of locations the user has visited in the past 14-days. If the user chooses Guest mode, they can only view a population density map made up of location data from Logged-in Users who have marked their location.
How we built it
We used Xcode and Swift to create our application. We used the storyboard feature to create paths from screen to screen for our application and hard-coded some of the other features using Swift. We viewed various tutorials for MapKit, Swift, and Xcode as this was our first time using these tools.
Challenges we ran into
Since we learned a new software and coding language for this project, we had some trouble combining all the different aspects of our application. For example, we started off with using SwiftUI in Xcode but then switched to Storyboard so we could include MapKit. Lots of trial and error!
Accomplishments that we're proud of
We learned a new language and participated in our first hackathon!
What we learned
We are proud we learned about iOS development and now know the basics of Swift and Xcode. We also gained experience working in a hackathon setting. We also learned how to include and work with APIs in iOS development.
What's next for COVID-19 Wise
Now that we have a working outline for our application, we want to improve it and make it more user-friendly. We want to create a heat map style population density map rather than using icons. We also want to create a pop-up for users to mark their location rather than having to switch tabs to accomplish this. Creating a help section for users to troubleshoot and technical difficulties would make the app more user-friendly as well. Lastly, we would like to tie in social media or a blog so that a larger community is formed to attract more users with a common goal in mind.
Built With
canva
ios
mapkit
storyboard
swift
swiftui
xcode
Try it out
github.com | COVID-19 Wise | An iOS application to create a community and help users make more informed decisions about going out. It helps them with contact-tracing to reduce the number of COVID-19 cases. | ['Meghana Thota', 'Amruta Deole'] | [] | ['canva', 'ios', 'mapkit', 'storyboard', 'swift', 'swiftui', 'xcode'] | 31 |
10,501 | https://devpost.com/software/lean-learn-during-earning-upskilling-all-workers-now | IMPORTANT
Other content:
If you want to take a look at the
admin panel
, please click here:
Youtube
Do you want to look at the
entire video
with research? Please click here"
Youtube
Inspiration
Due to the COVID-19 pandemic, many low skill workers have lost their jobs resulting in record breaking numbers. The civilian unemployment rate is
currently at 10.2%.
That leaves
16.3 million people unemployed.
As a result, The Mad Hackers decided to tackle this extreme issue which has lost the primary source of income for many families. It is essential for these workers not have this vulnerability right now and in the future and as a result we have created LEAN to help solve this issue.
What it does
LEAN has 2 main components: an admin panel and a user panel. The admin panel allows the company to upload information and see current candidates. We chose to not make this an aggregator because the employer has to be willing to have employees without a college degree - merely online certificates and whatever projects they come up with from those online courses. Employers get the benefit of having a qualified employee for a lower starting price, whereas employees get higher paying jobs than what they already have and once they leave the company, they can use that experience to catapult themselves. The user panel allows the user to get information about various jobs that are around, like a standard job-finding app.
However, what makes LEAN stand out is that it allows users to learn the skills from MOOCs, which you can search for within the app itself.
LEAN also helps you look at
job trends
with a
built-in prediction view
, filled with interactive visualizations and graphs.
You can find yourself a temporary job within LEAN too! Just go to the low-skill jobs pane, and find something that interests you. That way, you can make money while learning and preparing for your next job. You can also get money by going to the funding pane to take a look at different loan and scholarship opportunities (not included in video - added after recording and submission - will be pushed to GitHub soon).
LEAN also has a
forum for users to be able to talk with each other about their experiences and support each other.
LEAN also has an integrated
Projections tab
for jobs in the workforce for insight of the future
LEAN also has a
Courses tab
which allows you to input your courses and it will use an API in order to retrieve courses.
How I built it
The Admin panel was build using Vue.js. We used buefy to create a simple but elegant theme that made development both quick and stylist. Then, we use Google Cloud Firestore to manage our data in the cloud so that information could eventually be read by the prospective employee.
The course search integration was built in much of the same way, linking to Classpert to leverage their huge database of MOOCs across over 30 websites. This was then integrated into the application.
The job trends panel was custom-built using Datawrapper to create interactive visualizations, using data from the US Bureau of Labor Statistics. These panes where then embedded into the application.
The forum was created using tribe.so, an application similar to discourse. We chose this because it has a lot of features and is styled extremely well. We linked that into the application similarly to others.
The react native app was created using several apis and features. For the Home page, we used Google Cloud FireStore to store and retrieve data to manage the employer/admin and user interfaces. This would allow the posts from the employer on the web, to be posted on the react native app. For UI, we used react-native-base which allowed for more customizations than we previously had in order to provide the app a more premium and modern feel. For the courses tab, we created a page using an API provided by ClassPert in order to get the course data retrieval. We used react-native-maps in order to create the maps interface and find the current location of the user and display it. Additionally, the API provided by Indeed.com allowed us to retrieve temporary jobs within queries we passed through it. For the forum page, we used tribe.so and Web-View in order to integrate the forum into the application and make it readily modifiable by users. For the design tabs and the cool animation, I used react native navigation material tab navigators which allowed for the rich animations.
Challenges I ran into
There were challenges in implementing the UI on the RN App due to deprecations and Dependency errors.
There were challenges with GitHub not allowing files to be pushed correctly
There were challenges figuring out how to access certain datapoint
There were challenges with getting image uploading for the admin panel (logo).
There were challenges with making sure that data was being worked with properly, as sometimes, the views themselves would have impediments blocking us for hours.
What I learned
I learned how to manage time, how to work efficiently, how to not procrastinate and how to work together with multi-platform concepts which I had never implemented before.
What's next for LEAN
We hope to implement this app into the google play and iOS app stores to help those currently in need of such an app. We plan on styling better in order to get a more professional design. Additionally, we hope to add more features allowing for the user to connect to the employer more easily. We have many other ideas that we wish to implement, however time is one constraint that will always limit us but yet pushes us to work our hardest.
We would like to thank these hackathons we participated in for giving us the ability to demonstrate our skills and also challenging us to push them. We both found it to be a very valuable experience.
Built With
apis
cloud
expo.io
firebase
firestone
google
location-services
react
react-native
react-native-maps
vue.js
Try it out
github.com | LEAN (Learn while Earning, upskilling All workers Now) | LEAN is a job-finding website that allows users to upskill themselves on the job hunt while still being able to support themselves. | ['Vijay Daita', 'Om Joshi'] | ['Grand Prize', 'Team Submission Prize'] | ['apis', 'cloud', 'expo.io', 'firebase', 'firestone', 'google', 'location-services', 'react', 'react-native', 'react-native-maps', 'vue.js'] | 32 |
10,501 | https://devpost.com/software/chikin-tinder | Inspiration
"where should we eat?"
"where do
you
want to eat?"
"idk you pick"
We've all experienced this dilemma -- it has even inspired multiple memes across the internet (
ex
). Back when we could go out and eat with friends and family before COVID-19, deciding on a restaurant to eat at would sometimes be the most difficult and stressful thing in the world. Luckily, someone on Reddit came up with the genius idea of a Tinder-like app to match people's restaurant choices, and we've made that a reality!
What it does
Chikin Tinder allows groups of people to create party rooms with randomly generated restaurants based on criteria set by the organizer, such as location, number of restaurants, and price range. The organizer can invite others to the room using a code sent via text, and they can swipe through the restaurants Tinder-style, view additional details, and see which ones they end up matching on.
How we built it
React Native, Firebase, Expo, Yelp API, Figma
Challenges we ran into
Some of our biggest technical challenges were getting push notifications to work properly within Expo and working with the Yelp API to fetch the proper data we needed.
In terms of designing the app, we wanted to incorporate a fun personality throughout the UI while also maintaining simplicity and consistency in overall UX.
