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10,368 | https://devpost.com/software/data-day-grind-2020 | Our website!
Also our website!
World Happiness Index Choropleth by Country
Correlation Between GDP, Life Expectancy, and Perceptions of Corruption
Correlation Between GDP and Happiness of Citizens
Correlation Between GDP and Life Expectancy
Correlation Between GDP, Life Expectancy, and Freedom to Make Life Choices
Correlation Between Happiness and Freedom to Make Life Choices
Correlation Between Happiness and Life Expectancy
Inspiration
In light of current events, we decided that what better way is there to cheer up others than showcasing our data analysis and visualization of the World Happiness Index.
What it does
Pursuit of Happiness is a thorough data analysis and visualization of the World Happiness Index dataset, which contains statistics regarding an overall "happiness" score of citizens, as well as factors that affect it, such as GDP, perceptions of corruption, and freedom to make life choices. On the web app to display our findings, there are interactive 2D and 3D plots that show different correlations found in the data.
How We built it
In order to analyze the dataset, we used a jupyter notebook along with various python libraries to dive deeper into the data and find interesting correlations. After finding correlations, we used Plotly and Tableau to generate plots of the various findings. As well, we used SciKit-Learn to generate linear and non-linear regression lines to show trends and predictions in the data.
Challenges we ran into
One challenge we ran into was embedding the plots generated by plotly and tableau into our react web app. Since React has almost no support for embedding html files, we had to tediously convert the files into react components in order to get them to show.
Accomplishments that we're proud of
We are proud that we were able to coordinate and create the web app within the given time frame. Due to the difference in timezones, we were not able to work on our project at the same time. However, in the end we figured out how to coordinate and develop our project together through the use of planning tools.
What We learned
We were able to expand our knowledge of data science over the course of this hackathon. We all learned a bit more on how to effectively analyze large datasets, and visualize them using various tools.
What's next for Data Day Grind 2020
We hope to expand on our project in the future, and use multiple datasets in tandem with the WHI dataset to perform even more detailed analysis and visualizations.
DOMAIN.COM -->
http://pursuitofhappiness.tech/
Built With
plotly
react
scikit-learn
tableau
Try it out
github.com
pursuitofhappiness.tech | Pursuit of Happiness | Analyzing and Visualizing the World Happiness Index Dataset | ['Bill Bai', 'Abhay Baiju', 'Fayaz Azeem'] | [] | ['plotly', 'react', 'scikit-learn', 'tableau'] | 19 |
10,368 | https://devpost.com/software/crowdforecast | Inspiration
Our inspiration for CrowdForecast came from the current situation of the COVID-19 pandemic. As we all know social distancing is much preferred and a key guideline to every individual to avoid any further circumstances. So our major approach from this platform is to aware people of the crowded areas near them earlier.
What it does
So our project is basically a web app that will let the user give an exact amount of people in the specific area. If the area has a limited amount of seats or the vacancies and it is already full by people or if a great amount of crowd is already gathered then it will notify users that avoid going to a certain place.
Examples:
For example, if we consider restaurants, metro trains/stations, buses, etc. where the CCTV footage is available, by processing that data through our website we can give the exact amount of people in the respective area by considering the available vacancies so that the user is pre-aware about the place.
How we built it
Firstly choosing the topic to work on is a bit easy thing as we are facing a lot of crises during this year. Being a techy people in and out we all were thinking about contributing to the social cause technically, and so we came up with the idea to build a web app that can lead us to make sure about the biggest guideline given by the governments of various countries and that is social distancing. So we first decided to monitor the crowded places through the cctv footage availbale and give the exact number of people in the video frame. By doing this we can actually aware people about the vacancies available at the certain place or not. By doing this we can avoid going to crowded places by knowing it earlier that the place is crowded. For this we have used Google Vision Api and integrated it with the web app that we have created using flask
Challenges we ran into
We mainly faced difficulties relating to the handling of API’s and their integration with the software since it was our first time working with it.
Accomplishments that we're proud of
Being new to hackathons, we feel proud that we could come up with this project that could have a great impact on the major problems like the COVID-19. And even though there are many places we have to work upon, but to able to present this within this short period and learning a lot of new things is one of our biggest takeaways!
What we learned
Firstly this entire hackathon was a great learning experience as it helped us improve our coding skills and helped us to experiment with many new things which we were not familiar with earlier. Through our project, we were able to use our technical skills to create a product that promotes social responsibility by giving them pre-knowledge about the harm they can cause to society unknowingly, a social cause that makes this a whole lot special for us. It has also inspired us to implement more of such projects in the future.
What's next for CrowdForecast
There is a lot of scope for improvement in CrowdForecast as it can be built as a full web app and help in maintaining social distancing. It can have a more accurate forecasting and a better GUI.
Built With
domain.com
flask
google-cloud
machine-learning
python
vision-api
webapp
Try it out
github.com | CrowdForecast | avoid crowded places with crowdforecast and stay safe | ['Sanjana Nalawade', 'Himanshu Raut', 'Ashutosh Deshpande'] | [] | ['domain.com', 'flask', 'google-cloud', 'machine-learning', 'python', 'vision-api', 'webapp'] | 20 |
10,368 | https://devpost.com/software/weather-or-not-8tw5ev | Inspiration
There are so many things an image can speak and those eyes who can listen to those are fewer. Many people who have less vision power or have less exposure to weather and climate changes tend to get confused about the weather conditions. This project is made in order to tackle the weather prediction to make people aware of their surrounding weather changes and stay alert about it.
What it does
Weather Or Not is an application which captures the image from user and shows the predicted weather condition shown in the picture.
It has camera feature that fetches the image and classify in real-time
The types of weather taken in to consideration are :
Cloudy
Snowy
Rainy
Sunny
Foggy
We tried bought a custom domain "weatherornot.online" but couldn't add it to our github pages in time.
How we built it
The image dataset was collected through google images scraping using a chrome extension. After the dataset was prepared it was fed in to
Teachable Machine
. This is a wonderful machine learning tool for custom model preparation tasks. For this particular project, weather classification was done. The images are trained for 30 epochs and the output was put up as a webpage using javascript in backend.
Challenges we ran into
The image collection and website formating was the challenges faced.
Also adding the custom domain "weatherornot.online" to our github pages was complex for us since we hadn't had any experience in hosting.
Accomplishments that we're proud of
We are proud that we made our ML project in 24 hrs using cool Google tools.
What are learned
We learnt about Teachable Machine which is very new and we feel it's the best way to make a ML project for hackathon. Thanks to one of the mentor to suggest this to us.
What's next for Weather Or Not?
Next would be deploying the application in android for more portable and usable cases.
Built With
css
html
javascript
machine-learning
teachable-machine
tensorflowjs
Try it out
harshak777.github.io
github.com
docs.google.com | Weather Or Not? | Pictorial weather classifier. The project is aimed to classify the weather conditions based on a picture input. | ['Haripriya Baskaran', 'Harshak krishnaa'] | [] | ['css', 'html', 'javascript', 'machine-learning', 'teachable-machine', 'tensorflowjs'] | 21 |
10,368 | https://devpost.com/software/guess-that-digit | Inspiration
What it does
How I built it
Tensorflow.js
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for Guess That Digit
Built With
html5
javascript
python
tensorflow
tensorflow.js | Guess That Digit | This project recognizes digits that the user will draw on canvas. | [] | [] | ['html5', 'javascript', 'python', 'tensorflow', 'tensorflow.js'] | 22 |
10,368 | https://devpost.com/software/word_cloud_from_hashtag | Result of an #Hola search
Inspiration
During the brainstorming, we were thinking to make something curious and funny that can be obtained with data. We thought about the workshop we did in the same day, about a bot that can simulate a conversation just retrieving tweets from some users. Our initial thought and the workshop we did are our inspirations for this projects.
What it does
From some twitter hashtags, the app returns to the user a word cloud of the most frequent words of the tweets with the given hashtags.
How we built it
Basically, we used Python3, HTML and CSS for the webpage. For the deploy, we used Heroku. For fetching the tweets, we used the Python3 API GetOldTweets3 because we didn't have access to twitter developer tools. For drawing the word cloud we used a Python3 library called wordcloud.
Challenges we ran into
Most of the problems came from Heroku and Flask. This is because it was the first time we used those technologies.
Specifically, we had some problems with saving images in Heroku, which we couldn't solve due to the time. We also had some problems with getting the tweets because none of us had access to twitter developer tools.
Accomplishments that we are proud of
It's the first time we create something at a hackathon, but it only works correctly on local :( .
What we learned
We learned the very basics of web development with Flask and web deploy with Heroku. We also learned how to work in adverse conditions (work at home due the global pandemic).
What's next for Word Cloud From Hashtag
Our next step is solving the problem we have with showing images when the webpage is deployed by heroku. After doing that, we will optimize the webpage, because we are aware that it can take a lot of time to make petitions and retrieve results. We also want to add some features, such as only get tweets from a date or select a language. This last one feature will improve drastically the meaning of the returned word cloud.
Built With
css
flask
html
python
Try it out
github.com
word-cloud-from-hashtag.herokuapp.com | Word Cloud From Hashtag | Search hashtags and check the word cloud of the most used words in tweets that include that hashtag. | ['Xavier Nadal', 'santo0 La Rosa Ramos'] | [] | ['css', 'flask', 'html', 'python'] | 23 |
10,368 | https://devpost.com/software/email-tracker-cibyh2 | Online Form to Send a Trackable Message. Avaliable at: https://emailtracker.deepjain.com/
Extension that creates a button for seamless use.
Return Email.
Inspiration
It was getting frustrating that people were not responding to emails and that there was no way to know if the email was being ignored.
What it does
Tracks emails and notifies the sender when an email has been read by a return email.
How I built it
I built it using PHP and javascript. A secret token is sent as an image with the email that calls the server telling it that the email has been viewed. The server then sends out a return email with the required details such as IP and Time to the from address.
Challenges I ran into
Creating an image token that would not be seen by the recipient of the email. I ended up using a very small blank png image and used CSS to make the size of the image 1px by 1px so it is not seen.
What I learned
I learned more about email servers and email hacks especially email tracing.
What's next for Email Tracker
Public Extension Release for easier and seamless use(as in the pictures).
GitHub:
https://github.com/DeepSJain/Email-tracker
Built With
css
javascript
php
php5
phpmail
phpmailer
Try it out
emailtracker.deepjain.com | Email Tracker | know when your email is readknow when your email is read | ['Deep Jain'] | [] | ['css', 'javascript', 'php', 'php5', 'phpmail', 'phpmailer'] | 24 |
10,368 | https://devpost.com/software/boostme-4q6jst | Boost Me is a data-driven social media booster.
Inspiration
Most people use their intuition when preparing content for their social media. The words and hashtags used are not data-driven and will not take performance into account.
What it does
With Boost Me though, that's all changed.
You will write your tweet with all the hashtags you want to use. Boost Me algorithms will analyze each hashtag, according to the previous posts and will give you a score. Also, Boost Me will give you new Intelligent hashtag pre-optimized suggestions.
Once you're happy with your overall tweet score and the hashtags, you can post the tweet right there, spontaneously.
How I built it
My backend communicates with the Twitter Standard API, searching through every hashtag. It randomly selects 100 recent tweets, associated with the hashtag. Then, it will judge their performance, looking into a variety of parameters. Then it will send the text to Google Cloud Natural Language API, recognizing the most performant hashtags and it will suggest them to you.
Challenges I ran into
I've always participated in hackathons with teams. Having to work under pressure and alone, was a challenge that I had not faced before.
Accomplishments that I'm proud of
Setting an achievable goal, taking into consideration, and constantly adapting to the challenges that occur, is something I think I did well.
What I learned
It was my first time using a social media API for analysis purposes.
What's next for BoostMe
Boost Me can give you a ton of options, analyzing, optimizing, and monitoring your social media account. It can recognize the trends and guide you through them, to help you make the most out of them.
Boost Me is the social media booster app we were waiting for.
Built With
google-cloud-natural-language
node.js
react
twitter-standard-api
Try it out
github.com | BoostMe | Win twitter with Boost Me. | ['Parsa Safavi'] | [] | ['google-cloud-natural-language', 'node.js', 'react', 'twitter-standard-api'] | 25 |
10,368 | https://devpost.com/software/calihomes-info-sjci5b | Find Your Ideal Neighborhood.
Inspiration
People always look for a neighborhood which is nice and affordable. A place where you can live a comfortable life in your near perfect home. So,we came up with this smart and helpful idea that provided people with the exact data they are looking for, to help them find their home, and be accessible to everyone who's looking for a place in California.
What it does
CaliHomes-Info is a webpage that allows an user to interpret data, and find the suitable locality using coordinates, all from a pre-defined open source dataset.
How We built it
We brainstormed ideas and chose this idea because we felt people in and around California would find it most useful. Then we discussed our skill sets and divided our tasks accordingly. GitHub was used to share the files. Throughout the journey of converting this idea into a website, we helped each other out.
Challenges we ran into
The main challenge we faced was coordinating with different skills that we have. Our skill sets are very different (almost different domains of work) and we had difficulty organizing our idea onto a page. We had to stay up late and wake up early to get done with our tasks and run until the final moments of the deadline. Another challenge we faced was getting a domain name. None of us in our team had a credit card, so we weren't able to get our desired domain from domain.com.
Accomplishments that we're proud of
We established a webpage in less than 12 hours and learned a lot on the aspects of our skills that we need to work on for better collaboration in the upcoming hackathons.
What's next for CaliHomes-Info
Currently our website is still static. We plan to add databases and user information to make it fully functional. We also plan to add a Machine Learning model that accurately predicts the median price of each house according to the requirements of the user. Afterwards, we want to open it to the public and get worldwide.
Built With
css
html5
javascript
jupyternotebook
python
Try it out
calihome-info.netlify.app
github.com | CaliHomes-Info | Our Idea is to provide visualized data information to a user for finding the Ideal locality for his dream home. | ['Sanket Puhan'] | [] | ['css', 'html5', 'javascript', 'jupyternotebook', 'python'] | 26 |
10,368 | https://devpost.com/software/stone-paper-scissor-n6vc9h | Inspiration
What it does It generates random output to declare the winner
How we built it - By using algorithms and math function of javascript with DOM manipulation and combination oh HTML and CSS
Challenges we ran into - to generate the random out come and displaying it.
Accomplishments that we're proud of it shows good results with good time pass and a reset button.
What we learned DOM manipulation and HTML and CSS
What's next for Stone Paper Scissor
Built With
css3
html5
javascript
Try it out
soulhunter10737.github.io | Stone Paper Scissor | This is a short simple game of Stone Paper Scissors | ['Shibam Dhar', 'Loveneesh Dhir'] | [] | ['css3', 'html5', 'javascript'] | 27 |
10,368 | https://devpost.com/software/u-s-census-poverty-project | app example
cleaned data
original data
ap example
Pitkin County, CO
Inspiration
With the 2020 U.S census looming over the horizon, I thought it would be appropriate to give the past data kiss goodbye. On a serious note, I just thought it would be interesting to see what patterns exist between poverty, social services, and other factors.
What it does
Ideally U.S Census Poverty Analysis will display data about poverty for the County selected. The application may use some kind of machine learning or linear regression to predict future poverty data. The app will also find outliers where the rates of poverty vary greatly over time. I hope that policymakers can learn from outliers to make better decisions to end suffering.
How I built it
We got data from the Census website, and cleaned it. Then we used streamlit to present the data as line charts for counties or states selected by the user.
Challenges I ran into
It was our team's first time using streamlit, and we had some difficulty using it. I had trouble with the datasets, as some functions to delete columns would not work. We didn't get far enough to implement linear regression and machine learning.
Accomplishments that I'm proud of
Before this project, I knew some of the syntax of the python, but not much more. I wrote my first python scripts for this project, and started to learn tools I've never used before.
What I learned
streamlit, matplotlib, teamwork, python shell. I honestly learned a lot.
What's next for U.S Census Poverty Project
We need to improve performance for retrieving the data, before we can go a lot further. Moreover, I am interested in learning a tool called "CSPro". Once we/I get more familiar with how to query census data, we could maybe apply machine learning or linear regression to make predictions about poverty.
Built With
matplotlib
numpy
pandas
python
streamlit
Try it out
github.com | U.S Census Poverty Project | Are you a U.S public official? Do you want to improve your consituent's standards of living? Quickly spot trends between poverty and social services across counties in the U.S. | ['justinbroce Broce', 'Pranav Aggarwal', 'William Xu', 'Judy Yeonghyeon Ham'] | [] | ['matplotlib', 'numpy', 'pandas', 'python', 'streamlit'] | 28 |
10,368 | https://devpost.com/software/covid-19-help-space | Inspiration
During this time, we realized that even though there are so many resources online, the millions of options to choose from for useful information can get overwhelming super quickly. That's when we realized we wanted to make life, which is already very challenging for most people, a lot simpler by providing them with a central tool that will lead them to useful and reliable resources quickly and easily. We thought that this was especially important to have for people searching for help within self-care, food, news, jobs, and education
What it does
Our website allows people to find useful resources quickly and go straight to doing what they need to do without the stress of looking through all the options that pop up after one Google search. We have included five sections of information: Self-Care, Get Food, News, Job Support, and Education. Each page features a list of sources that are visible as icons until the user hovers over them to find more information about the resource. The user then has the option to click on the resource and get directed right to the site. In addition to the resource lists, we included a data visualization of confirmed COVID-19 cases by county (data from USA Facts) in the 'News' section and a spreadsheet of job listings in the 'Job Support' section.
How we built it
We built our website using HTML, CSS, and Javascript. We used Glitch to run our code. For the data visualization, we gathered the data from USAFacts and used Domo to make the visualization of confirmed COVID-19 cases in the United States by county. For the spreadsheet of job listings, we used UIPath Studio X's Data Extraction tool and created an automated tool that collected the title, description, and URL of the listing of job websites, so that we could create a spreadsheet that had job listings from different pages/websites all on one page.
Challenges we ran into
We ran into some challenged with the CSS format, but we were able to overcome them by referring to online resources and playing around with our code to see which parts were conflicting with others. Another challenge was that UI Path only saves to an Excel sheet and we do not have Excel, but we were able to remedy that by copy and pasting the preview of the data extraction onto an AirTable, which in the end made it easy to embed the data into our website.
Accomplishments that we're proud of
We are proud of the fact that we made a website with multiple pages and ways that the user can interact with, not just a static webpage. We were really happy with how the layout turned out. To be honest, we were a little bit intimidated by the thought of using UI Path and automation, but we were able to actually use the product! Something else that intimidated us was the thought of creating a data visualization because they look so complex, but we were really happy with our data visualization of confirmed COVID-19 cases by county.