Accomplishments that we're proud of
Given our busy summer schedules of working in internships and other projects, we're proud of consistently making time to work on our own parts of the app, meeting up every week to review our progress, and finally finishing the MVP of our app. Given that half of the team was new to React Native and mobile development, and the other half had only worked on one mobile app project before this one, we all learned a great deal of new skills and were able to come together to complement each others' skills in terms of front-end, back-end, and design to build a fun app that could be a real solution to a common problem.
What we learned
It's always important to test your application on different screen sizes to ensure consistency in UI and behavior across devices. We also found that taking some time to wireframe and lay out the overall app flow and user stories helped us expedite and streamline the dev process. Lastly, in these last few days, we learned that the presentation of the end product is just as important as its functionality and complexity.
What's next for Chikin Tinder
We'd love to add a feature where users can make customized sets of restaurants that they regularly eat at and be able to swipe through those in party rooms. To make the app even more engaging, partnering with new, local restaurants to provide discounts for users could encourage people to try novel eateries in their communities and form stronger relationships with local restaurant owners through food.
Built With
css
firebase
html5
ios
javascript
react-native
Try it out
github.com | Chikin Tinder | Tinder-for-Restaurants | ['Brian Sui', 'Janet Huang', 'Jenny Chang', 'Ashley Ahn'] | [] | ['css', 'firebase', 'html5', 'ios', 'javascript', 'react-native'] | 33 |
10,501 | https://devpost.com/software/self-aware | Medi-Box 3D Designing
Medi-Book Web Application Interface
Medi-Box
After 3D Printing, Final Design
hardware
Medi-Box
Doctors List on Medi-Book
Medi-Box
hardware
this picture shows our software with hardware and mobile application
working with ecg module
working
Inspiration
I have seen many peoples who live in remote areas, who move from one city to another in case of job postings. These people don't know about availability of hospitals, clinics, medicals and verified doctors near to them. So, we have developed a platform where people can easily connect with verified doctors near to their area by searching for doctors on our platform based on location.
The people of remote areas even big city people don't know about the latest medical schemes provided by the government. So, they can't use these very crucial medical schemes for their own. Our project will aware all patients about government medical schemes with eligibility criteria.
Their are so many people who are handicapped and faced difficulty in going to the hospitals for regular checkup of basic body parameters. Our project have IoT based box (a wellness device), which will help patients to have their normal body parameters reading at their own home and they can share their readings with doctor.
What it does
This project is for all those peoples who live in remote areas, valleys, hills, for those who are often move from one city to anoher because of buisness meetings and other things. All these peoples do not know about the availability of doctors, hospitals, clinics near to them. Even in case of COVID-19, this software is best to search doctors, hospitals, medical shops and clinics near to them. On MEDI-BOOK, patient can search doctors based on location selected and specilization of doctors. The major advantage of this web application is that peoples can see Government provided Medical Schemes very easily. This feature is not available on any existing projects. This software also have chat system through which patient can send their symptoms, previous medical reports and readings from MEDI-BOX to the selected doctor of any country and doctor from their end can prescribe patient very easily. Patients can have their MEDI-BOX readings on this software. Pateints can book appointments of any doctor. One of the major feature of MEDI-BOOK is that it will show live tracking of COVID-19 cases and news on it for the sake of patients and every time new case occurs in the area of patient, he/she will get notification of it automatically. If we see on larger picture, this software will going to help a lot to the world if we launch it.
With this, we have a wellness device "THE MEDI-BOX" which is a small box that can be connected with an android application and measures the human body parameters which includes "BODY_TEMPERATURE, PULSE RATE, ECG, HEART BEAT" and also "LIVE READING OF POLLUTION, AREA TEMPERATURE and HUMIDITY" of the area in which patient is currently stay, to check whether the current environment is suitable for the pateint or not. This box is easy to carry. All the readings will automatically send to cloud, MEDI-BOX mobile application and MEDI-BOOK software and these details will shared with doctor. We are now working to convert this box into a wearable band.
How I built it
It is built using basic programming languages and backend languages. I used thingspeak cloud for medi-box data storage and mysql for medi-book data storage.
Challenges I ran into
Sending real time data to cloud, but I made it.
Accomplishments that I'm proud of
Patients now will be aware about medical schemes which they can use for their own welfare.
Patients can easily connect with verified doctors near to their area.
Patients can have their wellness checking at their own home very easily.
What I learned
How to gather all data and use of web scraping also.
What's next for Self Aware
We will work on it and we are working on turning the medi-box into a wearable band and adding more functionality to them.
Built With
3d-designing
3dprinting
android-studio
arduino
bootstrap
css3
dht11
ecg-module
esp8266
firebase
google-maps
html5
java
javascript
jquery
lm35
mit-app-inventor
mq135
mysql
php
thingspeak
Try it out
drive.google.com
drive.google.com
drive.google.com
drive.google.com
drive.google.com
drive.google.com
drive.google.com
drive.google.com
drive.google.com
drive.google.com | Self Aware | The project is for the remote areas people and handicapped people who faced difficulty to go hospital/clinic for regular treatment. This project made simple for them to connect with doctors from home. | ['Rishabh Gupta', 'VIVEK CHHABRA', 'Amit Goyal', 'Rajneesh chaturvedi'] | [] | ['3d-designing', '3dprinting', 'android-studio', 'arduino', 'bootstrap', 'css3', 'dht11', 'ecg-module', 'esp8266', 'firebase', 'google-maps', 'html5', 'java', 'javascript', 'jquery', 'lm35', 'mit-app-inventor', 'mq135', 'mysql', 'php', 'thingspeak'] | 34 |
10,501 | https://devpost.com/software/covid19-bedchecker-mfhlv2 | landing page
signup
portal
Inspiration
We felt the difficulty covid19 patients face as they have to visit to hospital to check whether any bed is vacant in the hospital, if there's nil then the patient has to reach another hospital which creates problem for patients as well as hospital staffs.
What it does
Our web application allows hospital management to directly feed number of beds available and it is being added dynamically into the map. Patient can access this map to see the availabilty of beds in his/her region as well as get directions to the hospital.
How we built it
We used Bootstrap for front end and php for backend and ms-sql for database. We used python and jquery for chatbot. We used pandas streamlit for creating maps and displaying values.
Challenges we ran into
Hosting our data science web app was a bit tedious for ous.
Accomplishments that we're proud of
User can zoom in till he/she sees every streets and the hospital name and number of beds available and availabilty of ventilators.
What we learned
We learned new python libraries that we are looking forward to implement in future as well.
What's next for Covid19 BedChecker
Tying up with hospitals to get real time data, instead of a data set.
Built With
chatbot
css
html
jquery
pandas
php
sql
streamlit
Try it out
github.com
apexxcovid19999-com.stackstaging.com | Covid19 BedChecker | Through our web app a patient can check the availabilty of number of beds availabe for covid patients along with exact location and can filter out the hospitals containing ventilator options. | ['Amit Singh', 'PRAKASH SINGH'] | [] | ['chatbot', 'css', 'html', 'jquery', 'pandas', 'php', 'sql', 'streamlit'] | 35 |
10,501 | https://devpost.com/software/instant-chats-29pruj | Home Page
login signup
Video calling
Inspiration
Various organisations are struggling to work together due to work from home norms. Also family relations were being affected due to Covid19.
What it does
It bridges the communication gap that occured in the community due to the pandemic through chat/call/video-call.
How we built it
We used HTML CSS JS for Frontend and PHP MYSQL APIs for back-end. Python JS For Chatbot.
Challenges we ran into
As our team members were working remotely we were unable to help each other out efficiently. Also we had some problem while setting up video call feature.
Accomplishments that we're proud of
Video-call/Voice-call/Attractive UI/Instant Chats
What we learned
We learned the concepts of communication and network engineering.
What's next for instant CHATS
We'll upgrade our databases to more efficient hosting service.
Built With
apis
chatbot
css
html
javascript
mysql
php
python
Try it out
github.com
instantchat.epizy.com | instant CHATS | We are aiming for a messaging app where a person can use both his personal and officework.He can message video call and fileshare. an office can setup their own group where every member can fileshare. | ['Shubham Nagpal', 'Amit Singh', 'Prakash Rajpurohit'] | [] | ['apis', 'chatbot', 'css', 'html', 'javascript', 'mysql', 'php', 'python'] | 36 |
10,501 | https://devpost.com/software/donationfinder | Home Page
Login Page for Organizations
Sign Up Page for Organizations
Organization Profile Page
Map results of a donator's item search
Additional Contact Details
Inspiration
A lot of people have extra items in their homes and may want to donate them but through personal experience, we realized that something that might inhibit people from donating is the difficulty to find an organization to donate to. Especially, if you only have one or two items to donate or they are relatively uncommon items, it can be a struggle to find a place that takes them in. So, we thought an app that allows donators to locate nonprofit organizations easily would save donors a lot of time and bridge the gap between donators and nonprofits.
What it does
It is a web application that lets donators enter specific items they wish to donate and get results of all the matching organizations that need those items. The results are shown on a map with markers of the locations of the nonprofits as well as a contact details section. The organizations that are displayed on the map are those that register with the app.
How I built it
We used Java and the Java Servlet technology in a Maven project to create the web application. We also used html and css and javascript to build the UI. To get the map, we used the Leaflet and Mapbox APIs.
Challenges I ran into
Since this was the first web application we created, it was a challenge to get started and learn a variety of new skills needed to build the project. Some things like AJAX and Javascript's fetch function were very new and difficult to grasp at first but we were able to figure out any problems by getting help from google and especially Stack Overflow.
Accomplishments that I'm proud of
We're proud of trying a lot of new things with this project. Each idea that sprung up led to google searches and lots of learning. From creating animations with CSS and Javascript to using Bootstrap to style the pages, we were constantly being challenged and although it was hard at times, it was also really fun and it feels very satisfying to complete a project from beginning to end.
What I learned
We learned a lot from the basics of what a web application is to how to build one using different technologies and APIs. We also grew our knowledge of html and css and and good design techniques.
What's next for DonationFinder
-Search filters with options like within a certain radius or the size of the organization
-A way for donors to keep track track of the places they donated to
-More secure log-in facility for organizations
-Provide email or text options to contact the organizations directly through our web application
Built With
bootstrap
css3
html5
java
javascript
leafletapi
mapboxapi
Try it out
github.com | DonationFinder | A fast and easy way to find nonprofits that need your items for donation | ['Shaili M'] | [] | ['bootstrap', 'css3', 'html5', 'java', 'javascript', 'leafletapi', 'mapboxapi'] | 37 |
10,501 | https://devpost.com/software/move-it-covid | Inspiration
Due to the pandemic, it is important that people practice social distancing to slow the spread of the virus, and that they wear a mask to not only protect themselves from droplets with the virus, but to also prevent them from risking others with their own droplets.
What it does
It is an endless runner game with cute graphics where the player has to collect powerups such as toilet paper, masks, and hand sanitizers, to be more immune to the enemies, which are coughing maskless people.
Challenges we ran into
We were initially gonna build the app with React, but we struggled learning it, so we switched to Javascript. Upon transitioning, we struggled with sprite animations and building the overall app. On top of this, our conflicting schedules prevented us from meeting to work on it together.
Accomplishments that we're proud of
We learned the basics of making a game in Javascript, and are excited to learn more!
What's next for Move-it Covid
We want to actually have the coughing enemies in the game, as well as include a start and end screen.
Built With
canvas
css
html
javascript
Try it out
github.com | Move-it Covid | We're building an endless runner game geared towards a younger audience to teach best practices to keep themselves safe and prevent the spread of COVID-19. | ['Cirill Dalangin', 'Shanice Smith'] | [] | ['canvas', 'css', 'html', 'javascript'] | 38 |
10,501 | https://devpost.com/software/zeoco | null
Built With
null | null | null | ['Preet Batavia', 'Shreesh Tripathi', 'KARTHIK R', 'Gokul Puthumanaillam'] | [] | ['null'] | 39 |
10,501 | https://devpost.com/software/devarmy-lwu9mc | Home
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Inspiration
We, as students, usually face this problem! Not Anymore
Have a great idea in mind, are excited in the beginning, start working on it, and then the graph goes on tending to zero. This trend shows a reasonable rate of creativity but a depleting rate of implementation. I have worked on several projects, the ones having the potential to become the next big startup, but they go in vain because sometimes a particular tech stack is not known, or you have made too many commitments that you forget the exciting ones. Also, after talking to people at our institution, people tend to complete things they have taken up when they have a partner whom they are accountable to. In these situations full of problems, what developers require is a platform for themselves, not just some random WhatsApp and Telegram groups, which are muted as time passes!
What it does
DevArmy serves as a platform where one can find people to collaborate on projects with #NeedSimran and #ProjectIdea. One can also find a partner to do Online courses with #NeedSimran. One can seek help about some topic with #NeedHelp and take advice with #NeedAdvice on which online course to take up and other stuff. In case someone doesn't have the means to work on an idea but desperately feels it should be introduced to people, we have #ProjectIdea to help. The platform aims to bring in #CodeReview, #DesignReview, and #LinkedInReview in the coming times. Remember--"We rise by lifting others" - Robert IngersollThe platform DevArmy aims to bring a platform for the developers to solve their problems. A platform by the Developers, for the Developers! What we call the members of the community is the "Soldiers." Soldiers seeking solutions use the language of #hashtags
Challenges Solved:
How to find people for projects? Use #NeedSimran along with skills And Post your requirements clearly
Example-
I'm planning to build a Geeks Dating Site,
I'm good at Frontend using React,
Looking for someone to handle Backend, preferably college students.
NeedSimran
How to Share Project Ideas? Use #ProjectIdea
Example-
Geeks Dating Site #ProjectIdea
Chatbot for career counseling #ProjectIdea
We will try to bring up rewards and contests for the best ideas in the future!!!
How to get help from others? Use #NeedHelp Tip- Make sure to be very specific
Example-
I'm stuck with the Leetcode Problem, "Jewels and Stones".
NeedHelp
P.S. When you ask for help, make sure to help others also.
How to seek advice/guidance from Mentors? (Future Implementation) Use #NeedAdvice
Ex-
Is Javascript enough to crack Uber? #NeedAdvice
Do backend engineers earn more than frontend engineers #NeedAdvice
How to share some fantastic articles/posts/resources? Use #Resources.
Coming Soon…
How to get my Code/Design Doc Reviewed? && Get LinkedIn Reviewed? Use #CodeReview & #DesignReview Make sure to add a link to the Google Doc(make it public) P.S. When you ask to review, make sure you help others also.
How I built it
The app is built using Flutter for frontend from Google and Django rest API hosted on Google Cloud.
Challenges I ran into
Even today, when many developers are using flutter, the BLoC logic Documentations and practical implementations are not present. Fewer tutorials are present on working with Django REST Api and flutter, which makes our work less efficient. Even the existing university pattern of education does not give proper guidance about modern technologies. Our Team tried leveraging the power of elastic search for the hack, but again, lack of Documentation was a significant issue.
Accomplishments that I'm proud of
I started with BloC design in flutter.
What I learned
Django Rest API, flutter apps widgets
What's next for DevArmy
Coming Soon…
How to get my Code/Design Doc Reviewed? && Get LinkedIn Reviewed? Use #CodeReview & #DesignReview Make sure to add a link to the Google Doc(make it public) P.S. When you ask to review, make sure you help others also.