What we learned
We learned a lot more about using CSS to style web pages. We also learned how to use UI Path to automate data extraction from web pages. This was a super cool experience because initially, we did not know that UI Path could do something like that, and we were going to manually compile everything onto a spreadsheet. We saved so much time and we would definitely use UIPath again for that purpose. We also want to explore what other ways we can utilize automation to save us time. Lastly, we learned how to create data visualizations. It was amazing as well since the data from USAFacts is a massive repository and we were able to make a detailed and informative visualization of the whole country!
What's next for COVID-19 Help Space
We think that making everyone's life easier is always a plus, especially during this time, so we would love to keep adding more resources for everyone to use, as well as use our code to publish a real website. Also pivoting the site to host an online community where people could support each other during these challenges times would be something we are very interested in.
Built With
css
domo
glitch
html
javascript
uipath
Try it out
covid-19-help-space.glitch.me | COVID-19 Help Space | A easy to use platform with resources to help navigate life during the COVID-19 pandemic. | ['Genevieve Chin', 'Roselyn Chin'] | [] | ['css', 'domo', 'glitch', 'html', 'javascript', 'uipath'] | 29 |
10,368 | https://devpost.com/software/ez-eats | EZ eats app UI
EZ eats logo
EZ eats website
GitHub, Framer, and Presentation Link down below!!
Inspiration
We were inspired to create EZ eats after seeing and researching how much food is wasted in the world. Especially with our current situation, restaurants are wasting more and more unused food and losing money at the same time. This accounts for about ⅓ of the world’s food production which is wasted and goes to show how much can be done if we knew how to distribute it properly since it is still perfectly good food, it just hasn't been sold.
This not only contributes to growing food wastage numbers but also takes away from the economy which is already tremendously suffering. Restaurants are losing tremendous amounts of money as not as many customers are going to restaurants these days.
The major food wastage problem and the economy sailing into a colossal storm, due to the pandemic, inspired us to create EZ eats!
What it does
EZ eats connects users to restaurants in their area which have perfectly good unused food after hours that they would normally have to throw out. Users can order food from their favorite restaurants based on availability through our app and pick it up accordingly. The app will connect users with restaurants of their preferred cuisines and they can see which restaurants have leftover food daily, allowing them to purchase whatever they want while being at a cheaper price than the normal selling price. Since the food is being sold after hours, the price is reduced anywhere from 30-70 percent so the restaurants are still making money instead of losing it by throwing the food away, and users can buy good food at a cheaper price. This helps the problem of food waste and the economy at the same time.
How we built it
We made a website using HTML for EZ eats. We began by writing a simple code asking the user to input their contact information in order to receive updates about the steps that EZ eats will take moving forward. We also inserted logos and social media links where people can find out more about the app when it goes up and running. The website will update with new developments for EZ eats and will periodically send information to users who have signed up with their emails. In the future, this website will allow for more people to learn about EZ eats and its purpose; we are aiming to bring awareness to food wastage and how we can act upon it with the creation of this app.
We also created a functioning prototype on Framer which showcases the UI for the EZ eats app. We made all the screens for the app’s UI and then proceeded to link the buttons to their respective pages, allowing for a perfectly working prototype which can then be used as a model for the real app when created.
Challenges we ran into
Some challenges we ran into were agreeing on an idea as well as what we were going to do in order to execute it. We first started off by brainstorming ideas and then coming together in order to decide, which did take a considerable amount of back and forth. We then took some time to decide how we were going to turn the idea into a reality. These challenges overall helped us create a solid plan as to what we were going to do and how we were going to go about doing it, allowing for us to have a very smooth experience when actually working on a bulk of the project.
Other problems we faced were coding the website through HTML. We are both beginner level HTML coders, so a majority of our time was focussed on developing the website. We learned a lot along the process, ultimately, the long process was worth it.
Accomplishments that we're proud of
We are proud that we were able to create a website and a working prototype in the allotted time and that we were able to work together so seamlessly in order to create the best product we could. The website shows that the app is currently in progress and allows any interested people to sign up whenever they want to receive updates. This prototype allows us to see a true vision of what this app will be as well as its functionality.
What we learned
We learned how to make an idea into reality in a short amount of time by making a functioning prototype and website. We also learned the nuances of creating a website like the code and purchasing the domain so the idea could truly be ours. We also became more able to manage our time very efficiently and make an idea into reality. Let’s modernize our world and eat for less!
What's next for EZ eats
We hope that people truly see the vision of EZ eats and how it is aiming not only to help the environment but the economy as well. We plan to continue by doing some more in-depth market analysis and advertising it online and in-person in order to stir up interest. The more people who know about this problem and use this app to make a step forward, the more that we can curb the problem of food wastage and the effects this is taking on restaurants and the economy. This app is all about making a difference and this could be the first step to making it happen. Let’s modernize our world and eat for less!
Built With
framer
html
Try it out
github.com
framer.com
docs.google.com | EZ eats | Let's modernize our world and eat for less. | ['Mihika Bhatnagar', 'Annika Desai'] | [] | ['framer', 'html'] | 30 |
10,368 | https://devpost.com/software/todolist-skiyjr | todolist
This is a Todo-list project
Which has HTML , CSS and JavaScript, with DOM manipulation.
It has some animations and transformations with some additive features like, deleting it and marking it as complete.
We can also view the completed one separately , the uncompleted one separately and all of them all together by choosing the options.
Built With
css
html
javascript
Try it out
github.com | ToDo-List | This is a Todo-list project , which will collect your list and and modify them. | ['Shibam Dhar'] | [] | ['css', 'html', 'javascript'] | 31 |
10,368 | https://devpost.com/software/behavioral-cloning-for-self-driving-car | various classes of the image data
distribution plot for image dataset
image preprocessing techniques used
My model
the image is predicted belonging to the exact class speed limit 30km/h
Inspiration
The inspiration behind this project was to work with image data, to find the distribution of the dataset, and to learn the various techniques used for image preprocessing and training a custom convolutional neural network.
What it does
Trained a Deep Learning Model that can identify between 43 different German Traffic Signs using LeNet architecture.
How I built it
The dataset is available at
Bitbucket
. The dataset is sclassified into 43 different classes:
Speed limit (20km/h)
Wild animals crossing
Turn Left Ahead
End of no passing by vehicles over 3.5 metric tons
among many other classes.
These are the libraries I have used for this project:
1.numpy
matplotlib
OpenCV
tensorflow
Keras
Pickle
Random
Pandas
Requests
Pillow
The model is based on the LeNet architecture. LeNet is small and easy to understand — yet large enough to provide interesting results and an excellent first architecture for image data and convolutional neural networks. My plot for accuracy vs epoch is
Challenges I ran into
Splitting out Features and labels.
Preprocessing the images- Grayscale conversion, equalisation and image normalisation, splitting the image dataset and fitting it in the imageGenerator.
working on the model architecture, activation functions, and training the dataset for specified number of epochs
Accomplishments that I'm proud of
I've understood various image processing algorithms, model architecture and that I was able to predict the image oytcomes with an accuracy close to 98%
What I learned
I have learnt ways to work and classify image data, the various CNN architectures and the choice of various hyperparameters for tuning the model
here is the code
collab
What's next for Behavioral Cloning for Self Driving Car
This data project was a small part of the self driving car project that I simulated in a simulator. This trained model can be further processed and trained on a self driving car model so that it can be simulated by obeying various traffic rules like speed limit etc.
Built With
collab
google
keras
python
tensorflow
Try it out
github.com | Self Driving Car-Traffic Signs Classifier | Classifying traffic symbols into their respective classes. Image Dataset taken from German Traffic signs. It is part of the self driving car project i simulated in a simulator. check the video below. | ['Elio Jordan Lopes'] | [] | ['collab', 'google', 'keras', 'python', 'tensorflow'] | 32 |
10,368 | https://devpost.com/software/cognito-bnup5t | Note
We had the individual AI and Keylogger working, we were unfortunatley unable to combine them and thus there was no demo. To watch the individual demos for the AI and Keylogger you can go down to demo videos.
Inspiration
Every year thousands of people are diagnosed with Parkinson's. Many times its too late and their relatives are forced to watch as they become shells of the humans that they once were. The worst part is that Parkinson's is often difficult to detect and can be tricky to diagnose.
We wanted to create something that could help detect Parkinsons in a quick and efficent way, without being obtrusive or expensive.
Thus we present Cognito
What it does
Cognito is very simple
Cognito has a key logger which tracks specific typing metrics. Cognito stores these metrics which are then analyzed by an advanced AI algorithim which detects for signs of Parkinson's. If Cognito detects signs of the disease it will send an email alerting the user about the issue.
Cognito is a simple background script that doesn't need an internet connection and is simple and hassle free.
Cognito has plenty of potential as typing can not only be used for Parkinsons, but for many other dieases as well such as Huntington's and Alzheimer's Disease.
How we built it
We used the neuroQWERTY dataset and keras to develop an algorithm which detects whether or not a user has Parkinson's.
We then used python to develop a simple keylogger that tracks the metrics which the Algorithm will need to analyze.
Challenges we ran into
Developing the Algorithm was incredibly difficult. It took a lot of time and was difficult to debug. It was the group's first time working with numerical classification in AI.
Accomplishments that we're proud of
We are proud that we got the AI algorithm to work. It took a lot of time and effort, but it payed off!
We were also proud that we could detect such a deadly disease with such a simple metric... typing!
What we learned
We learned how AI works and how to use it and learned how to do key detection with python. For two thirds of the group it was their first time working with any sort of AI at all so this was a new and fun journey for all!
What's next for Cognito
We would like to develop our algorithm even further. Unfortunatley, Cognito has a 50% accuracy, however with the discovery of some new datasets and with the ability to spend more time with the Algorithim we feel confident that we could get the prediction to over 70%.
We then plan to release this so that we can start helping people all around the world!
Demo Videos:
Keylogger:
https://www.youtube.com/watch?v=iiWSOhdJlaA
AI:
https://www.youtube.com/watch?v=YuE35_pRSeE
Discords
CantTouchThis#8155
theaditya24#8701
anishfish#5103
Citation
Arroyo-Gallego, Teresa et al. “Detecting Motor Impairment in Early Parkinson's Disease via Natural Typing Interaction With Keyboards: Validation of the neuroQWERTY Approach in an Uncontrolled At-Home Setting.” Journal of medical Internet research vol. 20,3 e89. 26 Mar. 2018, doi:10.2196/jmir.9462
We used a few studies for inspiration and we used the neuroQWERTY dataset. The keylogger and the algorithm were our own however.
Built With
keras
keystrokes
machine-learning
python
smtplib
tensorflow
Try it out
github.com | Cognito | Detect Parkinsons with the power of typing and AI | ['Anish Karthik', 'Gaurish Lakhanpal', 'Aditya Tiwari'] | ['2nd Place', 'MacroTech Sponsored Prize', '2nd Place'] | ['keras', 'keystrokes', 'machine-learning', 'python', 'smtplib', 'tensorflow'] | 33 |
10,368 | https://devpost.com/software/test-together-yjzsuf | Inspiration
After Covid-19 lockdown restrictions have loosened up in some states in the US, I realized how more people might need knowledge of where testing sites were
What it does
How I built it
I used Figma to design the UI and exported it over to Android Studio XML files. Then I tried to figure out a COVID-19 Testing Center API and implemented it into my app.
Challenges I ran into
This was my first time focusing on UI and working with Figma and also the first app I've made in Android in about a few years, so it was a bit difficult to relearn the interface and the code.
Accomplishments that I'm proud of
I'm very proud that I was able to learn a new way to design applications and also for making a semi-functional android app. I also typically make web applications with APIs, so this was a fun new challenge.
What I learned
I learned how to work with Figma and also learned how to implement an API in Android and making JSON calls in the Android Java language.
What's next for Test Together
Implementing Google Firebase Authentication and allowing users to save certain test centers. Also working on creating a map for users to visualize the location in relation to themselves.
Built With
android-studio
api
figma
json
Try it out
github.com | Test Together | An android app seeking to inform the public about COVID-19 testing sites in their state | ['Fay Lin'] | [] | ['android-studio', 'api', 'figma', 'json'] | 34 |
10,368 | https://devpost.com/software/covidaccountable | Inspiration
According to
Fortune
magazine, most Paycheck Protection Program loan recipients remain unnamed. As the global economy enters into a recession, we must restore democratic oversight over how this stimulus money is used. Thanks to the work at
Accountable.US
as they have pored over SEC filings to elucidate where American taxpayers' have gone, we have created a Chrome Extension that will help people around the world judge whether companies that received PPP bailouts really deserve their patronage.
What it does
CovidAccountable
looks through a webpage and searches for company names that match that received
PPP funding
. Company names that have a hit in this database get highlighted where the user can learn about how much the company has reaped from the PPP.
How we built it
COVIDAccountable runs on Google Chrome. We wrote a custom script that uses regex to read through a webpage DOM and identify the names of corporations that received COVID-19 funding. The tooltip that occurs over the word when generated uses the tipped tooltip library (
https://www.tippedjs.com
). Corporation data is sourced from Accountable.us data on Trump bailout (
https://www.trumpbailouts.org/small-businesses/?fbclid=IwAR3wjOLPg8FgoDRcoDY9sB5_S4l1RM-yb-WqoGWPnb-oZGf6JzAGszfQ744
)
Challenges we ran into
Finding PPP lender Information
We thank
Accountable.US
for their work in amassing this research together as without it, this project would not have been possible. However, even finding this information was difficult. As such, the importance of this project is of even more importance as we must hold our government accountable to ensuring fair access to PPP funds.
UI/UX Design
Computer Science curricula are much more focused on theory than on the latest of user interface. Consequently, it took quite some experimentation and research to get a good library working. Hans had prior experience with the
Tooltipster
library, but we eventually went for the
Tipped
library instead.
Accomplishments that we're proud of
As we approach an election year, it is extremely important that we understand how our government has managed the COVID-19 pandemic, both in epidemiological management and in economic support for the general population. As this government has obscured efforts to understand how PPP money has been used, we're proud of our steps to unveil this thus-opaque process.
What we learned
Chrome Extension development
UI with the Tipped library
What's next for CovidAccountable
We hope to train name-entity recognition models that will be able to distinguish company names from other names, e.g. suppose a company were called Ananas, we would want to pick up the company name Ananas, but not pineapples on Wikipedia.
Built With
chrome
javascript
jquery
tooltip
Try it out
github.com | CovidAccountable | Chrome extension that identifies businesses that benefited from the 2020 Paycheck Protection Program. COVID mitigation incompetency is no excuse for lack of economic accountability! | ['Allen Mao', 'Hans Gundlach'] | ['Overall Best'] | ['chrome', 'javascript', 'jquery', 'tooltip'] | 35 |
10,368 | https://devpost.com/software/bed-tracker | Main page
Hospital registration
Flow chart
Created a customised web application using Maps to track the nearby hospitals around us which is connected to the hospital's database or data entered manually which will give information about the availability of beds and facilities in that particular hospital.
Built With
bootstrap
css
google
html
map
mysql
php
Try it out
github.com | Bed tracker | Know nearby available hospitals in one click and sort using many filters. | ['ritikgarg655 Garg'] | [] | ['bootstrap', 'css', 'google', 'html', 'map', 'mysql', 'php'] | 36 |
10,368 | https://devpost.com/software/a-vscode-extension-python-code-autocomplete-sort-of | Inspiration
This was really inspired by me when I try to learn how to code. There are just so many things I need to remember, I really wish to have a personalized code autocomplete so I can skip the redundancy in coding. Thus my extension was created.
What it does
Basically, it able to create an autocomplete snippet in the Visual Studio Code. And it read line by line, and it will recommend based on your input. It is personalized since I used the GitHub API. What I really want to work is being able to customize it, but it turns out that it's a little bit hard to customize it. So I just hard-coded the repository link. But surprisingly, I actually able to get the user's input for their username and their corresponding repositories.
How I built it
I built it using TypeScript as a VSCode Extension. And GitHub API is also a key component for this VSCode Extension. And Appreciate all mentors who helped me to built this extension!
Challenges I ran into
I ran into a lot of challenges, the biggest challenge is to get used to TypeError using TypeScript. I really not used to typed language. Another problem is difficulty of the documentation, it should really be able to make it even more clear. Although the code samples do help tremendously! Specifically, how to load code so the autocomplete actually works. Also, how to get GitHub API works using
request
module, etc.
Accomplishments that I'm proud of
I'm proud of to create my first TypeScript application and VSCode extension! And I learned how to use
request
module in TypeScript, I also made the partial extension works, so basically it's able to autocomplete code from my repository.
What I learned
I learned some basic of typed language in general, and TypeScript more specifically. I also learned how to communicate with different mentors, and I learned how to create a VSCode Extension!
What's next for A VSCode Extension | Python Code Autocomplete (sort of)
Use machine learning to make suggestion better
Fix the GitHub Repo, so I don't have to hardcode my repo anymore
Deploy to marketplace.
Built With
github-api
typescript
visual-studio-code
Try it out
github.com | A VSCode Extension | Python Code Autocomplete (sort of) | A Python Code Autocomplete VSCode Extension (sort of) | ['boyuan12 Liu'] | [] | ['github-api', 'typescript', 'visual-studio-code'] | 37 |
10,368 | https://devpost.com/software/plant-pod | home page!
our story!
about us
Inspiration
We wanted to create a fun hack that would enable us to learn how to create a web application and how to use APIs. Since both of our project leads have a passion for music and botany respectively, we decided to create an application that would cater to both interests.
What it does
The web application tells you what your plant personality is based on your favorite Beatles song. Discover new favorite flowers while you jam out to the Beatles on repeat. Start by selecting your favorite Beatles song from the drop-down, hit start, and start reading about your new plant personality. Take a photo of the plant displayed and share it on Instagram!
How we built it
The app is coded with Flask and deployed with Heroku. We used the Spotify API (ran out of time to finalize our use of the Trefle API) in our app to retrieve the desired plant and music information.
Challenges we ran into
After we got the Trefle API working, we realized that the dataset wasn't complete. As a result, many of our get requests would return "null" on the display page. We fixed this by limiting ourselves to using plants with a complete dataset.
The biggest challenge we ran into was with Heroku. We spent several hours trying to get our web application hosted on Heroku, but we kept running into file structure errors. In the future, we would spend more time getting the application working on our local machine and less time on hosting.
You'll notice from our GitHub that our dev branch isn't merged with master. We did not have enough time to merge the dev branch that contained the python and Spotify API code with the master branch that had all of our Flask and HTML/CSS code.
Accomplishments that we're proud of
Most of the members of our team were beginner coders, so the team leads were excited to have shown them a more advanced side of coding. Every single member on our team learned something new this weekend, from GitHub basics to back-end basics. Our project idea evolved a lot over the course of the weekend due to our limited technical skills. I'm proud of our team for never giving up despite the hurdles we ran into.
What we learned
Oh man, what didn't we learn this weekend? Our beginners learned: how to use GitHub, Terminal, HTML/CSS Basics, and Flask Basics. They also learned about what an API is and how to structure a web application. Our team leads learned how to use Flask and API's as well as how not to deploy on Heroku. We got stuck a few times, but thankfully we had a lot of mentors to help us get back on track! We are grateful to have met new, amazing friends, and we hope to collaborate more in the future!
What's next for Plant Pod
We all would love to learn more about how API's work and how to successfully host on Heroku, so we can better integrate their usage into future projects. We hope to merge the code on our two Github repositories into one web app. We plan on continuing the project in the future and using it as a tool for learning new technical skills.
Built With
api
css
flask
heroku
html
trefle.io
Try it out
github.com
github.com | Plant Pod | Discover Your Plant Personality Based on Your Favorite Beatles Song | ['Kelly Ly', 'Lavanya Sharma', 'Anum Ahmad', 'aswika Manivannan'] | [] | ['api', 'css', 'flask', 'heroku', 'html', 'trefle.io'] | 38 |
10,368 | https://devpost.com/software/datax-5y78dn | Splash Screen
Home Page Mock Up
Visualization #1
Visualization #2
Visualization #3
Visualization #4
Inspiration
With the world migrating into a more technology-oriented era, the amount of data we use has naturally grown exponentially as well. With additional data, the need to interpret, analyze, and manipulate the data is as prevalent.
The idea originally came as one of our teammates had previously used a visualization software called Gephi. However, in his time using it, the software was limited to a 2D scope and had to use characteristics like size and color to represent other dimensions making it harder to interpret. Additionally, with many data points, the plot soon seemed to look cluttered making it hard to interpret. To make this visualization and interpretation easier, we created DataX.
What it does
Cutting to the chase, our application does 3 things:
Takes your
CSV file and converts it to an interpretable format
in JavaScript.
Uses Three.js to
create a multi-dimensional representation
via the interpretable format previously created.
Implements dat.GUI for
customizable manipulation on the data set
such as restrictions and styling.
How we built it
We divided the work into 3 phases:
Initially, we split into two teams: one that focused on developing the home page of the website and the other that
Familiarized themselves with three.js.
Development of the visualization screen.
Integration between the screens.
Challenges we ran into
Conversion from the CSV to a readable format like lists and JSON objects.
Originally, we were planning on using Vue + three.js, however, we later decided against it because while the Vue + three.js library was well done, it was not complete and it lacked enough functionality that we would have had to spend a lot of time implementing it ourselves.
Finding data that worked well visualized in multiple higher dimensions was difficult as well.
Accomplishments that we're proud of
We are proud of implementing a working product in the time frame. In only 24 hours we created a tool that is
functional, sleek, and has application
. Also, we are proud of the way we implemented a topic that was completely unfamiliar to all of us in such a short time.
What we learned
Adam
- I learned how to use three.js for 3D rendering and dat.GUI for customized controls.
David
- I learned very basic spreadsheet manipulation in LibreOffice Calc and I learned how the CSV format works. I learned how to use the CSV package in python.
Keshav
- As a part of this project, I used JavaScript in a web application for the first time. Additionally, I learned how to implement libraries and tools such as Three.js, Papa Parse 5, and yarn.
Ben
- I learned HTML and CSS further and implemented them to make a responsive web design. Traditionally, I have never incorporated JavaScript into web pages, but this time I did. Second, I learned how to incorporate the designs and logos I made into the workflow.
What's next for DataX
We would like to add in even more functionality in the form of display data restrictions, better visual scaling, and better customizable scaling for the data itself (logarithmic scaling, clamping, linear scaling, etc.).
Additional Information
There are additional images of sample visualizations in the slideshow above.
Built With
css
dat.gui
html
javascript
papa-parse
three.js
web-workers(papa-parse)
yarn
Try it out
agoldstein03.github.io
github.com | DataX | An innovative, adaptive, and novel tool that allows for easily customizable multi-dimensional data representation | ['Keshav Ganapathy', 'David Aylaian', 'Adam Goldstein', 'Benjamin DiMarco'] | [] | ['css', 'dat.gui', 'html', 'javascript', 'papa-parse', 'three.js', 'web-workers(papa-parse)', 'yarn'] | 39 |
10,368 | https://devpost.com/software/my-first-android-app | My first android app has a text field and a button. You insert what you want into the text field, and hit the button, and the next screen/activity will output what you put into the text field.
Built With
android-studio
java | My First Android App | My first android app | ['Arcy Cruz'] | [] | ['android-studio', 'java'] | 40 |
10,368 | https://devpost.com/software/mapit-06gcwi | Home page with interactive map.
User submission page.
Graph visualization of submitted data.
MAPIT
MAPIT, or
Ma
pping
P
olice
I
n
t
eraction, is a web application that allows users to submit reports on police interactions. The goal is to aggregate data, allowing the public to use this information for a variety of things, ranging from keeping the police accountable, to identifying areas of over policing, to tackling problems of systemic nature through the identification of trends in data.
Inspiration
With increased attention drawn towards the systemic problems such as racism that can be found in police forces and the lack of data regarding it, we decided to build a program that would give power back to the people and constituents who would be able to use this data to not only educate people around them but be used to support the development of better policies, regulations and laws on all levels of government.
What it does
Users would enter information regarding the police interaction through a form. The form stores the information in a database, which can then be used to extract useful trends and data for the stats page and the map. Users will then be able to view the data by interacting with the map as well as graphs and tables on the stats page.
How we built it
HTML, CSS, JavaScript on frontend
Python with a Flask framework and SQLite database for backend
Challenges we ran into
Figuring out how to use mapping APIs well to overlay important data
Connecting SQLite database to chart.js to create a dynamic graph
Setting up the development environment (ie. git, local web server set up, etc.)
Accomplishments that we are proud of
Participate in our first hackathon!
Made a web app that has functioning parts to it
Learned a lot of new things (map APIs, CSS/Bootstrap, SQLite, etc)
What we learned
As
extremely
new hackers, we learned a number of skills that enabled us to become more comfortable with code. For many of the languages and tools that we used today, we had very limited prior experience. Thus, we were able to learn a plethora of new concepts throughout the short time span of this hackathon. Since this was our first time working on a larger project, as well as our first time collaborating on a coding project with peers, we applied teamwork and communication skills.
What's next for MAPIT
Providing more specific data based on location (by municipality, ward/communities within a municipality)
Use the other data collected (ethnicity, age, etc) for other data visualization purposes
Going through the challenges we faced and fixing the problems
Developing a mobile-friendly website or app for ease of access
Consider safety issues in terms of location tracking, user safety, etc.
Polish and improve user interface
Built With
bootstrap
css
flask
graph.js
html
javascript
leaflet.js
mspaint
python
sqlite
stack-overflow
Try it out
github.com | MAPIT | Visualizing crowd-sourced data of police interactions to promote social change and better community engagement. | ['Bonnie Lu', 'Ryan Chan', 'Daniel Qu'] | [] | ['bootstrap', 'css', 'flask', 'graph.js', 'html', 'javascript', 'leaflet.js', 'mspaint', 'python', 'sqlite', 'stack-overflow'] | 41 |
10,368 | https://devpost.com/software/inspired-tlo2y7 | Anxiety Main Page For Inspired
Home Page For Inspired
Share Your Quotes From Inspired
Bored Quotes For Inspired
Stress Page With Music For Inspired
INSPIRED
Inspired is a mobile app that helps you relieve stress, anxiety, and boredom by using quotes.
Inspiration
I decided to dedicate my project to try to help solve the mental health crisis. I got inspired after seeing how overlooked the mental health subject was. My motivation got stronger as i realized how many people had mental health issues and then I decided I would find a solution. My solution would help people become more calm, happy, and relaxed.
What it does
Inspired is an app that gives relief to stress, anxiety, and boredom using many techniques. These techniques include playing music depending on their mood, showing calm and relaxing pictures, and inspirational quotes. Using all of these, I created an app utilizing all of these to our best advantage. I also learned that people end up not knowing they have mental health problems for many years, so if someone thinks another person needs the app you can directly share the current quote through it.
How I built it
This entire app was made using Swift 5 in Xcode. To design the app I used Adobe XD to visualize the app. I made it so when you swipe a new quote will be shown using a swipe gesture recognizer. I also created a song playing system by using AVAudioPlayer().
Challenges I ran into
While creating a song playing system I ran into many problems. These problems came from the music not playing to the entire app crashing. I also had many problems with swipe reccongisers as they did not activate once I swiped. These problems held me back but after doing more in depth research on these topics I found out the problems and made sure to fix them.
Accomplishments that I'm proud of
Having known that I had an effect on helping the mental health community getting through these times has been an accomplishment for me. The purpose of this hackathon for me was to make an effect on this world, and I have achieved it. I am also proud that I completely finished the app and it is now ready for publishing. I am also proud of all the minute details I put into my apps from the music to the user friendly interface.
What I learned
I learned a lot about app development from design stage in Adobe XD to actually making it in Swift. Today I learned a lot about the programming language Swift and feel a lot more confident now about making an app before. Since this is my first hackathon I learned a lot about this format of competing and am looking forward to my future coding projects in Swift.
What's next for Inspired
I am going to upload it onto the app store and make it more mainstream for the mental health community to use. It may be a challenge but with my determination I can do it.
Built With
adobexd
swift
xcode
Try it out
github.com | Inspired | Inspired is a mobile app that helps you relieve stress, anxiety, and boredom with quotes. | ['Navadeep Budda'] | [] | ['adobexd', 'swift', 'xcode'] | 42 |
10,368 | https://devpost.com/software/thinkpos | Home Page
View Quotes
Add a Quote
Inspiration
With all the negativity being spread around in the online world, we [3 rising seniors in high school] wanted to find a solution that changes this narrative.
So, we decided to create a platform where people can spread positivity by submitting personal quotes on different topics.
Whether it is an educational, comedic, or even a interesting quote, you never know who may benefit from reading these unique statements from people coming from all walks of life. We want to provide a safe space for people to share their opinions and ideas on certain subjects without being criticized for the belief that they have.
Our goal for this project is to create a website that will leave a lasting impact on society.
What it does
ThinkPos provides people with a platform to spread positivity through personal quotes
. We provide a user-friendly platform where unique individuals can share their beliefs, ideas, and opinions on all kinds of issues that are prevalent in our lives today.
How we built it
Using
MySQL
and
Node.js
, we created a backend that stores all the quotes being written by people, along with their name and where they're from. We also created a detailed and personal frontend using
Javascript, HTML5, CSS, and Bootstrap.
*
Overall, we spent 8 hours creating this project and deployed it using Heroku. *
Challenges we ran into
We struggled to properly format the quotes and dynamically add them to the website as they were being created by the user. Along with this, we struggled with storing and retrieving the quotes from the SQL database.
Accomplishments that we're proud of
We were able to create a simple and intuitive interface to allow the users to view and write quotes with ease. We also successfully integrated the database with the frontend quotes display.
What we learned
We learned how to collaborate as a team in order to develop both ends of the website smoothly.
What's next for ThinkPos
We plan on deploying and publishing ThinkPos in order to allow people from around the world to use this platform frequently.
Built With
bootstrap
css3
html5
javascript
node.js
sql
Try it out
www.thinkpos.us
github.com | ThinkPos | Creating a positive change in the world through the power of quotes. | ['Skyler Gao', 'Ashay Parikh', 'Abhi Nayak'] | [] | ['bootstrap', 'css3', 'html5', 'javascript', 'node.js', 'sql'] | 43 |
10,368 | https://devpost.com/software/yemen-crisis-g6ei70 | Inspiration
Yemen is in the midst of the world's largest humanitarian crisis, yet the media is doing little to no coverage on it. My goal with this website was to bring more awareness to the issues in Yemen and provide an accurate data representation that can be constantly updated. People tend to take more action when the statistics and data is presented to them in an organized and appealing manner.
What it does
The website gives you a look into the crisis in Yemen through some facts and images, but the main purpose of the website is to present relevant data. The website has quicks stats pertaining to the crisis, and then present several types of charts showing the fatalities, food prices, imports, and more. It also has a resources page, allowing users to actually take action.
How I built it
I built this using html5, javascript, css.
Challenges I ran into
Some challenges I ran into was getting the charts formatted correctly and actually getting them to appear with javascript, but I was able to figure out and actually code for all of the charts.
Accomplishments that I'm proud of
I am proud to have tried something brand new using javascript to create chart, and I'm also proud of the slideshow on the homepage. The entire website idea is a big accomplishment because it can truly help others.
What's next for Yemen Crisis
I want to be able to update the data frequently as more number come in through the various sources. I also hope to expand this to other humanitarian crises around the world.
Built With
css3
html5
javascript
Try it out
yemencrisis.glitch.me | Yemen Crisis | The Yemen Crisis website was created to give a description of the humanitarian crisis going on in Yemen right now and provide a representation of the data surrounding it. | ['Saanvikha Saravanan'] | [] | ['css3', 'html5', 'javascript'] | 44 |
10,368 | https://devpost.com/software/covid-tracer-su64l9 | Inspiration
We wanted to pick something that was current, and important. There is a ton of data on Covid available, so much so that it can be difficult to read and digest. We wanted to make an application that makes it easier to understand all the information.
What it does
The application takes active data from the
Covid Tracker API
, and breaks it down by location and date. It then graphs that data so that the behavior of the virus can be seen over time more easily. It also provides some helpful links about the selected states' laws policies towards masks and other Covid related laws.
How I built it
The application uses react as the frontend, and pulls its information from the Covid Tracker API. It graphs the data using the Victory data visualization components. The Material-UI framework was used for styling.
Challenges I ran into
The formatting of the graphs so that they are dynamic while also being readable was difficult, especially since there is not that much documentation about the styling.
Accomplishments that I'm proud of
We are all very proud of the fact that we created a stylish, responsive, useful application in such a short amount of time. We are also very proud of the fact that we implemented a data predictor using linear and exponential regression, as predicting the trends of the virus is incredibly important right now.
What I learned
No one on the team had previously used data visualizers in react, nor had we used regression to make statistical predictions. We learned how to effectively use Victory, and regression.
What's next for Covid Tracer
We would like to implement a feature where you could compare the trends of more than one state at the same time.
Built With
covid-tracking-api
material-ui
react
regression-js
victory
Try it out
covid-tracer.netlify.app | Covid Tracer | A data tracker and visualizer for Covid19 cases in the United States. | ['Wesley Chen', 'matteoaricci Ricci', 'Lauren Yu'] | [] | ['covid-tracking-api', 'material-ui', 'react', 'regression-js', 'victory'] | 45 |
10,368 | https://devpost.com/software/smplfy | Inspiration
Often when trying to read research papers or articles for school or related projects, I found myself switching back and forth between the website and a dictionary for words or sentences I could not understand. I thought it was natural to come up an extension within Chrome itself that would save time and effort.
What it does
Smplfy is a chrome extension that takes what you have highlighted on a page and substitutes words or phrases that may potentially be difficult for the reader to understand with those that are much more, simple.
How I built it
Smplfy, being a Chrome extension, is like a mini-website built upon HTML and JavaScript. It reads what the user has highlighted and then sends API requests to the Datamuse API and database in order to get word-related information.
Challenges I ran into
The foundation of the extension was relatively easy to code; I spent most of my time fixing small bugs and fine-tuning the reliability and accuracy of the program.
Accomplishments that I'm proud of
I am really happy to have found a resource like the Datamuse API/database; I wish I had used it for projects in the past that required word-related API and I definitely will use it again in the future. I am also really excited to have made a functional Chrome Extension for the first time.
What I learned
I learned a lot about building Chrome Extensions and about APIs in general, specifically Datamuse.
What's next for Smplfy
Smplfy still is not 100% perfect, and I hope to tackle common errors and potential bugs in the near future! I am also considering certain peripheral features such as a dictionary.
Built With
datamuse
html
javascript
jquery
Try it out
github.com | Smplfy | Ever read an article or research paper online but had trouble understanding what it was trying to say? Smplfy is your guide! | ['Ashwin Rajesh'] | [] | ['datamuse', 'html', 'javascript', 'jquery'] | 46 |
10,368 | https://devpost.com/software/line-jumper | Inspiration
Although most countries are in quarantine amidst the COVID-19 pandemic, a lot of people still need to go out of their homes and buy groceries. Sometimes grocery stores can become overwhelmed with an influx of people and have to start lineups outside, creating higher infection risks for both customers and employees. We wanted to find a way to help people plan their grocery trips and minimize their waiting times.
What it does
Line Jumper uses crowdsourced data to determine the average wait time for specific grocery stores. It also allows users to find a grocery store's contact information and to leave their own input on their shopping experience.
How we built it
Line Jumper is created using the Flutter SDK and the Dart programming language. This allows it to be a cross-platform application for both Android and iOS.
Challenges we ran into
It was difficult finding existing data on grocery store lineups. So instead, we decided to use crowdsourcing, since it's more accessible than relying on companies to provide this information.
Accomplishments that we're proud of
We're really happy with the user flow that we created – it's straightforward and easy-to-use. For example, Line Jumper presents the user's recently visited store at the top of its homepage so the user can access the grocer they visit frequently.
What we learned
We learned that it was hard to find the necessary datasets or APIs for our use case. Since most datasets we found were static, it was difficult to search for real-time data regarding the waiting times and store information during the pandemic. Fortunately, we realized that data doesn't have to come as static datasets, but instead as crowdsourced data where members of the community would work together to inform one another.
Built With
dart
flutter
Try it out
github.com | Line Jumper | A handy tool for monitoring grocery store lineups during COVID-19 | ['Rafael Flora', 'Celina Gallardo'] | [] | ['dart', 'flutter'] | 47 |
10,368 | https://devpost.com/software/tobedecided | Inspiration
Inspired by the situation in Delhi, India, wherein people who get the report of "COVID-positive" are expected to visit a hospital and queue up for hours together for
a chance to get a bed
at the hospital. If they do not get a bed, they go to another hospital, queue up for hours, and
hope
for a bed there too. This movement of COVID-19 positive patients from hospital to hospital and queueing up is troublesome in two of many ways. Firstly, this movement increases the risk of spreading of the virus itself as these patients visit many different hospitals in the hope to get a bed, thereby infecting so many different places. Secondly, these patients do not get immediate care, and are forced to spend time waiting in queues.
An added problem arises in beds being "booked" by people in power and those that can pay the highest for that bed. A news report featured a shocking amount asked by a COVID-19 patient of 1 lakh INR (£1061) per bed per night. During the current times of pandemic, corruption in healthcare must be condemned. Beds must be allotted based on case severity and not on the amount of money.
This inspired us to make an application that would help overcome these issues, and be able to allot a bed to the person, most in need, without them having to queue up and go hospital-to-hospital.