How to seek advice/guidance from Mentors? (Future Implementation) Use #NeedAdvice
Ex-
Is Javascript enough to crack Uber? #NeedAdvice
Do backend engineers earn more than frontend engineers #NeedAdvice
Partnering with Hackathons serving as a platform for hackers to collaborate.
Domain.com
remote.space
Built With
django
elastic
flutter
google-cloud
heroku
mongodb
Try it out
github.com | DevArmy | Have a project in mind, need some help. Are you a UI ninja, and need a database warrior. Post your project idea on our app and find a partner who matches your requirements to complete the project. | ['Dipti Modi'] | [] | ['django', 'elastic', 'flutter', 'google-cloud', 'heroku', 'mongodb'] | 40 |
10,501 | https://devpost.com/software/teachme-74250z | This is what a 'teaching' page looks like - teaching students the key essentials.
This is what a question page would look like.
This is what the page would look like if they got it correct.
This is what the page would look like if they were incorrect.
This is what the projects page looks like.
Inspiration
As a student who was thrown into learning a particular language due to the school curriculum, I never really got the opportunity to learn and explore other languages without having to sign up for a full course. So I developed this product with young students in mind, so that they can go above and beyond and explore different langauges before choosing one to learn fully.
What it does
This website allows students to explore various languages and teaches them the 4 basic skills: printing and outputting, variables, inputs and arithmetic calculations. Following this, they can work on projects where they have to utilise the skills learnt in order to complete theem, and they can also play games which are made in that particular language.
How I built it
In order to build this I used HTML,CSS and BootStrap which did most of the front end work. For the back end, I used PHP, MySql and JavaScript.
Challenges I ran into
As this was one of the first big projects I have done, there were several challenges along the way. However, one of the main challenges I had was balancing the content with the presentation. Through trial and error, and testing it out on the target age audience, I was able to identify what worked well and what didn't. I made sure that any changes made were done for every page, in order to ensure consistency.
Accomplishments that I'm proud of
I was assigned a team at the beginning however they all gave up within the first few weeks, so I am glad that I was able to persevere and complete the project on my own. I am also quite proud of the way the project came together, ensuring that the content was presented in an engaging way to help young students. I have tested this with a few students, and all of them have decided to start learning a new language, some have chosen scratch and a few chose python!
What I learned
Given the large time scale of this project, I have learnt how to manage my time constructively in order to reach my end goal. I also learn how to use APIs in order to help make this project even better!
What's next for TeachMe
I would like to expand this project further and teach even more programming languages. I would also like to customise the platform to each student, so that it can recommend languages to explore based on what they previously did and what they liked / didn't like
Built With
bootstrap
css
html
javascript
php
sql
Try it out
github.com | TeachMe | A website to give young children the opportunity to 'taste' different programming languages | ['Roshni Vachhani'] | [] | ['bootstrap', 'css', 'html', 'javascript', 'php', 'sql'] | 41 |
10,501 | https://devpost.com/software/mask-detection-system | Project LOGO
User Interface
System detecting a mask is worn
System detecting no mask is worn
Plot showing the accuracy of testing
INSPIRATION
Given the current trends in incidence and underlying healthcare system vulnerabilities, Africa is facing a lot of problems due to the Covid-19 pandemic such as a drastic reduction in medical commodities and supplies following border closures and restrictions on exports, and financial resource limitations.
A lot of people these days are avoiding the use of basic tenets of hygiene during this crucial time such as wearing masks and gloves in public places. Moreover, they endanger establishments by not abiding by the guidelines and compromising the safety of themselves and others.
That is why we came up with the idea of Maskaught, a simple mask detection system that can be placed outside any shop which has access to basic surveillance cameras.
WHAT IT DOES
Maskaught is a convenient mask detection that system that can be placed outside any shop or establishment. This system would ensure that those who are found to be not wearing a mask would not be allowed to enter inside. Outside a mid-range or large scale shop with security, it can act as a helping hand to the security guard by minimizing his/her interaction with consumers with the help of this software and ensure their safety.
HOW WE BUILT IT
We first trained the system by providing a dataset containing pictures of people with and without masks. After training the system, all the images were converted into an array and two
deep learning models
for detecting face and mask were created. The accuracy of testing was also plotted as shown in the graph. Both the models were then loaded into a new Python file and a camera was integrated into the mask detection system. The system would then detect the mask on the face and displays the accuracy of detection. A
text to speech software
was also integrated within the system which would guide the customer throughout the whole process of detection.
CHALLENGES
Converting our python project into a web application was a significant challenge that was faced by our team. However, we used python's
Django
framework to bridge the gap between our python software and HTML. As a result, we were able to build an interactive and user-friendly interface for the project.
ACCOMPLISHMENTS
Completing a challenge always feels satisfactory. Thus the entire project from the mask detection to the web application to our business model are all accomplishments that we are proud of.
WHAT WE LEARNED
Through this hackathon, we had the opportunity to learn how to train a deep learning model and create a python program integrating the use of Keras, OpenCV, and MobileNet along with text to speech conversion software (pyttsx3). We also applied our web development skills to attach the python program to the HTML one using the Django framework.
FUTURE STEPS
Our idea also focuses on promoting the rise of small domestic businesses that do not get a lot of customers as they’re not able to keep a track of whether all their customers are wearing masks inside. This may sometimes procure them with financial losses as it may cause customers to stop coming to these shops due to the ease of contracting the coronavirus with people without masks.
Moreover, since our idea is inexpensive to enact where we need to only connect our web app to the camera the cost involved to adopt this system is pretty much minimal.
One more plus point regarding our system is its expanded use and modifications which can be made after adopting it. It can be further applied for security in the future when we are safer against the pandemic.
It can also add in more scanning features in the future like scanning for gloves.
With further improvements, this system could be integrated with CCTV cameras to detect and identify people without masks and could be used in the imposition of fines for people who don’t wear masks by the government.
Built With
bootstrap
css3
django
html5
keras
opencv
python
tensorflow
Try it out
github.com | MASKAUGHT | The convenient mask detection system | ['Mohammed Ozair', 'Parin Joshi', 'Fabin Joe Flasius', 'Rishabh Saini'] | [] | ['bootstrap', 'css3', 'django', 'html5', 'keras', 'opencv', 'python', 'tensorflow'] | 42 |
10,501 | https://devpost.com/software/alois-memory-care-assistant | Features
AlzBuddy is an interactive memory care assistant designed to improve the lives of Alzheimer's patients around the world. The tool is particularly useful in nursing home settings and applications. The tool itself has 6 main "tabs" with specific functionalities aimed to improve multiple facets of the patient's life.
The first tab is the "Sounds" module. The Sounds modules contains a variety of songs and commercials from the 1960s and 1970s that can help jog the memory of Alzheimer's patients. The app also contains common animal sounds, which is a great activity to help the patient remember various aspects of common life effectively.
The second tab of the app is the "Game" module. The Game module contains an interactive coloring game designed to help Alzheimer's patients with coordination and focus. The game itself was recommended by a medical doctor with decades of experience in the field. The game requires users to color corresponding buttons based on a provided task.
The third tab of the application is the "Notes" module. The Notes module contains a page that allows users to type in different reminders, messages, or statements easily. The module also includes a speech-to-text feature for patients who may prefer not to type or unable to do so. The notes can easily be cleared as well.
The fourth tab of the application is the "Facts" module. The Facts module of the app contains different information that is aimed at helping to orient the user in their surroundings. The facts page includes the date, the time, and the location, based on detected values. It additionally includes a simple image that helps point important directions for orientation purposes.