What it does
What if we could automate this system of "queueing-up" for a bed? What if we could have a system wherein COVID-19 positive patients would know exactly which hospital to go for a guaranteed bed, at the ease of their phone?
Keeping this in mind, we created a mobile application that lets:
1) COVID-19 patients look at bed availability in hospitals nearby,
2) COVID-19 patients send one e-application (through the app) for a bed to hospitals within 10km radius, by filling in details (such as age, past illnesses, travel history etc.) and attaching COVID-19 positive report scan,
3) The Machine Learning algorithm predicts and ranks the severity of the case/e-application using these details per bed space,
4) Based on the results of the ML model, hospital officials can be suggested on who the bed should be allotted to instead of allowing officials to indulge in allotting the bed to the highest bidder (the one with most money)
5) A hospital then allots an available bed to the most critical case/application after which the case/application is marked as "Treated" on the database of applications, which would signal to other hospitals that this particular case has already been catered to
6) The person who has been allotted the bed, gets a notification and a set time to arrive at.
In other words, we are creating a database of beds and the applications for those bed spaces, which are then ranked on the basis of severity using questions answered by the patient. The most severely ranked case gets a bed. This process brings about transparency and helps cater to those who need it most. It would aid in removing any corruption that exists in allotting bed spaces.
How we built it
The steps we followed for creating the ML model are:
1) Acquiring the Dataset: We found an appropriate dataset for this particular use case, on Kaggle.
2) Data Visualisation: We tried to visualise the data using various techniques and plots. We built correlation matrices, scatter and density plots, histograms to see which symptoms affected severity the most.
3) Data split: We split the data into 70:30 train:test.
4) Training: We trained the random forest classifier model on 70% of the data.
5) Testing: We then tested the model using the rest of the data.
6) Evaluation: We used various evaluation metrics to judge the performance of the model. It possessed a mean score of roughly 74%.
We then designed the app 'Covey', keeping in mind a simple user interface allowing easy input of data from the user point of view.
Further, we included a code written in JavaScript, which involved the Twilio framework to develop a messaging system to notify a patient if they have been allotted a bed at a hospital.
Challenges we ran into
Finding an appropriate dataset was the hardest task. This is because of the limited research on the ongoing pandemic. Secondly, downloading a few libraries that would satisfy the version requirement, took a significant bit of time and debugging.
What's next for COVID-19 Automatic Bed Allotter
We wish to increase the accuracy of our ML classifier and train it on a more intensive dataset, which includes more combinations of symptoms and other illnesses.
We are hoping to completely integrate the ML model with the app. Also, we hope to automate the notification being sent after a bed is allotted, as currently it requires a prompt to run the code which then triggers a notification.
Try out our App!
https://xd.adobe.com/view/3dbb8b3d-33da-4aca-9b7e-68ef428f888e-68e8/
Built With
adobe
javascript
machine-learning
node.js
python
random-forest-classifier
scikit-learn
twilio
Try it out
xd.adobe.com
github.com | COVID-19 Automatic Bed Allotter | Allotting hospital beds to those who need it the most in a fair and transparent manner. | ['Arun Venugopal', 'Arushi Madan'] | ['Best COVID-19 Hack'] | ['adobe', 'javascript', 'machine-learning', 'node.js', 'python', 'random-forest-classifier', 'scikit-learn', 'twilio'] | 48 |
10,368 | https://devpost.com/software/datadaygrind | HeartTrends Logo
Home page, displays the various analyses performed.
Depicts the age distribution among those affected by heart disease.
Proof for domain name, hearttrends.tech
Inspiration
Cardiovascular diseases, resulting in compromised blood vessels, clogged blood clots, and weakened hearts, are the leading cause of death for men, women, and the most racial/ethnic groups in the United States. One person every 37 seconds die from heart disease. HeartTrends offers an eye-opening data analysis that delves into the multiple factors and variables behind those affected.
What it does
HeartTrends is a simple yet immersive web application that discovers interesting trends and distributions from a UC Irvine database. The website depicts 5 novel factors behind cardiovascular diseases -- age, chest pain type, maximum heart rate, resting blood pressure, and serum cholesterol. Initially greeted with the home page, the user can choose from a variety of selection cards that link to a full-page exploratory analysis of previously mentioned factors behind the disease. Each plot offers an interesting relationship between general heart health and variables that can be easily measured at any time. The dataset used is primary data from people hospitalized for cardiovascular disease. Thus, the user can compare their own heart rate and blood pressure to the distribution, serving as a predictive model for future heart attacks and resulting symptoms.
How I built it
I built HeartTrends using R and NextJS. To generate all of the plots and charts that are displayed on the website, I coded a command script that reads in a CSV file taken from the UC Irvine Dataset on Kaggle. Then I sorted the file into the corresponding variables and created 6 ggplots of the age, heart rate, chest pain, blood pressure, and serum cholesterol. The y-axes display the frequency and the x-axes are the numerical distributions. After I created a plot of each of the factors, I combined them into one image, shown in the "All Plots" card, by using the grid.arrange function. I used NextJS and used CSS styling to create an easily navigable UI. The 6 cards redirect the user to their chosen analysis, serving as an informative and effective web application.
Challenges I ran into
This was one of my first times analyzing data and creating meaningful plots in R Studio. It was challenging to build and arrange the plots, but after reading more R documentation, it was awesome to see such interesting trends come out of a complex CSV file.
Accomplishments that I'm proud of
I'm proud of providing an easy-to-use predictive model for such a prevalent and dangerous condition.
What I learned
I learned how to data-mine and plot interesting graphs. I also discovered the impact that a good CSS style can make on a website. Initially, my website was composed of radio buttons and default fonts. But after creating new text formats and designs, I was surprised to see how great the UI appeared.
What's next for HeartTrends
I plan for HeartTrends to be expanded to include more diseases, such as different cancers and viruses. With the widespread COVID-19 chaos, I want to provide an exploratory website that can show the distribution of the virus around the world.
Built With
javascript
nextjs
r
react
Try it out
github.com
hearttrends.tech | HeartTrends | Predictive models for cardiovascular diseases through an exploratory UI. | ['Danny Zhang'] | [] | ['javascript', 'nextjs', 'r', 'react'] | 49 |
10,368 | https://devpost.com/software/covid-19-ultimate-tracker | s | i | s | [] | [] | [] | 50 |
10,368 | https://devpost.com/software/todoista | TODOISTA - Todo Apps made simpler
This web application is made with MongoDB, Express.js, React.js and Node.js. It has a simple motive to fulfil- making todo lists simple.
Features
Logged Exercises
Your todo list
Create todo Logged
Create User
Start date and deadlines included
ScreenShots
Check out the video on Vimeo
🤝 How to Contribute
For sending PR:-
Pick an open issue from the
issue list
and claim it in the comments. After approval fix the issue and send us a pull request (PR).
All the PR’s need to be sent to the appropriate branch (usually "master").
For Open issue:-
You can create a new issue and send a pull request.
Please go through our issue list first (open as well as closed) and make sure the issue you are reporting does not replicate an issue already reported. If you have issues on multiple pages, report them separately. Do not combine them into a single issue.
Our submission for the StackHack 1.0 Online Hackathon
Link
Important points
On Front End:
Implement a feature to add Tasks.
Implement a feature to set the due date for these tasks.
On Back end:
Implement the backend in one of the desired Tech-Stacks provided below.
Your backend is supposed to store all the tasks data received from the Frontend and store it in the Database.
You are also supposed to implement a Database in the Backend which should store all this structured data.
The data sharing between Frontend and Backend should be in JSON format rendered over REST APIs.
Zip all your Source Code, Screenshots, Deployment Instructions and Upload.
Contributors
Garima Singh
Mrinal
This project was bootstrapped with
Create React App
.
Available Scripts
In the project directory, you can run:
npm 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.
npm test
Launches the test runner in the interactive watch mode.
See the section about
running tests
for more information.
npm run 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.
npm run eject
Note: this is a one-way operation. Once you
eject
, you can’t go back!
If you aren’t satisfied with the build tool and configuration choices, you can
eject
at any time. This command will remove the single build dependency from your project.
Instead, it will copy all the configuration files and the transitive dependencies (webpack, Babel, ESLint, etc) right into your project so you have full control over them. All of the commands except
eject
will still work, but they will point to the copied scripts so you can tweak them. At this point you’re on your own.
You don’t have to ever use
eject
. The curated feature set is suitable for small and middle deployments, and you shouldn’t feel obligated to use this feature. However we understand that this tool wouldn’t be useful if you couldn’t customize it when you are ready for it.
Learn More
You can learn more in the
Create React App documentation
.
To learn React, check out the
React documentation
.
Code Splitting
This section has moved here:
https://facebook.github.io/create-react-app/docs/code-splitting
Analyzing the Bundle Size
This section has moved here:
https://facebook.github.io/create-react-app/docs/analyzing-the-bundle-size
Making a Progressive Web App
This section has moved here:
https://facebook.github.io/create-react-app/docs/making-a-progressive-web-app
Advanced Configuration
This section has moved here:
https://facebook.github.io/create-react-app/docs/advanced-configuration
Deployment
This section has moved here:
https://facebook.github.io/create-react-app/docs/deployment
npm run build
fails to minify
This section has moved here:
https://facebook.github.io/create-react-app/docs/troubleshooting#npm-run-build-fails-to-minify
💜
Thanks
Built With
css
html
javascript
Try it out
vigorous-kalam-504459.netlify.app
github.com | ToDoista | A ToDo app :orange_book: made using MERN. Keep a track of your activities on a single click. :thought_balloon: :computer: | ['Garima Singh'] | [] | ['css', 'html', 'javascript'] | 51 |
10,368 | https://devpost.com/software/opportunity-recommendation-system-ors | . | . | . | ['rahul garg', 'Pulkit Midha'] | [] | [] | 52 |
10,368 | https://devpost.com/software/iremember | First Look Prototype of iRemember
Logo
Inspiration
There are many mood tracking apps that keep a log of a user's mood for a specific day, and to look back at the end of the month to see the mood progress of the user. We, the iRemember team, however wanted to create an app that somehow captures important moments of an user's day, and turn it into a visualization users can look back at to see their wellness trends, and how these small moments (such as the hrs of sleep, daily tasks, feelings, thoughts, and moods) have progressed for any particular time period. Our motto is:
To make a difference in the world, we need to make a positive impact in peoples lives.
What it does
We wanted to create a daily task tracker, where a mobile app would help a user track simple things he/she does daily, and then help him/her see the pattern. For example, on a scale of 1-10, how healthy were your meals today, how easy was it to fall asleep, how much did you spent on social media, how much time you spent around nature, how much physical movement you did, how stressed were you or how optimistic are you. We would split these questions into different tracks -> '
Mood
', '
Sleep
', '
Health and Wellness
', and '
Daily Tasks you did today
'. Then we could show the users the correlation through graphs. For instance, a user can see whenever they got more hours of sleep, they felt less stressed and more peaceful (through the mood tracker and sleep tracker). Whenever you exercised, it was easier to fall asleep. Whenever you spent more time on social media, you felt your life was purposeless.
How we built it
We built the three pages (home, tracking page, and trends) using react native and javascript.
Challenges we ran into
Ran into some debugging issues with react native, since it was a new tool for us! But we learned a lot from it!
Accomplishments that we are proud of
Built a UI interface and home page + tracking with react native and got to learn several different and cool functionalities of app development!
What's next for iREMEMBER
Building more pages and integrating the app together to launch it to the world. We also want our product to potentially help and support Alzheimers patients in the future as well.
To make a difference in the world, we need to make a positive impact in peoples lives.
Built With
github
javascript
keynote
react-native
Try it out
github.com | iREMEMBER | Discover and find your trends! | ['Mualla Argin', 'Aarushi Ramesh', 'Rutvi Shah'] | [] | ['github', 'javascript', 'keynote', 'react-native'] | 53 |
10,368 | https://devpost.com/software/build-an-blockchain-app | Problems It Resolves
Inspiration
I.Fear of Missing Out’ Blockchain Solutions
2.Opportunistic Solutions
3.3. Trojan Horse Projects
Evolutionary Blockchain Projects
Blockchain-Native Solutions
I built it Using Blockchain to build a blockchain app using Etherium smart contracts . I will learn how to create a todo app with Etherium smart contracts using the Solidity programming language. I will also learn to write tests, deploy to the blockchain, and create a client-side application.
I will learn how to create a todo app with Etherium smart contracts using the Solidity programming language. I will also learn to write tests, deploy to the blockchain, and create a client-side application.
Accomplishments that I will learn how to create a todo app with Etherium smart contracts using the Solidity programming language. I will also learn to write tests, deploy to the blockchain, and create a client-side application.
I learned I will learn how to create a todo app with Etherium smart contracts using the Solidity programming language.
Cryptocurrency Converter In JavaScript .This is my Next Goal Which I am Currently Working On,
Built With
blockchain
django
iot
Try it out
github.com | Build an Blockchain app | A Guide to the Types of Blockchain Projects Ruling the Decentralized Economy By Sudeep Srivastav | ['Situ Dash'] | [] | ['blockchain', 'django', 'iot'] | 54 |
10,370 | https://devpost.com/software/codecapture | Inspiration
While in recent times, the world has started moving towards pro-CS education, the fact is that buying computers is a distant dream for most students and educational institutions across the globe even today. In most developing countries, the ratio of CS students versus the number of computers available is highly skewed and most students are still learning programming via pen-and-paper. Therefore, we decided to develop an extension for Visual Studio Code, one of the most commonly used code editors in the world, to be able to capture code from scanned images of handwritten text and save it in a file of the right extension on the computer.
What it does
The CodeCapture extension scans the image selected by the user for handwritten C code and gives us the formatted code in a separate '.c' file in our directory to be checked and tested. This allows us to test and check the code developed by multiple users in a short period of time.
How we built it
Upon coming up with the idea, we divided the extension into three major sections: Picking an image, calling the Computer Vision Read API, and using the response received to write to an output file.
For picking an image, we used the VS Code Extension API to have a native dialog asking the user to choose an image from local storage.
To call the Azure Computer Vision Read API,
axios
was used to make both the POST and GET Http requests.
The response received from the API was mapped to a string in a line by line format and was populated in a new file using the VS Code API.
Challenges we ran into
One challenge that we ran into was that we were not able to give formatted code in the output. As a temporary solution, we recommend the users to use a beautification extension for the time being.
Another challenge we faced was not being able to write to a file using node.js, we spent a few hours trying to work around the 'fs' npm package, after which we stumbled upon the VS Code API for the same and it made the task rather simple.
Accomplishments that we're proud of
This was our first ever experience creating a Visual Studio Code extension. Apart from that, not only did we create a functioning ML-enabled extension, but we also created a socially beneficial application that can help students and educators worldwide in improving the programming learning experience.
One major accomplishment that we achieved was using the Azure Computer Vision Read API for scanning the handwritten code. As we are all amateur hackers, creating an ML-enabled extension was definitely a Herculean task for us, which we successfully implemented.
What we learned
Our biggest learning was creating our first VS Code extension. Apart from that, we also learned how to use Computer Vision API (handwritten text detection - Read API) functionality using the powerful features available in Azure Cognitive Services. Also, since only one out of the 4 of us had prior full-stack development experience, it was also a great opportunity for the lot of us to learn JavaScript.
What's next for CodeCapture
We will be working on implementing in-built code formatting functionality to help the users beautify the output they need before it is saved in the file. We will also be working on adding multi-language support for languages such as Java, Python, etc. to make it more intuitive user experience.
Built With
azure
computer-vision
javascript
json
vscode-api
vscodeextension-api
Try it out
github.com
marketplace.visualstudio.com | CodeCapture - VS Code Extension | A collaborative VS Code Extension that scans handwritten code from images and saves it in the concerned file-type to check and test | ['Simran Makhija', 'Aditya Oberai', 'ekansh gupta', 'Nandini Sharma'] | ['Best Overall'] | ['azure', 'computer-vision', 'javascript', 'json', 'vscode-api', 'vscodeextension-api'] | 0 |
10,370 | https://devpost.com/software/aristotle-d9xl1w | Inspiration
If there is one thing we can agree on, despite meeting for the first time, it’s that Coding isn’t easy. Have you ever been in a situation like this?
One of the major issues shared by entry-level programmers in the difficulty in understanding the logic behind the function they are writing, especially with all the abstract notations, figures, and grammar.
Regardless of what programming language you are learning, logical and analytical thinking is the basic essence of programming and overlooking it is a bad idea.
This can be made worse if you are unfamiliar to English – the dominant tongue of programming languages, since your way of logical train of thought could be significantly different. Well then, what should we do?
What it does
Meet Aristotle – an extension to help you follow logic behind codes.
Say I am a beginner, who stumbled across an apparent solution code online that finds the area of a triangle but can’t figure out why it works. I can submit it and call it a day but that isn’t learning! Aristotle translates your code into pseudocode, adjusted to resemble natural language as much as possible. The logic behind your code can be analyzed step by step - inducing greater critical thinking rather than obvious hints for solutions.
Our pseudocode is also easier and more accurate when translated, making logical analysis more accessible to international students. Aristotle also promotes a community of logical thinkers. You can upload your code – pseudocode pair (Share), then browse similar cases from others for comparative studies and further inspiration. If you want to discover others’ train of thoughts while solving certain types of problems, rather than easy solutions, you can use our search engine to see relevant examples.
By building this ecosystem, we hope to aid students’ properly grasp the foundation of programming in a more accessible manner.
How I built it
We used Javascript(NodeJS) to set up the project, and enable WebView as a view engine of our project. Dynamic contents (e.g. rendering different pages) and UI of the WebView was done with HTML, CSS, and Javascript. We implemented a Python script responsible for translating the code to pseudocode, and allow it to run on NodeJS background.
Challenges I ran into
It was our first time publishing an extension, so it took some time to get used to Azure development tools. Additionally, generating code to pseudocode took very long time, especially in considering enormous ways to write a code, and generating the pseudocode that is easily readable.
Accomplishments that I'm proud of
We are all so excited to present a fully functional extension within a day.
What I learned
We learned a lot about VSCode system itself, how extension commands function and how to customize the contents of VSCode.
What's next for Aristotle
It would be a dream for us to further polish the extension and have users from all around the world. If we were given more time, we would like to implement some chatting features that cheer people up during the pandemic and further expand conversational features.
Try it out
marketplace.visualstudio.com
github.com | Aristotle | Understand the logic behind your code | ['Sanghoo Oh', 'Sang min Lee', 'Hyunjoe Yoo', 'Yona Kim'] | ['Most Creative'] | [] | 1 |
10,370 | https://devpost.com/software/vscode-puzzle | Banner image for the project.
Screenshot of an example output.
vscode-puzzle
vscode-puzzle is a super simple VSCode add-on that collects a problem from the internet and brings it directly into your editor. Practice your programming skills with ease.
Note: this project was built start to finish in the last 24 hours. It was not started before the hackathon began. Here's
proof
!
Features
vscode-puzzle currently supports problems from r/dailyprogrammer, ProjectEuler, and CodingBat. It fetches a random problem for any of those three sites, creates a folder, and stores both a markdown file with the problem description and creates a
.py
file for you to begin your solution.
In the future, there is a plan to support a different preferred export type (other than Python), and problems from different websites.
Requirements
n/a
Extension Settings
In the future, there will be an option to set your preferred solving language.
TODO: use the
contributes.configuration
extension point to set this up!
Known Issues
TBD
Release Notes
This is currently being built as a part of the Microsoft VSCode Hackathon. Release notes to come following this weekend.
1.0.0
The initial release of vscode-puzzle is described above.
Built With
typescript
vscode
Try it out
michaelfromyeg.github.io
github.com
marketplace.visualstudio.com | VSCode Puzzles | A super simple VSCode add-on to go grab a coding puzzle from the internet and place it in your current directory. | ['Michael DeMarco'] | ['Best use of an external API'] | ['typescript', 'vscode'] | 2 |
10,370 | https://devpost.com/software/errorresolver-vscode-extension | Extension
Inspiration
As developers use Stack Overflow as a daily tool to get all their queries, so why not develop an extension where you don't have to leave VSCode at all and get the same experience of error resolving.
What it does
User can search any query/errors they are having and get it answered within the VSCode
How I built it
I used the StackOverflow API to fetch the questions and the answers.
Challenges I ran into
As it was my first time in developing a VSCode Extension, I had some minor issues in working with the data and displaying it.
Accomplishments that I'm proud of
I created an extension which will be helpful for every developer out there :D
What I learned
How to develop VSCode Extensions.
What's next for ErrorResolver VSCode Extension
Publishing it in marketplace and adding new features
Built With
html
stackoverflow-api
typescript
Try it out
github.com | ErrorResolver VSCode Extension | Resolve your errors by searching them on StackOverflow within VSCode. | ['Sumit Banik'] | [] | ['html', 'stackoverflow-api', 'typescript'] | 3 |
10,370 | https://devpost.com/software/language-helper | Inspiration
Helping out all the new programmers who get bogged down and stressed out by all the different resources and varrying information.
What it does
Gamifies the learning process, solidfying productive habit of learning and practicing
Challenges we ran into
A new API to learn to use.
Accomplishments that we're proud of
Having a semi-working product at the end of the day.
What we learnt
To overcome all odds and adversities to produce a final result.
What's next for Language Helper
Integration of custom challenges, a more interactive GUI.
Built With
css
html
javascript
jquery
node.js
Try it out
github.com | Language Helper | Teaching users how to code in the easiest way possible. Gamifying the process and reducing stress along the way. | ['ghulamusman Usman', 'Ben Schack', 'Satyam Raina', 'eames-palmer Palmer'] | [] | ['css', 'html', 'javascript', 'jquery', 'node.js'] | 4 |
10,370 | https://devpost.com/software/helpme-vscode-extension | helpme README
This is the README for our extension "helpme".
Features
Tired of retyping the same errors into Google and StackOverflow? Can't remember the one amazing link you once used for an elegant one-liner?
Helpme is here to save the day!
To add a question, simply type
+
and enter the question details and link:
Triggering question add
Adding question details
Adding question URL
To search added questions, type
#
and choose from the autocomplete dropdown.
Triggering question search
Searching questions list
Requirements
The project dependencies include
"jsonfile": "^6.0.1",
"path": "^0.12.7"
and can be installed by running
npm install .
after cloning the extension repo.
Release Notes
Will be updated!
1.0.0
Initial release of helpme!
Built With
typescript
Try it out
github.com
marketplace.visualstudio.com | helpme-vscode-extension | Access frequently used helper code links without leaving VS Code! | ['Raul Alcantara', 'Shinjini Ghosh'] | [] | ['typescript'] | 5 |
10,370 | https://devpost.com/software/note-it-a8jhdt | When I started coding, the initial hurdles were to remember the things I learnt in that particular tutorial. I would add comments above code snippets to make sure I remembered what that particular code did. This helped when I was reading the code, but when I wanted to refer back that code in some other project, I had to keep searching my project directory. Also during the tutorial I used to note down the important tips and tricks that the instructor used to mention. Writing them down on a paper proved inefficient as I again had to search through pages.
This extension will help new coders to mark code snippets and write brief comments about them which would get saved in a single file inside the project directory. Suppose, I want to save how I implemented authentication using node.js I can just select the important lines of code snippets and click the extension to save it in a new file with my added comments. I can refer the same code snippet later on just by opening that file instead of searching the entire project directory.
This is exactly the extension I needed but didn't find any. This extension has lot of scope to be improved by adding code tracking and other features which would really help beginners. I hope this extension would help new coders to improve their efficiency and help them in their future projects.
Built With
typescript
Try it out
github.com | Note-It | A simple vs code extension to make notes of your code snippets. | ['Karan Hejmadi'] | [] | ['typescript'] | 6 |
10,370 | https://devpost.com/software/webdev | Inspiration
as students we went through difficulties trying to teach myself web developments we want to make it easier for new student and with little encouragement to keep on it I added a motivational massages.
What it does
It create the boilerplate of the web page in html and css
How I built it
as a team we used the documentation VS website provided.
Challenges I ran into
we ran into some errors adding html to the code.
Accomplishments that I'm proud of
create my first VS extension.
What I learned
as a team we learned how to create an extension from scratch.
What's next for WebDev
adding the new version of bootstraps to it.
Built With
javascript
Try it out
github.com | WebDev | ¡Let's make learning web development easier! The users are motivated to do so. | ['Zinah ALJANABI', 'Alfredo RI', 'Mehak Kamal', 'Niver Martinez'] | [] | ['javascript'] | 7 |
10,370 | https://devpost.com/software/cpp_snippet_extension | Mostly beginners start with python now a days so to move from python to another language one has to understand some syntactical changes. As python is less syntactical when learning another language say c++ one has to understand its syntax. So with this extension on can learn how c++ syntax are for print , for loop, while loop, if-else,etc
we learned how we can create snippet of code even say custom snippets.
for this
cpp_snippet_extension,
when user type any syntax name for example
"if-else" *
then snippet will suggest *
"if-else" condition
and after hitting the suggestion the whole syntax will comes up in editor. every syntax in the c++ we can use it using*
cpp_snippet_extension,
* by using this it will easier to code the program for beginners. and he/she can understand the syntax format of c++.
for now we have the snippet for the c++ language.we can add more for different languages.
it was really exciting to make the cool interesting snippet from VS code
we will add more feature in it
More functionality and support for snippets
Built With
javascript
json
node.js
Try it out
github.com | cpp_snippet_extension | The idea is to make young coders feel comfortable to get accustomed to cpp syntax as they move from less syntactical language like python | ['riddhi gondaliya', 'Ninad10code Dadmal', 'Paola Montserrat Vega Ortega', 'Abdul Moueed'] | [] | ['javascript', 'json', 'node.js'] | 8 |
10,370 | https://devpost.com/software/ms-learn-vs-code-extension |
window.fbAsyncInit = function() {
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
)
}
});
};
(function (d, s, id) {
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
Microsoft Learn
offers the definitive guide to learn code concepts and offer a variety of
learning paths
, this inspired me to build an extension
integrated
with VS code so
the learner doesn't have to switch between the browser and the development environment
.
What it does
This extension is a webview for the Microsoft Learn website, allowing seamless integration inside the VS Code instead of switching to a separate browser.
How I built it
This extension is built using Node.js, Yeoman, and VS Code Extension Generator.
The Yeoman and VS Code Generator packages are installed using the node package manager npm using the VS Code terminal. Subsequently, Yeoman allows generating the extension workspace while building it from existing templates.
The package is then modified to create a command that responds to running the extension. In this case, webview panel generates the desired webpage when an appropriate HTML source is provided.
Challenges I ran into
I ran into challenges associated with populating the webview panel to display the website content.
Accomplishments that I'm proud of
My first VS Code extension on the marketplace.
What I learned
I learned that great UX is very important and it should not only be visually appealing but it should also offer ease of accessibility.
What's next for MS Learn VS Code Extension
This extension can be greatly expanded to offer embedded tutorials, ready to import code blocks, and much more!
Built With
html
node.js
npm
typescript
Try it out
github.com | Microsoft Learn VS Code Extension | Learn to code with built in support for Microsoft Learn in VS Code | ['Shivam Beniwal'] | [] | ['html', 'node.js', 'npm', 'typescript'] | 9 |
10,370 | https://devpost.com/software/vega-vscode-extension | Inspiration
VSCode extension API is really powerful and MLH gave us an opportunity to use the same, to build new things and help young developers to shine.
What it does
It converts vega json format to chart, which can be viewed in the webview
How I built it
I used the vega library for parsing the json and vscode extension api
Challenges I ran into
The problems mostly faced where regarding integrating and using the charting library
Accomplishments that I'm proud of
What I learned
What's next for Vega VSCode Extension
I am looking for to build this extension even further and give variety of configurations for the charts.
Built With
vega
vscode
Try it out
github.com | Vega VSCode Extension | This extension uses Vega library to generate graphs from JSON. VEGA is a visualization grammar, a declarative language for creating, saving, and sharing interactive visualization designs. | ['Adrij Shikhar'] | [] | ['vega', 'vscode'] | 10 |
10,370 | https://devpost.com/software/take-a-break-s3jzri | GIF
Take a Break! in action
Inspiration
I keep getting mesmerised into the world of programming. Its common with developers and sometimes we need a push to take a break and maintain our cool.
What it does
This extension allows you to set a reminder to take a break.
How I built it
I build using typescript and VSCode APIs
Challenges I ran into
My main challenge was to understand the VSCode API and extension structure.
Accomplishments that I'm proud of
I am glad, i got to work on my first VSCode extension via this Hackathon.
What I learned
I learnt to built amazing extensions for VSCode.
What's next for Take a Break!
Adding more customizations and shortcuts
Built With
javascript
node.js
typescript
Try it out
github.com
marketplace.visualstudio.com | Take a Break! | It's nice to deep dive into programming but you gotta take a break sometimes to prevent your brain from crashing. | ['Syed Umair'] | [] | ['javascript', 'node.js', 'typescript'] | 11 |
10,370 | https://devpost.com/software/vscode-extension | Bootstrap 4 with CDN
Ever been trying to start with a bootstrap template?
This is normally not an issue but I found it tedious with using
!
then add all CSS with font-awesome and jquery etc.
This extension will solve the issue for you with a simple
!bcdn
+
TAB
and your up and running with a full template
Shortcuts / Commands
Bootswatch Template variations
Command
*
Help Text *
!bcdncerulean
Creates an Bootstrap 4 Template with Cerulean Bootswatch Colors
!bcdncosmo
Creates an Bootstrap 4 Template with Cosmo Bootswatch colors
!bcdncyborg
Creates an Bootstrap 4 Template with Cyborg Bootswatch colors
!bcdndarkly
Creates an Bootstrap 4 Template with Darkly Bootswatch colors
!bcdnflatly
Creates an Bootstrap 4 Template with Flatly Bootswatch colors
!bcdnjournal
Creates an Bootstrap 4 Template with Journal Bootswatch colors
!bcdnlitera
Creates an Bootstrap 4 Template with Litera Bootswatch colors
!bcdnlumen
Creates an Bootstrap 4 Template with Lumen Bootswatch colors
!bcdnlux
Creates an Bootstrap 4 Template with Lux Bootswatch colors
!bcdnmateria
Creates an Bootstrap 4 Template with Materia Bootswatch colors
!bcdnminty
Creates an Bootstrap 4 Template with Minty Bootswatch colors
!bcdnpulse
Creates an Bootstrap 4 Template with Pulse Bootswatch colors
!bcdnsandstone
Creates an Bootstrap 4 Template with Sandstone Bootswatch colors
!bcdnsimplex
Creates an Bootstrap 4 Template with Simplex Bootswatch colors
!bcdnsketchy
Creates an Bootstrap 4 Template with Sketchy Bootswatch colors
!bcdnslate
Creates an Bootstrap 4 Template with Slate Bootswatch colors
!bcdnsolar
Creates an Bootstrap 4 Template with solar Bootswatch colors
!bcdnspacelab
Creates an Bootstrap 4 Template with Space Lab Bootswatch colors
!bcdnsuperhero
Creates an Bootstrap 4 Template with Super Hero Bootswatch colors
!bcdnunited
Creates an Bootstrap 4 Template with United Bootswatch colors
!bcdnyeti
Creates an Bootstrap 4 Template with Yeti Bootswatch colors
Try it out
github.com | vscode-bootstrap-extension | Hello Everyone, I am Sumit Saha and currently I am pursuing B.Tech CSE from MVJCE and I made bootstrap template for doing things easier. | ['Sumit Saha'] | [] | [] | 12 |
10,370 | https://devpost.com/software/nightbow | Nightbow
Nightbow is a true black VS Code theme with bright colors.
Prerequisites
Before you begin, ensure you have met the following requirements:
You have installed the latest version of
VS Code
.
Installing Nightbow
Nightbow can be found in the VS Code Extensions gallery and in the Marketplace.
Using Nightbow
Change VS Code colorscheme to
Nightbow
.
More Info
Built With
vscode
Try it out
github.com
marketplace.visualstudio.com | Nightbow | A true black VS Code theme with bright colors. 🌃🌈 | ['Abhishek Keshri'] | [] | ['vscode'] | 13 |
10,370 | https://devpost.com/software/ask-me | GIF
Demo
Inspiration ❤️
.
Our main inspiration was the Stackoverflow bot.
We wanna contribute to make easier programming learning.
We remembered the old Microsoft Office assistant (Clip :heart_eyes:) and thought it was a good idea to have something like this on VSCode.
What it does 🤔
Smart chatbot that help with common programming questions.
How we built it 🛠
Keras
,
gensim
and
scipy
for NLP (Emanuel)
Microservices architecture
for consuming the machine learning models (Emanuel)
** Strapi** for the data management (Wilson)
and a
WebView
for rendering the chat on VSCode. (Juan, Wilson)
Challenges we ran into 🤯
Connections between microservices 😩 and some small issues with the WebView on VSCode.
Accomplishments that we are proud of 🧐
We finished and published the extension! 🎉🎉
What we learned
We learned a lot about the VSCode extensions ecosystem and the Extension API.
What's next for Ask me
Support javascript and many others languages
Built With
gemsim
html5
keras
node.js
postgresql
python
strapi
typescript
Try it out
github.com
github.com | Ask me | Your smart assistant for coding | ['Juan Rodriguez', 'Wilson Tovar', 'Emanuel Isaac Afanador'] | [] | ['gemsim', 'html5', 'keras', 'node.js', 'postgresql', 'python', 'strapi', 'typescript'] | 14 |
10,370 | https://devpost.com/software/wewecode | The Inspiration
The first time I learned coding (through an online course), I struggled so much I didn't touch code for a year. Struggling helps us grow, but struggling alone is very daunting. I didn't know how many others were struggling as well. It was just me in my bedroom. Little did I know about open source projects. And when I did, the act of git merging my newbie code into a public project refueled my nightmares. I wanted to work with someone at my level in real time to debug import statements and learn with me. After completing my first group project at college, I learned a valuable lesson. Struggling alongside other peers fosters a great sense of community and collaborative problem solving.
The Idea
Personal projects can be tough to think of and difficult to embark on. We wanted to leverage the power of peer programming that VS Code's live share offers along with the sense of community opensource platforms provide. Using the extension, users can post their project live share link with descriptions onto the WeWe Code site. They can also cap the amount of peers they are looking for. Peers looking to join projects can scroll through WeWe Code interface to find a project of their liking.
The Tech
We used flask, python, and sql alchemy to build a server to handle api calls, serve our site, and manage our database. We hosted the project on Heroku. We ran into some challenges when trying to build the API due to the CORS security issue. However with the help of mentors and a bit of stack exchange, we were able to get it up and running. We also struggled with edge case testing. During certain calls, our server would breakdown. However, I am proud of the final product as it is intuitive and easy to use.
Next Steps
We want to make sure that our solution really does center around those who need it the most. The only way to do that is a lot of end customer interviews and a lot of iterative prototypes. We hope our project really is capable of creating an impact, and would love to keep contributing to the project.
Built With
css
html
python
sqlalchemy
typescript
Try it out
wewecode.herokuapp.com
marketplace.visualstudio.com | WeWe Code | Building a Pair Programming Community for New Coders to build Personal Projects | ['duttar18 Dutta'] | [] | ['css', 'html', 'python', 'sqlalchemy', 'typescript'] | 15 |
10,370 | https://devpost.com/software/initium | initium
Hello World! This extension is meant as a starting point to extensions in VSCode.
To get started, select the language you wish to develop in and Initium would recommend a set of extensions to make your experience easier. The list of extensions will be actively maintained by the community. Please refer to the contributing guides below to recommend your favorite extensions.
Happy Coding!!!
Inspiration
In the previous semester, we took distributed systems that involved a lot of setups, and following them along was a bit difficult (especially beginners). The main reason why people choose to not take the course is because of how overwhelming the setup and debugging process can be.
Learning
We have been using VSCode for a while now but this was our first hands-on experience on learning VSCode works internally and how the extensions we have come to love and rely upon are built. Hopefully, our idea acts as a stepping stone to help other students such as ourselves, and bring down the scary walls that stop students from a non-CS background from learning how to code.
Challenges
Currently, we have selected top extensions and extensions we personally use. However, there are a lot of extensions and languages in the VSCode marketplace which might go under the radar. To solve this challenge, we are open-sourcing the project so that other developers can also contribute to the list and add/remove extensions and languages. We got the inspiration from GitHub's awesome lists.
Features
Initium provides an initial dashboard which has five categories:
Essentials
: This section installs three extensions by default -> GitLens, -> Code Spell Checker, -> TODO Highlight
Python
: This section shows recommended extensions for Python projects but doesn't install them by default. Our current recommendations are -> Python, -> Code Runner, -> Linter
Javascript
: This section shows recommended extensions for Javascript projects but doesn't install them by default. Our current recommendations are -> Quokka.js, -> ESLint, -> Prettier
Potpourri
: This section shows some miscellaneous extensions but doesn't install them by default. Our current recommendations are -> Bookmarks, -> Bracket Pair Colorizer
Advanced
: This section shows some advanced extensions but doesn't install them by default. Our current recommendations are -> Regex Previewer, -> REST Client
The video can be found here
Recommendation File Format:
{
"language name": {
"extensions": [
{
"displayName": "ESLint",
"description": "Integrates ESLint JavaScript into VS Code.",
"installID": "dbaeumer.vscode-eslint",
"publisher": "dbaeumer"
},
]
}
}
Contribution Guide
To contribute, you can edit the
recommendation.json
file in the format specified above and raise a PR for the same.