The fifth tab of the application is the "Pictures" module. The Pictures module of the app includes pictures of various world leaders, famous locations, celebrities, and more. This is designed to help jog the memory of the patient and generally serve as a talking point for 1-to-1 caregiving. The module also has a button that helps the user go to their gallery efficiently.
The sixth tab of the application is the "Vibrations" module. The Vibrations module contains soothing vibration patterns that are aimed at engaging the patient and providing tactile input. This is a simple module that works with the click of a button.
Events
We are also going to several events soon to market our app further. One event we are going to is an event near Austin, TX in August 2021. Over 700 nursing home and healthcare professionals are expected to show up, alongside several hundred potential consumers. The event is specifically about Alzheimer’s Disease and dementia, which increases the likelihood that the individual people can either become users of our app or tell a loved one who has dementia to use Alois. This event will be a significant event in terms of marketing for Alois. Many nursing home chains in Texas have nursing homes outside of Texas and even outside of the United States. If we become acquainted with these nursing home chains, we can expand to other nursing homes in the nursing home chains outside of Texas and internationally.
What's Next
There are multiple key additions we are planning to make to the application in the future. These new features will be designed to expand the functionalities of the app to be more useful for broader market groups and diverse communities.
The language-expansion of the application will involve the addition of new languages, including Spanish, Hindi, Mandarin Chinese, and French. We are working with volunteer translators to make this happen, and this will generally aid us in expanding to diverse marketplaces across the world.
We additionally are looking into new modules in the application that could do the following: assist caregivers specifically, add features for later-stage patients, allow for greater interactivity, and provide higher-functionality games and visuals.
Finally, we are looking into the general market-expansion of the app for new cognitive disorders. This would include expansion into new conditions like Parkinson's, general dementia, and Traumatic Brain Injury. It also would include rebranding initiatives to attract patients and diminish stigma and greater module customization and interactivity
assistive gadgets/plug-ins to enhance the experience.
Built With
android-studio
java
xml
Try it out
play.google.com | AlzBuddy - Memory Care Assistant | Our application provides a user-friendly and straightforward way to assist, entertain, and engage dementia patients around the world. | ['Vedant Tapiavala', 'A B'] | [] | ['android-studio', 'java', 'xml'] | 43 |
10,501 | https://devpost.com/software/eduquix-v2-0 | EduQuix- Quiz
EduQuix- Meetings
EduQuix- SignUp
EduQuix- LogIn
Meet the Creators
EduQuix- Home Page
EduQuix Store- Home
EduQuix Store- Books
Inspiration
Corona Virus pandemic lead to online teaching everywhere, That made us to think of making a project solving the problem related to online teaching and bringing every needed features to a single educational platform.
What it does
Some of the features are listed below:-
It asks students and teachers to sign up or login. After that, it provides the students zoom URL to join the online meeting, teachers has to start their own meeting and has to upload the meeting ID and password to the website server so the students may join.
After the meeting ends, the students has to solve quiz related to the class which will automatically give them marks according to their performance. Teachers get excess to upload the quiz.
Teachers may assign students projects or assignments using this platform and students can submit their work before the deadline.
Also this project enables users the access to order school essentials like books, pens and other stationery online through it.
How I built it
The delivery part was built using wix.com's theme and by modifying it into stationery store website.
Android app was made using Kodular.
Rest of the complete website was made using Bootstrap Studio by integrating website with, Zoom for the meetings, Firebase to get the meeting ID and password for the Zoom meeting and then linking the main site with the delivery site made through wix.
Challenges I ran into
I was new to website development, so, Working on the project enhanced my experience with Website Development.
Accomplishments that I'm proud of
I got to learn about website development as I'm beginner to website development.
I got to learn integrating firebase to websites as well as android apps.
I was a beginner to bootstrap but now I have enough knowledge to make a website work using bootstrap
What I learned
Team Work is a major thing I got to learn by working with teammates belonging to different parts of the world.
I was new to website development. So I got to know more about website development using bootstrap and wix.com
I used to integrate mobile apps with firebase but this project gave me an opportunity to learn about integrating websites with firebase.
What's next for EduQuix
In future, we plan to make an iOS app so it would be easier for everyone to use it even for them who don't own an android phone, computer or a laptop.
We would try to add notification pannel in the project through which students may get aware of emergency updates like if class gets postponed or gets canceled.
We would introduce, free online tutorials, so that students may learn more, outside the classroom.
We will also add a feature, for easier note taking during classes, which can also be accessed, after lessons for future references.
A feature for teachers, to upload files such as presentations, to allow contribution for both students and teachers.
We can tie up with local stationery stores to provide users same day delivery.
Built With
bootstrap
css
html
javascript
kodular
wix
Try it out
github.com
keshavmajithia.github.io
hkhrapps.wixsite.com
drive.google.com
drive.google.com | EduQuix 2.0 | Endless Learning From Home! Seamless Delivery of School Supplies! | ['Keshav Majithia', 'Aanya P'] | [] | ['bootstrap', 'css', 'html', 'javascript', 'kodular', 'wix'] | 44 |
10,501 | https://devpost.com/software/cov-urgency-263law | Masks in our website
More masks
Disinfectants in our website
home page
Android App Starting
Food Items-App
Fruits-App
Masks-App
Navigation Bar-App
Medicines-App
Inspiration
Due to the COVID-19 Pandemic, news channels begin to spread awareness to get some emergency products but due to lockdown in almost all countries, it became difficult for everyone to go out and buy themselves emergency goods. As food delivery apps/software collaborates with local restaurants to deliver food, the same way, we came up with an idea, following the same principle, to deliver needy products to the users! So, we decided to work on a website and an app that solves problems of many, also within a day.
What it does
COV-Urgency is an all-in-one emergency product delivery software that delivers needy products to the users. Some of its features are:
Delivers products within a day
Ensures safety when delivering product; zero contact delivery
Providing all the necessities asked by the user
How I built it
The website was created using bootstrap studio
MongoDB is used to store user data
Android app was made using Kodular
Used google as a source of images
Challenges I ran into
Different time zones: We have a completely diverse team. Teammates belonged to different time zones like IST and EST. It was hard to collaborate. So, we decided to divide work and asked to complete it at a given time and then the final product was combined at last. We also had some issues building our website as we did not know advanced HTML and CSS so it was a learning process throughout.
New to backend programming: we were new to backend programming, and we got to learn basic knowledge about backend and we hope we would learn more in the future.
Accomplishments that I'm proud of
Enhanced our skills with frontend programming
Tried Backend programming for the first time, I would love to learn more in backend and would try to implement in real-life projects
COV-Urgency may employ people from different parts of the world to deliver products.
COV-Urgency may increase the profit of local store owners by collaborating with them and by bringing their products online.
What I learned
Backend programming
Team Work
Got to know about people from different parts of the world.
Used MongoDB for the first time as a database
What's next for COV-Urgency
The website needs some improvements like UI improvement and backend fixes.
We would introduce iOS app for COV-Urgency so that more people can get the benefit.
We would try to Collaborate with some local stores so, we may implement the project in real life as soon as possible
We would try to employ people as much as possible so that it would we beneficial for society.
Built With
bootstrap
css
github
html
javascript
kodular
mongodb
php
python
sql
Try it out
github.com
keshavmajithia.github.io
drive.google.com
drive.google.com | COV-Urgency | All in one Emergency Products Delivery Store that Delivers products The Same Day! | ['Keshav Majithia', 'smriti sharma', 'Aanya P', 'Evan Wang'] | ['Best Business Potential- Clerky Lifetime package'] | ['bootstrap', 'css', 'github', 'html', 'javascript', 'kodular', 'mongodb', 'php', 'python', 'sql'] | 45 |
10,501 | https://devpost.com/software/project-find-a-partner | Currently, due to the pandemic, many companies are closing and professionals are unemployed. There is a
need for a global platform that can be accessed by cell phone and / or computers in a simple way and that
entrepreneurs and professionals can access to conduct searches in order to find a way to interact with people
who have the same professional purpose. The entrepreneur must make his job needs and what he offers to
professionals available through standard forms. Professionals must make their professional experiences and
what they seek through standard forms available. Searches can be done manually or automatically by the
system by professionals looking for entrepreneurs and vice versa.
Built With
blockchain
datalake
flutter
mysql
python
Try it out
devpost.com | Project Find a Partner | This an information system for managing search for professional partnerships to provide interaction between unemployed people and entrepreneurs in search of professionals to form work partnerships. | ['Jose Alexandro Acha Gomes'] | [] | ['blockchain', 'datalake', 'flutter', 'mysql', 'python'] | 46 |
10,501 | https://devpost.com/software/offline-movement | App Logo
GIF
App Demo
App Ad Poster
Offline Movement
Offline Movement is a phone application that allows users to connect to others without using Cellular Data or the Internet. This Offline Messaging feature is secured by a peer-to-peer mesh network (Bluetooth) that allows for direct communication between smartphones.To enforce privacy the app includes encrypted messages and tools to blur individuals' faces in photos and vidoes. In order to ensure safety the app has a voice-activated video recording system installed. Offline Movement is a savior during disaster situations and mass gatherings.
Vision & Inspiration
As protests against police brutality have swept across the nation following George Floyd's Death, Protestors are looking for apps to ensure their safety. In order to guarantee the safety of friends and family going out to protest we looked into existing apps and we came upon the Firechat Offline Messaging App. Firechat uses a peer-to peer mesh network allows users in close proximity (400-500ft) to message each other without cellular data or the Internet. It inspired us to develop an app used in case of disaster situations and mass gatherings. Users may contact nearby individuals for help without cellular data or the Internet. Additionaly they may use voice activated features (code-words) to enable voice activated video or voice recording if they're enduring abuse or violence and cannot physically turn on their phone's camera. Finally, to guarantee that their cellular device is not used against them, a voice activated shut-down feature will also be implemented..
How we built it
Design UI/UX
Code UI/UX in Android Studio
Secure peer to peer mesh network (Offline Messaging) with Bridgefy SDK in Android Studio
Add Android Studio Voice Capabilities to allow for Voice Activated Commands
Utilize OpenCV SDK for facial recognition tech to blur individuals’ faces in photos and video messages in Android Studio
Challenges We Ran Into
Bridgefy is a developer-friendly SDK that can be integrated into Android and iOS apps(including messaging apps) to make them work without the Internet. However, when this SDK was implemented into our app we noticed that many of the methods Bridgefy SDK used have been deprecated.This may be due to the fact that the last update to the repository was 12 months ago. We attempted to replace those methods with newer versions of the methods however some methods no longer had replacements so we were unable to implement the SDK like we wanted to.Additionally, many of us are better equipped in python and web development and know less about app development. We were unable to go into IOS app development and test the IOS Bridgefy SDK because not all members of the team owned a Mac.
Our team faced difficulties in communicating with each other due to time zone differences.With the timezone difference, some of us had to compromise by sacrificing our sleeping schedules.In addition, sometimes the internet connection sucks.However, we did not want time zone differences, sleep deprivation and a bad internet connection to hold us back from participating in this hackathon.
Accomplishments We are Proud of
Utilizing the knowledge we gained from the workshops to create our application
Being able to work together and produce something despite our major time zone differences and limited time.
Being able to bring all of our unique educational backgrounds to produce a product.
Learning that this is a novel idea that others have not created before.
What we learned
We learned how to use Android Studio for the first time, and how to work together with different skill sets. In addition, we learned that many tools like Bridgefy SDK and OPENCV SDK exist that can be used to make our app a reality.
Built With
Bridgefy SDK
- SDK used to set up offline messaging
Android Studio
- Developing App
Figma
- Designing UI/UX
OpenCV-SDK
- Facial Recognition for Face-Blur
Java
- Coding Language
Getting Started/Set Up Guide
In Github click the "Clone or download" button of the project you want to import --> download the ZIP file and unzip it. In Android Studio Go to File -> New Project -> Import Project and select the newly unzipped folder -> press OK
In Android Studio, create an Android Virtual Device (AVD) that the emulator can use to install and run your app.-->In the toolbar, select the AVD that you want to run your app on from the target device drop-down menu.Click Run. OR Use Android Device. On the device, open the Settings app, select Developer options, and then enable USB debugging.
Authors
Mualla Argin
-
App Development: Back: Full Stack Development | College sophomore in Computer Science
-
margin25
Victoria Nguyen
-
UI/UX Design | 42 Silicon Valley Biology/Computer Science
-
VictoriaNguyenMD
Agnes Sharan
-
App Development: Back End Development| Student in CS
-
agnes-sharan
Layan Ibrahim
-
Video and PPT | Junior at Emory majoring in Neuroscience and Behavioral Biology
-
layibr
What's Next for Offline Movement
In the future, we are hoping to fully implement the voice recognition tool so that it only recognizes registered users voices so others cannot misuse the app. Additionally, we are looking to make the program run so that it gives user advice according to the contents of their audio or voice recordings. We also hope to better implement our idea with a full understanding of Bridgefy SDK and OpenCV SDK.
Built With
android-studio
bridgefy-sdk
figma
java
opencv-sdk
Try it out
github.com | Offline Movement | Stay Safe And Let Your Voice Be Heard! | ['Layan Ibrahim', 'Mualla Argin', 'Agnes Sharan', 'Victoria Nguyen', 'Victoria Nguyen'] | ['Grand Prize'] | ['android-studio', 'bridgefy-sdk', 'figma', 'java', 'opencv-sdk'] | 47 |
10,501 | https://devpost.com/software/activity-pathway-m6a3tc | Home page of the app
Fitness tab
Grocery Shopping Tab
Traveling Tab
Schedule Tab
Cooking Tab
Me traveling to Hawaii's Green sand beach
Me traveling to France's Eiffel Tower
Inspiration
My friend had a hard time staying fit and eating healthy during the past few months. My friends parents travel every time my friend had a break in school. Due to COVID-19, they can't travel or visit any places. My friends parents also have a hard time trying to find a store that allows you to buy groceries and delivers in at their house. This is what inspired me to make this app.
What it does
Activity Pathway is an app that several activities that it can help you with such as helping you staying fit daily, eating a healthy appetite daily, help you remember all the activities you need to do, help you travel across the globe, help you buy your groceries, and help you track your order after buying groceries from the app.
How I built it
I used html and css to code the app, but also used my ideas and an online app maker to create my app.
Challenges I ran into
The challenges I ran through was trying to create a camera feature, where when you use Activity Pathway to travel virtually, you can take a picture of the places you went to keep in a gallery of photos. I realized that there wasn't much time to code this feature and that it was too complicated, so I left it for something to add to my app in the future.
Accomplishments that I'm proud of
I'm proud of the grocery option thats in Activity Pathway and the traveling option. I feel proud because mainly love to buy groceries and travel to different parts of the globe. Due to coronavirus, people have to stay home and even going to a grocery store has gotten dangerous. I feel proud of my app since it helps people go to places that they always dreamed of going while they are at home due to coronavirus. The grocery option helps people buy their groceries in order for them to stay safe and not go outside during the environment.
What I learned
I mainly had forgotten most of how to code in html and css, but after this hackathon, my skills in html and css have grown far beyond what they were before the hackathon started.