Future Updates
Adding more language support
We plan on creating the HTML content dynamically by adding more keys in the recommendation file.
Add version support so that it is similar to how package.json works
Export the list of packages to make it easier for instructors to share the settings and extensions they feel would make the most sense.
Add packages based on the proficiency level of the user/student to help match their needs
Built With
javascript
Try it out
github.com
marketplace.visualstudio.com | initium | This extension is meant as a starting point to extensions in VSCode. | ['Piyali Banerjee', 'Anirudh Sridhar'] | [] | ['javascript'] | 16 |
10,370 | https://devpost.com/software/stack-overflow-search-2bxy0w | Prototype markdown / formatting support
Answers with labelling
Support for other languages
Collapsible cards
Inspiration
I remember when I first started developing (and right now as well), a large part was spent on trying to resolve various errors in the code, along with a lot of information not learned in school or books. StackOverflow is an excellent resource in doing that. Although just relying on StackOverflow without thoroughly understanding what's happening may lead to problems, I believe for newer developers it is an (near-)essential resource to save frustration and keep their interest invested. So, I desired to build a tool to make it easier for newer developers to aggregate search queries / questions.
What it does
A command is added such that, after running the code, any errors that occur are parsed / cleaned into relevant search keywords. These search criterion will then be used to query the StackExchange API, which then displays all questions (not only one question and answer) that are relevant on a compact and interactive interface.
How I built it
The extension command when run will:
Grab error messages from the terminal, while detecting programming language (vs Diagnostics, more on this later)
Runs a regular expression to pattern match (and ensures only the latest compilation is considered)
Extracts the matching patterns from the regex and filters out some characters / patterns which make the search hard to find data (i.e. code from the standard *ibrary's source, especially with templating)
Separates them (space or special character delimited) into an array of strings
Takes the first k strings and concatenates them as search terms. Experimenting on k but later on thinking to have an algorithm for it
Queries StackExchange REST API, and retrieves all questions and answers
Constructs an interactive webview with the dynamic response data through generation of static HTML and inlined javascript
Challenges I ran into
Retrieving error messages: Initially thought to read the terminal output / or listen to it, but that provided to be difficult. Also considered using Diagnostics (would be best in hindsight). Reason it was implemented through reading the terminal output was for flexibility for detecting custom error patterns, possibly even some non-compile time ones. Only later on realized the difficulties and issues that would occur with it. For retrieving the terminal output, unfortunately the proper API call (onDidWriteTerminalData) is only a Proposed API so will be only compatible with Insider only. Current workaround is utilizing a temporary clipboard. (Insight of using clipboard from
https://github.com/mikekwright/vscode-terminal-capture/blob/master/src/extension.ts
)
Search query: There were a lot of uncommon search / question terms / characters which resulted in poor search quality. In the end decided to filter them out, along with splitting the search queries and only taking the first k words. More words = more accuracy but less or no results, less words = lots of results but low accuracy. For now it's hardcoded, but believe if have more time can develop an algorithm to find the optimal return point (along with taking throttling API calls into account)
Fetching from the StackExchange API: Initially, I was thinking of just using web crawling to grab all the HTML then loading it in a WebView. However, this will fetch much more than necessary and isn't the proper way to do it, and will encounter various Captcha issues as well. Another consideration for this challenge was using an iframe workaround. However, it isn't very reliable and may encounter compatibility issues. Thus, I decided to learn Stack Exchange's REST API and make full use of it.
UI: There were issues creating an interactive WebView with dynamic data. There are many excellent and clean ways to do it, but in the end due to limited time, made a hacky pseudo-javascript generator, and just passed the html with the generated inline javascript to the webview.
Accomplishments that I'm proud of
Learning about the various API calls
Got a functional minimum viable product out in limited timeframe
Solved various challenges encountered (although very hacky, but it's a hackathon)
What I learned
StackExchange API
VSCode API
TypeScript basics
What's next for Stack-Overflow-Search
What I consider in order of priority:
If more people are interested, cleaning up / modularizing the code. Maybe try generating a react app for the webview
Consider using Diagnostics instead
More accurate search. Need to define an algorithm / metric for search accuracy, was first considering binary search / multiple API calls throttled to a depth, but too many may cause slowdown. Considering multiple async calls starting at different pivot positions (see comments for TODO)
Other engines (google search, etc) implementation
Can consider using translation APIs (though have to research the accuracy first)
Built With
typescript
Try it out
github.com | Stack-Overflow-Search | Searches stackoverflow / stackexchange API for errors | ['Tony Zhang'] | [] | ['typescript'] | 17 |
10,370 | https://devpost.com/software/codescope | GIF
Code Scope in action
Inspiration
Recently I've been teaching my sister, who is in High School, coding. Sometimes when reading code, there will be keywords and functions whose meanings and use aren't always clear. I wanted to make something to allow people new to coding to quickly learn what means what.
What it does
This VS Code extension allows users to select a function name or keyword. There, the user can do
Shift+Cmd+P
then type in
Scope It
. It will then redirect users to documentation or more information about the word they selected.
What I learned
I had never built or published a VS Code extension before. I learned some things about the VS Code API and how the publishing process works. I hope to build more extension in the future with what I have learned.
What's next for Code Scope
Currently the only supported language is Python. In the future, I hope to bring support to other languages like Java, Javascript, and Swift.
Built With
javascript
node.js
Try it out
github.com
marketplace.visualstudio.com | Code Scope | A tool to help new developers understand the code they read | ['Zain Ali'] | [] | ['javascript', 'node.js'] | 18 |
10,370 | https://devpost.com/software/blockvscode | BlockVSCode
Matthew Lee, Grade 12
Inspiration
Scratch and other visual based programming languages enjoy great popularity at the K-12 CS education level. Despite this, my peers and I have found that the skills of working with Scratch's IDE don't translate well into programming at a more professional level.
What it does
BlockVSCode allows any student to use Visual Studio Code as a tool to code at the beginner level. Users can interact visually with the extension; they can also view the corresponding "Javascript" code.
How I built it
I used the Visual Studio Code Extensions tutorial to learn how to use Webview. I used a library called React-Blockly to implement the block code aspect of the extension.
Challenges I ran into
The React app was difficult to manipulate and I often had trouble rendering the extension.
Accomplishments that I'm proud of
I'm proud to have gone through the process of making and VSCode extension and look forwards to making more.
What I learned
I learned that it is difficult to integrate a web framework like React with VSCode extensions.
What's next for BlockVSCode
GitHub integration: share code with others!
Built With
node.js
vscode
Try it out
github.com | BlockVSCode | A VSCode Extension for directly programming with block code. | [] | [] | ['node.js', 'vscode'] | 19 |
10,370 | https://devpost.com/software/java-data-structure-vscode-vizualizer | Motivation and Use Case
Coding complex data structures is difficult, especially due to the lack of visuals. To make learning data structures and algorithms easier, this extension visualizes data structures before and after they are manipulated. Extension currently only supports Java.
Use case: As a beginner in data structures, I want to write a method to reverse a linked list or perform in order search on a BST. I want to visualize the data structure I’m operating on.
Why?
Coding Java is in english, which may be difficult for those who do not know english well. Visuals serve as a universal language. This extension will lower the barrier for learning how to code methods that operate on classic data structures. This will allow a beginner programmer to learn how to work with these data structures faster.
Although most software engineers don’t use these data structures, the data structures are fundamental to computer science and many university computer science classes teach them.
Progress
This project is not complete yet; some parts have not been coded up.
Completed
Implemented Java method to convert LinkedList to JSON adjacency list representation. JSON file is written to disk.
Create example LinkedListNode and Runner classes
Starter code from
vscode-sample-webview
will visualize image in WebView window
To Be Implemented for Minimum Viable Product
Write the python script that uses the python interface to graphviz to render a png image of data structure
On User command palette execution in VSCode, run python script from extension.ts and open webviews of images. Implementing by changing image file name in extension.ts from sample code
Make available to VSCode Extension Store
Try it out
github.com | Java Data Structure VSCode Visualizer | Visualize data structures written in Java within VSCode. | ['Eric Li'] | [] | [] | 20 |
10,370 | https://devpost.com/software/pybin | Ending output from my extension
GIF
Gif representation of how it is used
Inspiration
I worked as a STEM Instructor for 2 years for elementary aged students and this project was geared towards the classroom setting of teaching a new technology to children.
What it does
The extension provides easy to remember snippets to provide an example and correct format for python functions, variables and explanations of how they work.
How I built it
Made with a little bit of node.js
Challenges I ran into
Looking up how to format and make the extension work on my local host, was first time making an extension.
Accomplishments that I'm proud of
That it actually works and that I have the ability to expand this extension
What I learned
Extensions are powerful and can be used to fast track learning by cutting to the chase to the real learning and applying straight away what to learn.
What's next for Pybin
Add more examples, larger code snippets to introduce data structures and possibly games.
Built With
javascript
node.js
python
Try it out
github.com | Pybin | Supplemental snippets for kids trying to learn Python. | ['Ethan Medrano'] | [] | ['javascript', 'node.js', 'python'] | 21 |
10,370 | https://devpost.com/software/visualize-control-flow | GIF
This extension allows you to generate a control flow diagram for your current file.
Visualize Control Flow
Understanding code is tough. Nested conditionals, loops, recursion -- the abstraction can be hard to visualize. This extension generates a control flow diagram to help students visualize their code.
Using this extension, you can generate a diagram that shows the control flow of your code. This is great particularly for students to see their code's logic in a diagram. We use the UML Activity Diagram format, making these diagrams easy to view and understand. Currently supports visualizing control flow of Python code. Actively developed by
@evank28
and
@AronZeng
as part of #VSCodeHackathon.
Built With
python
typescript
vscode
Try it out
github.com | Visualize Control Flow | Understanding code is tough. Nested conditionals, loops, recursion -- the abstraction can be hard to visualize. This extension generates a control flow diagram to help students visualize their code. | ['AronZeng', 'Evan Kanter'] | [] | ['python', 'typescript', 'vscode'] | 22 |
10,370 | https://devpost.com/software/stack-help | Inspiration
https://marketplace.visualstudio.com/items?itemName=Arnav.stackhelper
The inspiration came from something that I wish existed and was well supported. I wish that I could find answers to my errors without spending time running code, searching for answers that could take hours of valuable time. I know that I was not the only programmer that has this issue. Beginning Programmers and Veteran Programmers alike have this issue as well. This could save programmers that are new to programming to easily find errors without having to search on Google for the right answer. If I was a beginner, I would need this extension. This extension could have saved me and save others from their valuable programming time, and help beginners learn as well to find the best answers on Stack Overflow.
What it does
This extension has 5 specific commands that can be used.
Search StackOverflow
Find Help with Errors On Stack Overflow
Enable a Line by Line Error Highlighter
Disable the Line by Line Error Highlighter
Search in Stack
Search StackOverflow Provide an Input Box for the user to type something that they want to search on Stack Overflow. It then opens related searches in the default Web Browser in Stack Overflow's website.
Find Help with Errors On Stack Overflow reads the debug console to find errors. It then suggests the user to choose an error to search Stack Overflow and then opens a link to the default Web Browser.
Enable a Line by Line Error Highlighter finds errors while a user is typing and shows the error in realtime without running code. This works for any language!
Disable the Line by Line Error Highlighter disables the error highlighter if a user does not need it anymore.
Search in Stack uses Stack Exchanges API to find relevant articles. The user highlights text that they want to search, right-click, and enable the extension or use a keyboard shortcut. It then provides a list of Stack Overflow articles and shows which articles have answers and which do not and show the upvotes/downvotes of the question along with the title and author.
How I built it
I used the starter extension code by using the yo npm module and wrote the extension in TypeScript. I used the VSCode API and Stack Exchange API to bring the extension to life.
Challenges I ran into
This was my first time making extensions and I hadn't used VSCode many times. So I encountered many issues but overcame them. A very big issue I had was using Node.js and npm. I had encountered many issues as my versions were outdated and some functions deprecated. I overcame this by searching solutions on Stack Overflow and found my answer. Another challenge I had was running the extension, I would get error messages that would prevent my program to run. I also had the error to figure out how to use the Stack Exchange API, I didn't have much experience with this type of API, but eventually overcame it.
Accomplishments that I'm proud of
Running my first VSCode extension!
Becoming familiar with VSCode and how extensions work.
Bringing an idea that I've always wanted and made it a reality.
What I learned
I learned so many things. I learned:
How VSCode can make programming fast and efficient
How VSCode extensions work
How to make a VSCode extension
How Stack Exchange API works
How APIs work
What's next for Stack Help
Publish to VSCode Marketplace
Add more features
Make Stack Overflow available without leaving VSCode (Use WebView API)
Use Machine Learning to help find answers faster and rate the answers for a particular question a user had to make the Extension efficient and seamless.
Make errors easier to understand ie. implement Help50 from Harvard.
Built With
node.js
stack-exchange-api
stack-overflow
typescript
vscode-api
Try it out
github.com
marketplace.visualstudio.com | Stack Help | A multi extension that uses Stack Exchange API and VSCode API to find answers and help on Stack Overflow, additional features include error highlighting while writing code. Supports all languages! | ['Arnav Shah'] | [] | ['node.js', 'stack-exchange-api', 'stack-overflow', 'typescript', 'vscode-api'] | 23 |
10,370 | https://devpost.com/software/productivity-tracker-jwp179 | Inspiration
I wanted to be more productive.
What it does
It tracks how many characters you type per hour.
How I built it
I wrote code.
Challenges I ran into
The fact that I only had three hours.
Accomplishments that I'm proud of
I did or didn't do it in three hours. Currently posting so I have more time to work.
What I learned
How to make a VS Code Extension.
What's next for Productivity Tracker
Unsure if I will continue working on it. I just wanted to post something.
Built With
charts.js
javascript
node.js
Try it out
marketplace.visualstudio.com | Productivity Tracker | Get a visual understand of how productive you are inside of VSCode by seeing how many characters you type every hour. | ['https://www.loom.com/share/81cd359c388b44e39b4dd1921861e078', 'Justin Fernald'] | [] | ['charts.js', 'javascript', 'node.js'] | 24 |
10,370 | https://devpost.com/software/vs-babelfish | Inspiration
Less than 20% of the world speak English.
Yet, the current landscape of programming and software development is largely centered around the English language. I'm not just talking about programming constructs like "for", "if", and "else", but rather, the large body of documentation for many third-party libraries that are written solely in English. Only few large companies have the resources to translate their documentation into different languages, which leaves thousands of other libraries (many built by individuals or small groups) inaccessible to non-native English speakers.
Imagine if you were a newcomer to programming and saw that the documentation for a library you want to use is in a language you don't understand. It might just turn you away.
BabelFish (inspired by the multilingual fish from the Hitchhiker's Guide to the Galaxy) aims to tackle this problem, making software development more inclusive and accessible to everyone.
What it does
BabelFish analyzes source files for documentation comments, detects their language, and automatically translates them into the user's native language if it is in a different language.
How I built it
I used Typescript, the VSCode CodeLens API, as well as Azure's Cognitive Services API for the language detection and translation
Accomplishments I'm proud of
I was really happy when I managed to develop a method of parsing the comments in JS files and determining the appropriate lines to translate
What I learned
I didn't have any knowledge of the VSCode API or Azure Cognitive Services before beginning this hackathon so it was quite challenging to pick them up while developing the extension at the same time. However, having now gained a much deeper understanding of these 2 topics, it's exciting that I've managed to develop an extension for the text editor that I use everyday!
What's next for VS BabelFish
There are still some small issues with the extension that I will fix (e.g. it shouldn't translate argument names after @params in the comments)
Currently, the extension only supports Javascript files. I would like to expand it to support multiple additional languages.
I would also like to investigate how to improve the aesthetics and ease of use of the extension as I understand that the screen may get cluttered with translations when there many comments in a single file.
Built With
azure
cognitive-services
typescript
vscode
Try it out
marketplace.visualstudio.com | BabelFish | Breaking down language barriers in software development | ['Isaac Ong'] | [] | ['azure', 'cognitive-services', 'typescript', 'vscode'] | 25 |
10,370 | https://devpost.com/software/vscode-extension-learnproglang | This extension for Visual Studio Code is meant to help new programmers find useful resources quickly.
Built With
typescript
vscode-api
Try it out
github.com | VSCode-Extension-LearnProgLang | Helping new programmers find useful resources quickly. | ['Dalton Winans-Pruitt', 'Shailendra Jakhar'] | [] | ['typescript', 'vscode-api'] | 26 |
10,370 | https://devpost.com/software/polyglot-hello-world | Inspiration
There are countless ways to install a programming language on your system. Beginners are struggling to find the best solution, but oftentimes, all they need is one clear tutorial.
Beginners should not be struggling with these questions:
Do I need to use
nvm
or
node-v12.18.1-x64.msi
to install
Node.js
?
Do I need to install Python 2 or Python 3? Should I use Anaconda?
What's the difference between OpenJDK and Oracle Java? Do I need Java 8 or 11?
I wanted to provide a curated list of opinionated installation tutorials for beginners, so they can focus on learning and not wasting time on their setups.
What it does
Polyglot Hello World provides a simple interface for beginners to find simple installation guide for a programming language of their choice.
How I built it
VSCode API allows extensions to create persistent status bar items. Polyglot Hello World extension provides a clickable button in the status bar which provides links to each programming language's installation guide & hello world tutorial.
Challenges I ran into
There are support for only three languages: Python, Javascript and Rust. I would love to provide information about other popular languages like Java and C, but I don't know any beginner friendly way to setup VSCode for those languages. I usually depend on VSCode dev containers for those situations, but I thought beginners would have hard time understanding how to manage Docker containers in their systems.
Accomplishments that I'm proud of
My initial plan was to build a Heroku integration for VSCode. After having conversation with fellow hackers, I acknowledged that Heroku integration is probably not an extension a beginner would want to install. The community was really helpful during the initial idea pitching process, and getting feedback from people outside of my team was a great experience. I think the discussion I had with MLH hackers is more satisfying than actual implementation process this time.
What I learned
Although VSCode is my code editor of choice, this was my first time learning & using VSCode API. I am glad that I now know how flexible the editor is, and it is exciting how I can easily add functionalities to my tools.
VSCode extensions API reminds me of emacs experience, but with typescript. I have tried to use emacs as my daily text editor few years ago, and I loved the flexibility & customizability of the program. However, emacs was extremely difficult to configure it just the way I wanted it to be, so I switched over to VSCode for the developer experience where everything "just works". It is funny how I am amused by VSCode's customizability again.