What's next for Activity Pathway
What next for Activity Pathway is adding the camera feature so that people can take photos and save them in my app. What also is next is that people can insert a photo of themselves or of their family and my app would identify all the people in the photo inserted and my app would add the photo of the people from the inserted photo so that it looks like the photos you take while traveling were actually taken and that your entire family traveled to that place. Another thing that is next for Activity Pathway is that I would like to add a education option where children could learn different subjects. The education option can be for toddlers to high schoolers or even college students that need to refresh some of the skills they learned in the past. Also, if I had more time, I would have made my own live fitness and cooking videos.
Built With
ar/vr
css3
html5 | Activity Pathway | Activity Pathway is an app that can help you do several different activities to stay active while at home. | ['Tanvi Waghela'] | [] | ['ar/vr', 'css3', 'html5'] | 48 |
10,501 | https://devpost.com/software/medicine-screener | Inspiration-In the 1900's everyone used to go to Doctors for everything from a common cold to a fever. This program helps patients find what medicine they need so they don't need to go to the doctor unless they need to.
What it does- How the program works is that it asks you for your symptoms. If you have cough and pain then you press numbers to convey it. Then it will tell you which medicines you need to buy and where to get them. In the next 5 days, it will ask you if you are vomiting or if you feel better. If you don't feel better for 5 days then it will give you the phone number to call the doctor.
How I built it- I built it by building small parts of the program at a time then combine it. I checked if it works and if it is wrong I break it into smaller parts to find the bug. When I built it into two big pieces I combined it and fine-tuned it so it would work perfectly together.
Challenges I ran into- I ran into a major problem of variables. I needed to use them in two different places but I couldn't since It was a local variable. To solve this I got rid of some of my loops and rearranged so it would need separate variables. This way it did not matter it was a local variable.
Accomplishments that I'm proud of- I am proud of finishing this project since this my first project that I did by myself.
What I learned- I learned that you also need to expect the unexpected and that you need to change the entire structure of your program to include all parts.
Built With
python
Try it out
github.com | Medicine screener | To Help Patients cure themselves. | ['Arya Kunisetty'] | [] | ['python'] | 49 |
10,501 | https://devpost.com/software/weatherornot-4prsow | The homepage for our web app
A sample prediction, showing both algorithm and AI model confidence
A summary of our project structure
Profile Page
Inspiration
It’s been known for years that impoverished neighborhoods experience much higher rates of chronic diseases, such asthma, diabetes, and more. Some of these conditions are adversely affected by climate patterns, like Air Quality Index and temperature. We decided to make a tool to assist these communities in this regard.
What it does
Our web app provides a user friendly portfolio page, after they register and log in. The user then provides their location and health conditions, which will be stored into a database along with other information. They will then have access to up to date risk analysis, through email updates or directly on our app, based on their health conditions and climate data, with 3 different levels of warning. Finally, the user can provide feedback on whether the recommendation was correct, improving our systems performance.
How I built it
Our app was built through the Django framework, which maintains the security of our product. We integrated a SQL database to keep track of patient information, including health conditions, over time. We also added an email server for more convenience. We use the Meteomatics and Weatherbit API’s to access climate data. Using all this data, our app runs a non-heuristic algorithm and a machine learning model (made from tensorflow and keras) to predict risk. The model can be improved through feedback from the user. Finally, we host our app on an Apache server.
Accomplishments that I'm proud of
We are proud of integrating our SQL database, which makes access to location and health data more efficient. We are also proud of our model’s ability to improve over time from user feedback. A model is only as good as the data it is given. Therefore, the ability to continuously retrain on new data drastically increases the potential for our model.
What I learned
We researched the effects of weather on numerous chronic diseases in order to create an algorithm that effectively takes into consideration. We also learned a lot about how to use Django to make and deploy our web app. We had some trouble with file paths when we migrated our app into the server, but we solved this in time.
What's next for WeatherOrNot
We will continuously train our machine learning model until it eventually replaces our algorithm. Currently, we only have about 20 diseases we can analyze; we plan to increase the size of this list. We also plan to use more climate data to better evaluate the risk present at any given day.
Built With
css3
django
html5
javascript
keras
meteomatics
python
sql
tensorflow
Try it out
github.com
weatherornot.tech | WeatherOrNot | WeatherOrNot is a health assistant that analyzes risks based on local climate using a machine learning and algorithmic hybrid system, assessing factors like UV index, pollen concentration, and more. | ['Sachet Patil', 'Pranish Pantha', 'Maanav Singh', 'Mohit Chhaya'] | [] | ['css3', 'django', 'html5', 'javascript', 'keras', 'meteomatics', 'python', 'sql', 'tensorflow'] | 50 |
10,504 | https://devpost.com/software/attendance-for-google-meet | List of students and symbol showing attendance
Edit Class Screen
An automatically generated attendance Google Sheet
Inspiration
In the era of COVID-19, virtual classes have become the norm. For teachers, however, taking attendance in these virtual classes is often a pain. They must keep track of when students join and leave among side conversations and distracting visuals. Many teachers at our school complain about the difficulty of taking virtual attendance, claiming that existing Google Chrome extensions are buggy and unreliable.
What it does
Our Google Chrome extension,
Attendance for Google Meet
, streamlines the entire process of taking attendance in a Google Meet. When a teacher first joins a Meet, they are prompted to choose the class that the Meet is for, such as "Period 1 Math". They can edit the class to customize the list of students, add other classes, or delete them. The extension automatically detects when students join or leave the call and records it in local storage. At any time, teachers may click on the attendance button to view each student's status (present, absent, previously present, or not on list), and export the data to a
beautifully formatted
Google Spreadsheet in their own Google Drive.
How I built it
The extension was built with HTML, CSS, and Javascript. We injected these scripts using DOM manipulation into the Google Meet page to match the Material Design theme. We set up an OAuth2 consent screen to ask the user for permission to create a Google Spreadsheet in their Google Drive using the Google Sheets API.
Challenges I ran into
Using the Google Sheets API was rather difficult due to its complexity; however, we managed to abstract the functionalities with functions to make the process simpler. It was also hard to match the exact style of the Google Meet UI because Google minifies its class names, so parsing the page source was troublesome. The Material Design library documentation was
infuriatingly
unclear and we often could not do what it said we could do, but we overcame these hurdles by making functionality ourselves.
Accomplishments that I'm proud of
We are proud of the appearance of our extension and the appearance of the exported spreadsheet. We are also pleased that we not only managed to piece together a comprehensive UI in two days but also create an almost fully functional chrome extension that seamlessly integrates with such a large video platform.
What I learned
We learned about manipulating the DOM with Javascript. We learned about implementing design libraries, in particular Material Design, into our HTML and CSS. Additionally, we learned basic video editing skills.
What's next for Attendance for Google Meet
We plan to fix any bugs in our extension and later deploy the completed product to the Chrome Web Store to help teachers around the world take attendance.
Built With
css
google-sheets-api
html
javascript
material-design
oauth
Try it out
github.com | Attendance for Google Meet | A Google Chrome extension for teachers to make virtual attendance taking easier than ever. | ['Aditya Balasubramanian', 'Tyler Lin'] | ['Grand Prize Winner', 'Best Web Hack', 'Amazon or Visa Giftcard'] | ['css', 'google-sheets-api', 'html', 'javascript', 'material-design', 'oauth'] | 0 |
10,504 | https://devpost.com/software/trackable | A better way to care and connect.
Inspiration
In a time where healthcare workers are working long hours away from their families and patients are unable to see their loved ones, it is up to us to help everyone feel more cared for. Not only that, many public places are not following COVID-19 protocols, including social distancing, requiring face masks, and offering sanitization supplies or sanitizing regularly, increasing your risk factor by 82%. In many ways, it’s no surprise that the same groups that have faced persistent poverty and histories of discrimination are now also the ones at higher risk of contracting the coronavirus and bearing the brunt of its economic cost. This is where our website, Trackable, comes in.
What it does
Trackable is a website that utilizes crowd-sourced data to inform users about the safety of certain public locations. We also realize that due to COVID-19, many people are facing isolation in their daily lives and are not able to communicate with their families as much, so we are offering a dedicated place where you can send meaningful messages to those who need it. Lastly, we know that many people are very paranoid about their exposures with COVID-19, so we created a free quiz that can calculate how likely you are to get contracted with the virus.
How we built it
We created our website using HTML, CSS, and JavaScript.
Challenges we ran into
We had trouble connecting to the Google API because it was really hard to implement it to the website.
Accomplishments that we're proud of
We are proud that we finished this project during the hackathon duration.
What we learned
We gained a lot of experience in coding and had lots of fun during HackDefy!
What's next for Trackable
We foresee that our platform will be fully functionable and attracting thousands of users within 8 months. In the next month, we plan to continue to develop our platform by improving the front end looks and back end security & functionality. Second, we plan on spending about 2 months to get feedback on our prototype and adjust our product accordingly. Once finished, we can launch the product to the general public. The last and longest step, taking 4 and a half months will be our marketing campaign, in which we will expand our user base. We will do this through two major channels: social media influence and spread of information through word-of-mouth. This is our plan of strategy for Trackable.
Built With
css3
html5
javascript
Try it out
trackablewebsite.nehak04.repl.co | Trackable | A better way to care and connect. | ['Neha Konduru', 'Pranav Konduru'] | ['Best Health Hack'] | ['css3', 'html5', 'javascript'] | 1 |
10,504 | https://devpost.com/software/protestfind-vis9fz | ProtestFind
Built With
css
html
python | ProtestFind | Social Good App | [] | ['Best Activism/Empowerment Hack'] | ['css', 'html', 'python'] | 2 |
10,504 | https://devpost.com/software/reduceyouruse | Inspiration
Our inspiration to make this project mainly stemmed from a desire to inform people about our climate. Many people are not aware of the extent of this issue, and we wanted to create an informative website that was also fun to use.
What it does
This website explains the climate crisis sweeping the world, then has the user take a survey with questions that pertain to their lifestyle. At the end of the survey, the user is given a point value based on how environmentally conscious they are, as well as a list of things they can do to help the environment and lower their carbon footprint.
How we built it
The website's front-end was built using HTML and CSS, with Flask as the back-end. The user's points are stored as a session within the website.
Challenges we ran into
We ran into some challenges making the questions change after they are answered. We eventually resolved to do this by storing a value for the question's number in a session and redirecting the user to the results page when they've answered the last question. We also ran into a lot of HTML/CSS formatting issues, primarily with making all of the buttons aligned.
Accomplishments that we're proud of
We were proud of the design of the website, as we had never designed a website before and we thought it ended up looking pretty good. We were also proud of the survey/results link which redirects you to either the survey or your results depending on whether you had already taken the survey.
What we learned
We learned how to center the contents for the page to fit any window/monitor size automatically. Additionally, we learned how to make a more responsive website for the user by using hover & transitions elements.
Built With
css
flask
html
python
Try it out
reduceyouruse.pythonanywhere.com
github.com | Reduce Your Use | Reduce Your Use - a website which helps you be more environmentally conscious. | ['Cooper Christianson', 'Salam Rahal', 'Erik Liang', '21-krebs'] | ['Best Environmental Hack'] | ['css', 'flask', 'html', 'python'] | 3 |
10,504 | https://devpost.com/software/ideal-incentifying-driver-exposer-and-learning-tool | Inspiration
In 2018, 36,560 people were killed in motor vehicle traffic crashes on US roadways, a 2.4 percent decrease from 37,473 in 2017.
Of the young drivers with known seat belt use who died in motor vehicle crashes in 2017, 47 percent were unrestrained at the time of the crashes.
In 2018, 15 percent of young drivers ages 16 to 20 years old involved in fatal crashes had blood alcohol concentrations (BACs) of .08 g/dL or higher; it is illegal in the US for anyone under age 21 to drink alcohol.
In 2018, 6,283 pedestrians were killed in traffic crashes, a 3.4 percent increase from 2017 and the highest number in 28 years.
In 2018, 857 pedalcyclists were killed in traffic crashes, a 6.3 percent increase and the highest number since 1990.
What it does
We start out at the authentication screen, which has been created with the help of Google Firebase. When we go to register an account, we see this change reflected in the authentication. In the video, I previously had a different testing email and after refreshing we see the new email I had input. Then we are signed in and a new document is created and assigned to the user after the creation of their account.
Now to the main four tabs:
(This is out of order in the video because I did it in a rush)
Complaint/Rewards System
At the home screen we are able to view various sections of the app. One of the main features of the app is being able to submit a complaint, which is then put in pending, until the complaint is verified by local authorities. This allows anyone to be able to use this system to find and expose people in violation of the traffic laws, allowing for safer roads. Additionally, the subconscious effect of this is that people will stop violating these laws knowing they could get a ticket via this app. The complaint is then sent into verifications, where the data is stored in Firestore. Local authorities will be able to access these complaints through Firestore and approve or deny the complaint, which is used for determining whether the user receives points for submitting the complaint. The points can later be used by the user to redeem coupons and other rewards (Still in progress as there may be more sponsorships).Complaints are approved when local law enforcements feel that the complaint had enough details and evidence in order to be able to give a ticket to the person who has been complained about. After being approved, this is reflected in Firestore and it will be reflected in the UI.
Road Analytics
In the road analytics page, we have a maps UI showing our current location. We are able to type in a road which we want to see details regarding. After entering we find useful details such as the danger level of the road, the amount of IDEAL users on the road and the estimated amount of people on the road at the current time. This information allows the user to know whether they should use that road or not with these fine tuned details.
Resources
The last page of this application is the Resources tab where we are able to view the various resources teaching us regarding the various important traffic violations present. This allows to the end-user to learn about the various traffic laws as well as the violations they are complaining about to make sure they are submitting a valid complaint to local authorities.
How I built it
To create the authentication, I used google firebase's authentication api in order to create a backend using Google Firebase. This made it easier than me creating my own backend in a tight time frame. It helped me create custom user assigned data as well.
For the rest of the back end, I also used google firebase's Firestore, a realtime database which allows for end-users to update data in the application (sending forms, ect.) asap. This allowed me to be able to use user custom data for each user with these firebase technologies being able to integrate with each other.
For the tab navigator, I used react-native-navigation's material tab navigator. For the point system, I used Firestore for data modeling and assigning custom data to each user. For the form UI, I used react-native-base in order to create the form elements.
For the point system, I built the backend with google Firestore, as previously stated, to efficiently upload and store data in real time. I created the data model with google Firestone where everything was stored.
I also used expo permissions and their image-picker library in order to get the image and upload it to Firestore.
I hope this makes the world a better place.
Challenges I ran into
I had many issues with Firestore for storing data due to the data modeling. It was quite difficult to have a specific document assigned to one user, which I have learned how to implement properly over this experience.
Accomplishments that I'm proud of
To help have IDEAL Roads
Teach others regarding Traffic Violations
Provide Critical Information regarding roads to end-users
What I learned
I learned how to implement custom user interface with Google Firebase's Firestore
What's next for IDEAL (Incentifying Driver Exposer and Learning Tool)
I hope to create an admin system in the future rather than local authorities accessing Google Firebase directly.
Built With
apis
expo.io
firebase
google-firebase
react-native
react-native-base
react-native-maps
Try it out
github.com | IDEAL (Incentifying Driver Exposer And Learning Tool) RIDER | Helping creating IDEAL and Safe Roads for all of us | ['Om Joshi'] | ['Best Mobile Hack', 'Third Place'] | ['apis', 'expo.io', 'firebase', 'google-firebase', 'react-native', 'react-native-base', 'react-native-maps'] | 4 |
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