What's next for Polyglot Hello World
Built With
node.js
typescript
Try it out
github.com
marketplace.visualstudio.com | Polyglot Hello World | Installation Guides & Hello World Examples for Popular Programming Languages | ['Donghyeon Kim'] | [] | ['node.js', 'typescript'] | 27 |
10,370 | https://devpost.com/software/bootsnip-1po90q | bootsnip README
This is the README for your extension "bootsnip". After writing up a brief description, we recommend including the following sections.
Features
Describe specific features of your extension including screenshots of your extension in action. Image paths are relative to this README file.
For example if there is an image subfolder under your extension project workspace:
Tip: Many popular extensions utilize animations. This is an excellent way to show off your extension! We recommend short, focused animations that are easy to follow.
Requirements
If you have any requirements or dependencies, add a section describing those and how to install and configure them.
Extension Settings
Include if your extension adds any VS Code settings through the
contributes.configuration
extension point.
For example:
This extension contributes the following settings:
myExtension.enable
: enable/disable this extension
myExtension.thing
: set to
blah
to do something
Known Issues
Calling out known issues can help limit users opening duplicate issues against your extension.
Release Notes
Users appreciate release notes as you update your extension.
1.0.0
Initial release of ...
1.0.1
Fixed issue #.
1.1.0
Added features X, Y, and Z.
Working with Markdown
Note:
You can author your README using Visual Studio Code. Here are some useful editor keyboard shortcuts:
Split the editor (
Cmd+\
on macOS or
Ctrl+\
on Windows and Linux)
Toggle preview (
Shift+CMD+V
on macOS or
Shift+Ctrl+V
on Windows and Linux)
Press
Ctrl+Space
(Windows, Linux) or
Cmd+Space
(macOS) to see a list of Markdown snippets
For more information
Visual Studio Code's Markdown Support
Markdown Syntax Reference
Enjoy!
Built With
node.js
yeoman
Try it out
github.com
marketplace.visualstudio.com | bootsnip | Bootstrap snippet creator (https://marketplace.visualstudio.com/items?itemName=kevroi.bootsnip) | ['https://marketplace.visualstudio.com/items?itemName=kevroi.bootsnip', 'Kevin Roice'] | [] | ['node.js', 'yeoman'] | 28 |
10,370 | https://devpost.com/software/next-vscode | nEXT Extension pack
nEXT-snippets in marketplace
Creating Custom code snippets
Using yeoman to create extension templates
Package.json file
Publishing the extension to Marketplace using vsce
In the VS Code marketplace!
nEXT-vscode
This is an extension which CS beginners can use it to learn ML and Data Science!
Intro
nEXT is a solo-made project which is mainly focussed on building extension for those who start their Data Science journey ahead. It consists of 8 extensions (mainly focussed on Python3 and not IPYNB) which the user can immediately jump and start learning the basics!
This extension pack contains two self-made extensions (nEXT-snippets, nEXT-edu). I wanted to make it as a ext-pack so that beginners can relieve tension for installing each at a time. You can install separate extensions from the list but those two are mandatory and important!
Inspiration
I'm a ML enthusiast and I like to work with Data Science. So, I spent a lot of time trying to learn the basics! To avoid that burden, I decided to create a extension pack which includes all the VS Code pre-requirements to work with Python for Data Science. That's how I got the idea of making the extension "nEXT"
Technology used
I used yeoman to create a basic extension template (both for snippets and extensions). Then I used my old ML codes to take the snippets and create basic commands to import them. Finally, I learned and created an Azure DevOps account to review and publish the extension using vsce tool.
Challenges I faced
I didn't know that VS Code extensions can be created at the beginning. Creating an extension is a challenging one, because I had to think what the user has to code, the various scenarios and the basic needs. I had to work on making extensions, rethink about the needs, update the version again and again! But that is exciting!
What I learned
Creating a basic VS Code extension and extension pack
Creating custom Code snippets
Publishing the extension pack to the VS Code Marketplace using vsce
Theory about JSON packages and version control
How to spend time efficiently in making a software!
What I'm Proud Of
Earlier I used to think of how extensions work and co-operate! Now, I learned the basics and I'm confident that I can create and publish extensions to benefit the users who are new to CS.
What's next?
Since I learned about creating VS Code extensions, I'll now try to create some to help for the beginners who are interested to learn about technology by contributing to Open Source and publishing it!
Built With
github
json
npm
vsce
vscode
yeoman
Try it out
github.com
marketplace.visualstudio.com | nEXT | This is an extension pack (along with self-made ones) which CS beginners can use it to learn basics of ML and Data Science! | ['Aadhitya A'] | [] | ['github', 'json', 'npm', 'vsce', 'vscode', 'yeoman'] | 29 |
10,370 | https://devpost.com/software/vscode-learnc | GIF
Poster
learnc - Description
With the help of this Extension, you can easily learn the C language. I hope you like it. This is a prototype. the final extension will be published on 4th July 2020.
Features
Create your folder with .c extension.
Start Learing with #allcmd
Use all command according to your need.
All Command
C-Documnetation --------- #cdoc
C-syntax ---------------- #csyntax
C-comments -------------- #ccomment
C-datatypes ------------- #cdatatypes
C-if -------------------- #cif
C-if..else -------------- #cifelse
C-if...else ladder ------ #cifelseladder
C-switch Statement ------ #cswitch
C-for....loop ----------- #cforloop
C While loop ------------ #cwhileloop
Data Structure Documentation: #csearchandsort
Selection Sort: #cselectionsort
Insertion Sort: #cinsertionsort
Bubble Sort: #cbubblesort
Merge Sort: #cmergesort
Linear Search: #clinearsearch
Binary Search: #cbinarysearch"
Maths
Addition of two number: #csum
Substraction oof two number: #csub
Multiplication of two number: #cmul
Divison of two number: #cdiv
Write your first program in C
Type -> #cfirstp
Then Follow the steps:
-> #step1 #step2 #step3
Type #aboutdev to contact developer.
Requirements
The 'C/C++' extension is recommended for this file type. C gcc Complier.
1.0.0
The initial release of learnc
Built With
https://marketplace.visualstudio.com/items?itemname=yash.learnc
Try it out
github.com
marketplace.visualstudio.com | VSCode-LearnC Submission by Yash Chauhan | I'm solving a problem that most of beginners found while getting started with code to solve this via VS code extension. I have build an extension that runs on command to guide the beginners to code. | ['Yash Chauhan'] | [] | ['https://marketplace.visualstudio.com/items?itemname=yash.learnc'] | 30 |
10,370 | https://devpost.com/software/what-is | GIF
What is package.json?
What is
it
At this VS Code Hackathon, I created an extension called
What is
that helps beginner programmers become familiar with certain auto-generated project files that may seem confusing and daunting at first. For instance, when you create a React project for the first time, you may be wondering, what is package.json? Or when you are browsing a GitHub repo for the first time, you may wonder, what is a README file?
Background
As an avid programmer, I like to understand how all the files work together and what all the different language syntax means in a project. Since some projects are just too difficult and complicated to get started manually, programmers tend to use some pre-configured code and settings files. However, starting a project with dozens of files already created, and sometimes in languages that you may not even know, it can be daunting and confusing. That's why I find it hard to jump right into a project when there is so much starter code and so many auto-generated files that I don't even understand. The
What is
extension was created so that other new programmers can learn briefly about these files and feel less overwhelmed when starting a new project.
How it works
The file options currently supported are the following:
package.json
package-lock.json
README.md
.gitignore
robots.txt
When one of these files appears in your project, you will have the option to learn more about the file by right-clicking on it and selecting the feature
What is
. A brief description of the file will then be shown in a message. This extension is a quick, easy way for new programmers to become more comfortable with their projects.
How I built it
This extension was built using the VS Code Extension template for TypeScript. The extension contains a single command,
What is
, that appears in the menu when a file is right-clicked. When the command is selected, a function is run that parses the file name to determine which of the file options it is. Then a description of the file is retrieved from a predefined mapping. Finally, a message is shown to the user with the description of the file.
Challenges I ran into
One challenge I ran into was figuring out how to determine what type of file the user clicked on. I wanted to make a single, universal command
What is
to increase readability and improve the user experience. Thus, the determination of the file type would need to be done on the backend. However, there is no method to get just the file name as opposed to the whole path of the file that was clicked. So instead, I decided to use a handy tool in JavaScript,
endsWith()
to check which of the file options the path ended with.
Additionally, I ran into a lot of unfamiliar errors since this was my first time using TypeScript. I had an issue with declaring types in a nested object and didn't realize that I had to create interfaces and abstract types. Through browsing the web, I was able to find the right syntax.
Another challenge was just navigating and learning the VS Code Extension API. This was my first time building a VS Code extension and at times I was confused about what to put where in the package.json file. Some commands needed to be in the activationEvents and the contributes commands, and a separate explorer menu. But, as I worked through the project, I caught on quickly and feel more prepared to build a new extension in the future.
Accomplishments that I'm proud of
I am proud of myself for completing this project. I got stuck a lot along the way and was feeling the time pressure towards the end. I had a lot of good ideas, but was only able to build something simple. Nonetheless, I learned a lot, I had fun, and I am excited to continue building in the future.
What I learned
I learned how to build a VS Code extension, navigate the API, work with a package.json file, and publish my extension to the VS Code Extension Marketplace. I also got to work with TypeScript for the first time.
What's next for What is
In future updates, I would like to add support for more types of files that beginner programmers often find confusing as well as maybe generalizing the support to file types/languages rather than specific file names. For instance, if someone was coding in Python for the first time, they could right-click on a
.py
file, select
What is
, and read a brief description about Python.
Built With
json
typescript
Try it out
marketplace.visualstudio.com | What is | Feature to help beginner programmers become familiar with common (and confusing) project files | ['Amy Weitzman'] | [] | ['json', 'typescript'] | 31 |
10,370 | https://devpost.com/software/python-inline-repl | GIF
use variable
GIF
use function
GIF
re-run
GIF
exercise
Python-Inline-Repl
Inspired by the inline-repl feature from
Simple GHC (Haskell) Integration for VSCode
, the extension python-inline-repl
can run Python codes within comments and preserve the result in your file.
Advantages for learners:
No need to open another tab for running/showing the code
Results are saved in the file so that you know what examples you have tried
Allows the instructors to create exercises easily by leaving results as specifications (see the GIF)
Further allows students to only focus on one file. No README, no write-up
Also allows students to easily compare their output against the output from instructors by putting two comment blocks together
Built With
typescript
Try it out
github.com | python-inline-repl | A light-weight in-line Python evaluator that allows students to try out their code within comments. | ['Zijie Zhao'] | [] | ['typescript'] | 32 |
10,370 | https://devpost.com/software/doc-doctor | Demo ScreenShot
Doc Doctor
Docstring grammar checks
Features
Grammar check
Checking grammar of the docstring.
Demo
Installation
API key
Go to
https://www.grammarbot.io/
, register an account.
Save the API key to settings.json for doc_doctor.key
Inspiration
Understanding how the code works is very important. This extension will check for grammar mistakes so that typos and such mistakes can be fixed and the code will be comprehensible.
What we learned
We learned how to make VS Code extensions and publish them.
How we built
We used the GrammarBot API to build it.
Challenges we faced
We were facing troubles in fetching API and connecting to it.
Built With
grammarbot
javascript
Try it out
github.com | Doc-Doctor | Doc string grammar check | ['Zijing Zhang'] | [] | ['grammarbot', 'javascript'] | 33 |
10,370 | https://devpost.com/software/easyapi | Extension result
Inspiration
There are multiple experiences that inspired me to make this extension. I have tried my best to write about them in brief.
When I started using APIs, I tried following online tutorials but most of the APIs these videos were either not available or were not free. I also have been running into problems while looking for a particular API that suits my purpose. Even at hackathons, I have seen a lot of developers using APIs to develop their product so I believe that it would be really helpful to have access to the different APIs that are available.
Yesterday, my friend told me about Robinhood's API that would allow developers to build their own trading applications. I also came across the Spotify API that even allows one to integrate Spotify Analytics. I am sure that there are many such APIs available and it is important for developers to know about them.
What it does
It is an extension which calls an API to get different APIs associated with the category user wants. It prompts the user to enter the API category in an input box. The APIs related to that category are scraped and returned by the API and presented in a json file by the extension. The user can also choose the file name using the input box that shows up. Sometimes the data loading process takes a lot of time and that leads to a "Please try again" message. Trying the same commands again would load the data properly. Example: If the user wants to use Twilio APIs then a simple Twilio Phone search would provide the user with a number of different APIs by Twilio. The user can also search for other APIs like AWS APIs, Azure APIs and many more.
How I built it
I built it by first scraping web data using python. I scraped data and built a REST API using Flask that serves that data. I then hosted that on Heroku and called that information in the extension. The extension creates a new file and stores the information there. It also contains the link to the API's documentation which could help a developer learn more about the API.
Challenges I ran into
The major challenge was when I was trying to scrape the data as I had to make sure that the result is returned quickly and the most important chunks of data are returned. I believe that just presenting the API with its description wouldn't have helped so I had to scrape the url of the API's documentation which was nested on different pages. I had to follow those pages to scrape the url. I later ran into problems with the API taking a lot of time in returning data which was resolved by reducing the manipulation my API code had to do.
What I learned
I learnt how scraping could come handy in increasing the access people have to different resources viable online. On the technical side, I learnt how to make API calls inside a Visual Code Extension.
What's Next
I hope to make it easier for developers to integrate APIs in their applications using this extension. Different APIs have different endpoints but I hope to use this extension in helping the user to integrate an API of their choice. I also hope to get rid of data loading timeout problems soon.
Built With
flask
javascript
python
Try it out
marketplace.visualstudio.com | EasyAPI | Explore different APIs suited to your needs | ['Himanshu Jain'] | [] | ['flask', 'javascript', 'python'] | 34 |
10,370 | https://devpost.com/software/find-a-peaceful-protest-fi9ka2 | Inspiration
When I watched the news, I noticed how many protests around the world support different communities and movements. However, I also noticed many protests had violence, which often was not related to the movement itself. Violence is a reason many people who want to support their movement don’t attend these protests. For this hackathon, I decided to build something to help people connect and find peaceful protests.
What it does
Find a Peaceful Protest is an interactive map with user-generated content. It allows users to add new protests and find existing ones. It also has a review system where users can add their own account of the protest and images of the protest.
To reduce the amount of fake protests and reviews, Find A Peaceful Protest has a smart system where it calculates your reliability. The more reliable you are, the greater the impact is of your new protest or review.
Additionally, a color-coded map navigation system makes it easy to see which protests are right for you. Markers on the map are color-coded according to how peaceful the protest is rated, and the opacity of markers are set according to how reliable it is.
How I built it
For the map, I used Leaflet.js for the user interface, OpenStreetMap for the map content, and ESRI for geocoding and reverse geocoding. For the backend, I used Firebase Realtime Database to store data and Firebase Storage for image storage. For the general structure of the website, I used HTML/CSS and JavaScript, as well as W3.CSS. I used Firebase Hosting to host my site.
Challenges I ran into
I was not familiar with the Leaflet.js library when starting the project, so it took some time to understand and learn it. Additionally, I had some problems with getting an image URL from Firebase Storage, but eventually figured it out after reading the documentation.
Accomplishments that I'm proud of
I am proud of figuring out how to implement the Leaflet.js map without prior experience in using the library.
What I learned
I learned a lot about Leaflet.js, as well as Geocoding and accessing geolocation in the browser.
What's next for Find A Peaceful Protest
I plan to implement an account system for Find A Peaceful Protest to further increase reliability of data and repeated reviews from the same person.
Built With
esri
firebase
html5
leaflet.js
openstreetmap
Try it out
github.com
find-a-peaceful-protest.web.app | Find A Peaceful Protest | Not attending protests because of violence? Find a Peaceful Protest today. | ['Benjamin Man'] | [] | ['esri', 'firebase', 'html5', 'leaflet.js', 'openstreetmap'] | 35 |
10,370 | https://devpost.com/software/learn2code-coderscommune | Some Coding
Some More Coding
Home Page
Contact
Ressources
GitHub Files
Inspiration
Our goal is to help create a community of aspiring young coders and give them the tools they need to achieve their dreams. By fostering the ambition of brilliant young minds and immersing them in the world of coding, we can help them become the future leaders of tomorrow.
What It Does
Our belief is that if children are not able to go to school, it is our responsibility to bring the school to them through our E-Learning platform. Our platform acts as a go-to site for those unable to access a conventional education so that they are able to get the resources they need to help them achieve their dreams. While reducing the costs normally associated with educational institutions such as tuition, books, and supplies, Learn2Code is able to work with international governments to adopt this E-Learning system to give children access to the education in coding they deserve.
How We Built It
Using Brackets as a source code editor, we created the website filled with tutorials and games and used CSS for the design. The games were coded using Python in Pycharm and are available to download through the website. There is also the ability for "clients" to get in touch with us to reach out for help.
Challenges We Ran Into
This was our team's first website and we began this with no prior experience in web or game development. Essentially, we learned all the concepts from scratch in order to create the website and games.
Accomplishments That We're Proud Of
We started this competition in order to teach ourselves the concepts of web development and were able to create a wonderful program for our first time.
Built With
bootstrap
brackets
css
dreamweaver
html5
photoshop
pygames
python
Try it out
github.com
learn2codecc.netlify.app | Learn2Code: CodersCommune | One stop resource for those who don't have access to a conventional education to learn and explore their passions in coding through resources and games. | ['WILLIAMS THOTTUNGAL', 'MAJD AL-AARG', 'ALEXANDER MOGHADAM'] | [] | ['bootstrap', 'brackets', 'css', 'dreamweaver', 'html5', 'photoshop', 'pygames', 'python'] | 36 |
10,370 | https://devpost.com/software/whycode | Inspiration
I'm currently studying Computer Science in college and am about to graduate. But as the years of menially studying different data structures, systems designs, and languages have passed by, I've become less interested in coding and don't see any fulfillment in it. I don't see any reason I should be pursuing a field like this besides getting a job that will make lots of money. I don't have the same bright, eye-lit spirit as I did when I saw the Computer Science field for the first time and said: "That's awesome, I want to do that." I've lost motivation to be a coder.
I built this extension to hopefully motivate not just me, but students who are learning Computer Science for the first time as well to make something cool. There is a lot of menial work that software developers have to do in this industry, and it is discouraging to see all those logic and syntax errors pop up when the program runs/compiles. Students are bound to making these errors at least once, so they will feel deterred if they are having difficulty figuring out what is causing the problem. I want this extension to keep all kinds of software developers engaged in what they are doing, especially students so that they can create awesome products just like us hackers.
What it does
At the start of activation, and every 15 minutes, it will send a random motivational message to the user. The user activates the extension by typing Whycode in the text line that appears after hitting Ctrl+Shift+P in the VS Code window.
How I built it
I used VS Code to develop and debug this code. I made two arrays: one for the start motivational message and one for the message sent on intervals because the contexts of each message vary with the amount of time the user has started working. Certain messages are more applicable at the start of work rather than 15 minutes into the work. I essentially kept the starting template the same but changed the callback function in registerCommand().
Challenges I ran into
I took a break from this project but ended up procrastinating on it, and my current disinterest in coding was deterring me from continuing it. Luckily, I wanted to at least demo something to the judges, so that's how I was able to get it done.
Accomplishments that I'm proud of
Making my own VS Code Extension for the first time
What I learned
I'm currently 21 years old, which is an age where people are still trying to figure out their purpose in life. I learned that I don't have to commit to being a coder my whole life, but I can still use the skills I've acquired to change others' lives for the better.
Money or prizes don't bring happiness. While we are currently revolutionizing the way we work in the world by pouring out new technology every day, it's important to always be grateful for the things that we have, the values that we live by today. Knowing these attributes fulfill our lives every day makes us happy.
What's next for Whycode
Allow user configuration for how often you want to be "motivated"
Allow user to deactivate/reactivate Whycode; send a message upon deactivation/reactivation
On detection of errors, encourage the user to figure out what the error might be
Custom motivational messages
Make it a passive extension: no more manually entering "Whycode" to activate
Allow for jokes
For statistical purposes, collect info on the user's current attitude: ask the user if they would like to share how they are feeling about what they are doing and record the info in a database.
Built With
typescript
visual-studio | Whycode | A VS Code extension that maintains a user's motivation to code | ['Christopher Dungo'] | [] | ['typescript', 'visual-studio'] | 37 |
10,370 | https://devpost.com/software/idea-generator-pnqfr8 | Inspiration
The most common question I've been asked when folks first start coding is "... So... What should I do?". I built this extension to answer that question!
What it does
Gives the user a random idea, and base code, at easy and medium difficulty. Hard challenges are given without base code. A user will be given their random challenge/idea, along with a link for more info, base code, or to re-generate (get another idea).
How I built it
I took a few code challenge prompts from:
https://www.linuxtrainingacademy.com/projects/
and set up a new VS Code extension with a QuickPick and a few basic InformationMessages.
Challenges I ran into
Debugging took a little while to get used to, as well as finding the exact functionality I was looking for. With so much offered, there's a bit of a needle-in-a-haystack feeling when trying to find the right tools.
Accomplishments that I'm proud of
This is my first Code extension and I was able to complete a working prototype in a reasonable time! This may be the first hackathon where I get a good night's sleep! :)
What I learned
Lots about Code extensions and the functionality available. It would be a lot of fun to build this extension out further, and I think I may do so when I have the time!
What's next for Idea Generator
Setting up a server -- right now this is a pretty bloated extension (or at least, it would be if I continued to build it out exactly as I have), so next steps would be to get an IG server setup, followed by an 'admin view' where new challenges could be added. Finally, multi-language support, beyond just Javascript, would be great to have!
Built With
generator-code
javascript
vsce
yo
Try it out
marketplace.visualstudio.com | Idea Generator | When starting out, the toughest part is always coming up with a good idea! This extension is designed | ['Will N'] | [] | ['generator-code', 'javascript', 'vsce', 'yo'] | 38 |
10,371 | https://devpost.com/software/grocery-grab | Inspiration
As COVID-19 strikes the nation, grocery stores are struggling to meet shoppers’ demands in the face of a global pandemic. Crowded and inefficient stores can prove potentially deadly for at-risk populations. Businesses are in need of a way to implement a smart shopping experience that prioritizes the safety and optimization of their stores.
This is why we created Grocery Grab, a mobile app that uses augmented reality, pathfinding algorithms, and NCR’s cloud services to provide a quick and contactless shopping experience.
What it does
Lets user make a virtual shopping list based off of a store's product catalog and get each product's location in the store
Generates the shortest path between products using a pathfinding algorithm and a travelling salesman problem heuristic solution, allowing for faster circulation of customers.
Helps the user navigate inside of a store using augmented reality or an interactive map.
Checkout through the app, freeing up long lines, and ensuring germ-free transactions.
Outside of COVID response, Grocery Grab can help retailers reduce labor cost and bring the online experience into the brick and mortar store.
How we implemented NCR's API
The retailer will upload the store's items to the NCR cloud using the Business Service Platform and the Catalog API. Each item has attributes including the name, price, location in the store, and the identifying code. Upon launch, the app will make a call to fetch the entire catalog as well as creating a new cart in the cloud through the NCR Selling Engine. Every time an item is added to the cart, the virtual cart is updated as well. Upon checkout, the Selling Engine calculates the total, processes the customers' payment, and deletes the cart from the cloud.
Challenges we ran into
Creating the (entirely custom) pathfinding algorithm
No one had any experience in augmented reality
Getting familiar with NCR's APIs
Sleep
Accomplishments that we're proud of
Augmented reality
Pathfinding algorithm
Getting the API to work
Good-looking UI
We got a lot done in 36 hours, pretty cool
What's next for Grocery Grab
Implementing the augmented reality into more seamless and interactive technologies such as Google Glass
Develop a system for retailers to manage information in the cloud.
Built With
android-studio
arcore
augmented-reality
java
ncr-bsp
ncr-catalog-api
ncr-cloud
ncr-design-system
ncr-selling-engine
restful-api
Try it out
github.com | Grocery Grab | Reimagining retail shopping with pathfinding, mobile checkout, and Augmented Reality in the COVID era. Our app minimizes interpersonal contact and time in store, ensuring more safe customers. | ['Gary Peng', 'Nicholas Hulston', 'Joe Vitko'] | ['1st Place Overall', 'NCR: Develop a disruptive and innovative solution that solves at least one of NCR’s most significant problems for Banks, Stores, or Restaurants', 'Top 8 Overall'] | ['android-studio', 'arcore', 'augmented-reality', 'java', 'ncr-bsp', 'ncr-catalog-api', 'ncr-cloud', 'ncr-design-system', 'ncr-selling-engine', 'restful-api'] | 0 |
10,371 | https://devpost.com/software/write-noise | Background Music
Comedian's Joke Visualized
Website Converter Page
Inspiration
This project has been a wild ride. Coming into this hackathon with little information as to what we as a group wanted to create, it felt like an impossible task to get any meaningful work done within about the 36 hours. The first three hours were spent on hard brainstorming, splashing our mini-white board with as many ideas that we could think of. Simulation of living without glasses, simulation of colorblindness, a calorie fitness app, a Youtube addiction-curber, a Bridge AI. There were so many problems that we wanted to solve, but nothing stood out for all four of us. Right before dinner time hit, I thought about the incredibly cool animations of the old Windows Media Player had. You know, the swirly, trippy, colorful images that played in sync with you song? I thought that’d be incredibly cool to make. Kurt, though, thought of an even better idea: representing an audio file by a singular image. Not everyone was for this idea, initially, as we kind of thought of it as a joke concept at first. Like, how hard could it be to convert bits to bits? It’ll be easy weekend.
Challenges
Challenges started to arise deep into Friday night though. As we thought about it more, we concluded it was a conflict of whether we wanted the image to be a one-to-one conversion or an artistic representation. On one hand, it would be extremely cool and useful to have an image completely represent a sound. It would be great for encoding information in the physical world and act as “QR code” for sound. On the other hand, the idea of seeing a computer-generated picture and immediately understanding what a song’s tone and vibe was extremely satisfying too. We went to sleep, nervous but excited, with an idea that we knew had a lot of potential.
Process
Saturday morning, we drew up the semblance of a plan. The plan was to convert the song’s raw bit data into the fields of the pixels of the image, and that newly created image would then be multiplied by invertible transformation matrices created dependent on analyses of the audio’s unique characteristics (frequency, amplitude, key, length, etc). We each divided the work by section: Ethan primarily worked on the audio-to-image conversion algorithm, Morris worked on the developing our dynamic website, I worked on the transformations, and Kurt was a helper that greatly contributed to all three. In all three, we had major obstacles that weren’t foreseen.
Ethan developed two algorithms, one that converts a .wav file to an image and one that converts an image back into a .wav file. For the .wav to image conversion, we assumed that the .wav file would be a 16-bit file as that is what is most common. We needed to convert these 16-bit data points into a 32-bit pixel, so we did the following. We broke up bits 2-16 and assigned them to be bits in the RGB values of a pixel. We distributed the bits such that the most significant bits in the input were the most significant bits in the colors. We then padded the rest of the RGB values such that they were each 8 bits long. Next, we used the first bit (signed bit) in the input to determine the alpha value of the pixel. If the bit was positive the alpha was 255 and if negative the alpha was 128. The exact opposite process was used to turn an image back into a .wav file. The algorithms are designed such that if you run a file through one of the algorithms and then use the outputted file in the other algorithm, the final output will be the original file.
I looked at the characteristics of music and how to extract that information from an audio file. I was able to find the average frequency rather easily, as well as the average amplitude. The one obstacle that I faced was the finding the key. I innocently thought that it would be easy converting the song to a MIDI file and have an algorithm analyze the key. It was not. After 5 hours of searching, I came to the sinking conclusion that the conversion could only take place in Python 2.7, when the rest of the project was being written for Python 3.8. While searches of version control with virtualenv gave me hope, we simply didn’t have enough time to implement it. Saddened but not discouraged, I still wanted to overlay two sin waves of the sound file’s unique frequency and amplitude. But because so much time was spent as a group in developing the website and algorithm, these features had to be ultimately cut. Alas, a project made in less than 2 days won’t always go according to plan.
Finale
Morris and Kurt spent Saturday afternoon finding out exactly what kind of website solution we wanted to go through. We as a group had a little experience with web development, let alone dynamic website development. They juggled with the idea of Firebase with Google Cloud, but the ultimate solution was Flask. With a Frankenstein of google searches and snippets of a previous Flask solution that Ethan worked on, at midnight we achieved perfection: a website that could legitimately take a file upload and not die. We were so excited that I think Morris’s scream at 1 AM woke up the whole dorm.
Built With
css
flask
heroku
html5
numpy
python
scipy
Try it out
writenoise.herokuapp.com | Write Noise | We know that sound can be transcribed, but how would a visual representation of audio look? Through our project, we wanted to integrate art and tech to explore how sight and sound can be intertwined. | ['Morris Wan', 'Charlie Liu', 'Mingoose', 'Kurt Hu'] | ['2nd Place Overall', 'Top 8 Overall'] | ['css', 'flask', 'heroku', 'html5', 'numpy', 'python', 'scipy'] | 1 |
10,371 | https://devpost.com/software/crust-ewzfrn | Our Figma Mockups
Dashboard Analytics 1
Dashboard Analytics 3
Inspiration
With more people stuck at home due to COVID-19 pandemic, there has been a surge in demand for food delivery services. Due to this, more and more restaurants are offering home delivery/curbside pickup options. With multiple retail options, restaurants are finding it hard to manage their services. This has also caused cases of inconsistency in what people see online and what they receive as deliveries
What it does
To solve the problem of surge in online orders, we have designed a state-of-the-art “SurgeBalance” algorithm that uses ML and Data Science to make sure restaurants are never under the nerve. Our app uses technologies like Augmented Reality to provide consumers a ground-truth of their orders and portion-sizes - thus creating a seamless transition from Brick & Mortar to virtually at home. To top this all, we have designed a data analytics dashboard for restaurants to manage and run their businesses smoothly. All built using NCR’s rich APIs!
We define concept of “busyness” of a branch and quantify it using our algorithm:
Multi-Objective Minimization Problem - distance of consumer from branches, and the busyness of a branch
Surge Balancing Algorithm:
Using available staff, number of active orders, difficulty of preparation
“Complexity” of menu item - function of preparation time and elapsed time since order was placed
“Busyness” is calculated by a regressive approach based on staff, complexity of all orders
Final choice of optimal branch to send order to is the minimum of weighted sums of driving time to customer and busyness
We have also created a loyalty program for our returning customers to prevent them from rerouting to new locations over and over again. The greater the loyalty points, the more of getting lower weight times. This provides an incentive for a loyal user base.
And we are the most "social" delivery application to date - you can create a virtual menu with your friends, split bills evenly, and enjoy the fun of going "dutch" while being at home, even in different states!
Our first Figma prototype designed using NCR's design guidelines:
https://www.figma.com/proto/5P5AFAfP3NbJjztrDS37k8/HackGT?node-id=2%3A2&viewport=180%2C331%2C0.35989025235176086&scaling=scale-down
Our React Native + Django app for iOS/Android:
https://github.com/gursimransingh93/crust-hackgt7
What's next for Crust
We have built a solution that can be scaled easily with current systems and uses a mobile-first approach to solve a lot of problems that NCR is facing right now. An interesting approach: we plan on placing this as a white-labeled API-as-a-Service that significantly improves and extends/builds upon DoorDash’s white-label Drive service.
Built With
arkit
augmented-reality
django
react
react-native
swift
Try it out
github.com | Crust | Crust is a one-stop solution in form a consumer app that lets users enjoy a seamless food ordering experience while making sure the restaurant supply chain is optimized for our post-COVID needs. | ['Pulak Agarwal', 'Saumya Jain', 'Gursimran Singh', 'Hritik Sapra'] | ['Top 8 Overall'] | ['arkit', 'augmented-reality', 'django', 'react', 'react-native', 'swift'] | 2 |
10,371 | https://devpost.com/software/maskon-6dghtp | Goals
Inspiration
Many stores require masks and enforce occupancy limits to limit the spread of COVID-19. However, there doesn't yet exist a streamlined system to help ensure shoppers are wearing masks, and close doors when the safe occupancy limit is hit.
What It Does
Our hack is composed of:
A deep learning model which detects whether a person is wearing a mask or not in real time trained using Microsoft Azure.
Two ultrasonic sensors that track customer entry/exit by measuring signal spikes when the door is crossed (directionality is achieved by seeing which sensor was crossed first)
A mask dispenser that dispenses masks when an unmasked face is detected
Our solution reduces the risk of having an extra human that could potentially be infected or get easily infected by several customers - and cuts cost of having to pay an extra employee.
-MaskOn is cheaper to implement than having to pay an employee to do the same job for a week!
The system will (A) automatically keep the door closed when the occupancy cap has been reached, and (B) instruct unmasked users to retrieve and put on a mask before allowing them inside.
The idea is to integrate our software with existing stores CCTV/automatic door systems to keep installation costs at a minimum. Businesses with this existing hardware can use our Microsoft Azure API to get the pretrained model for mask/face detection and integrate our solution seamlessly.
How We Built It
We were able to find many datasets online for masked/unmasked faces, which we used to train a CNN using keras and Azure GPU acceleration
-Saved the trained model in Azure and created an API to allow for easy business integration
We used OpenCV to stream video from the camera and detect masks in real time using the model
We used an Arduino to control a mask dispenser and detect when people cross the threshold using ultrasonic sensors
Challenges We Ran Into
Optimizing the framerate; running mask detection on every frame is slow, so we used partial face recognition to identify if there is a subject visible in the camera first before running the more intensive mask detection model.
It was difficult to get the people counting working, ultrasonic sensors were noisy and we spent a lot of time finding the right way to filter the readings. We ultimately used an FIR moving average filter to get smoother detection. An IR sensor would have been easier to work with.
The Future of MaskOn
-Better entry/exit counter system
-Smaller mask disposal solution
-Modules for easier integration onto any business storefront
Built With
azure
colab
keras
python
tensorflow | MaskOn | Reduce COVID-19 risk in stores by automatically enforcing PPE and occupancy requirements at the door. | ['Ausaf Ahmed', 'Harsha Tambareni', 'Kehinde Adedara', 'Aditya Varun Pratap'] | ['MLH: Best Hardware Hack Sponsored by Digi-Key', 'Top 8 Overall'] | ['azure', 'colab', 'keras', 'python', 'tensorflow'] | 3 |
10,371 | https://devpost.com/software/ballotproof-vision | logo
home
address
file upload
autocrop
cropping confirmation
uploading files
manual crop
upload complete
output
annotation UI
BallotProof
Voting made faster, smarter, and more secure.
@authors:
@Devrath Iyer
(Stanford '24)
@Ethan Shaotran
(Harvard '25)
@Koushik Sridhar
(UNC '24)
@Pratham Soni
(Stanford '24)
Introduction
With an emphasis on social distancing and remote engagement as a result of the COVID-19 pandemic mail-in voting surged from 24.9% to 50.3% of ballots [
1
] in the 2016 and 2020 primaries, respectively. This surge will also trigger an unfortunate increase in ballots rejected due to the avoidable human error; we’ve already started to see the effects, with half a million ballots rejected [
2
] in the 2020 primaries. As first-time voters, this issue is extremely critical to us as our generation seeks democratic representation. In an effort to reduce rejection rates, we introduce BallotProof, a methodology built for faster, smarter, and more secure validation of ballots.
What It Does
BallotProof is built from the ground up with ease of use and security in mind. As a result, the platform was developed with a server-independent structure, with all image analysis done on the client-side to avoid any risk of data leakage. BallotProof takes in input images of the front and back sides of your ballot and uses image analysis to specifically determine which errors can prevent your critical vote from being counted. We handle everything for you from start to finish, with automatic cropping of your pictures to showing exactly which sections in which errors were made and specific templates made for your unique ballot.
Our methods are currently able to point out if you've made any of the following:
Incorrect pen colors
Blank sections
Excessive bubble fill-ins
Improper write-in format
Ban bubble fill-ins
And much more!
And all you need to do is enter your address and take pictures of two images without fear of your data being compromised!
How we built it (Programs, Tools, & APIs)
So how did we make it happen?
Geocod.io - API for Congressional District Checking
OpenCV.js - In-browser image processing for cropping and analysis
PIL - Generation of test examples.
Django - Provisioning website backend.
Amazon AWS S3 - Hosting annotation files.
Python - Django and example generation.
HTML - Website structure.
JavaScript - Scripts including data loading and analysis
Heroku - Server hosting platform.
Domain.com - Our domain name:
www.BallotProof.tech
:)
Future Steps
We do recognize that there are limitations in our project. We are committed to the continual improvement of BallotProof as a service to facilitate greater participation in democracy. In particular, we wish to continue to improve our analysis algorithms, especially automatic cropping. We also wish to include additional testing fields such as required signatures and dates, and our current data structures are set up for that integration. With additional time, tools like Tensorflow JS are appealing as ways to incorporate deep learning within the scope of our work.
Aside from the technical front, a significant part of our goal is increased accessibility. To do that, we must partner with local governments to gain access to sample ballots, so that we may construct annotation masks for our analysis. As part of that, we plan to build a annotation tool that will drastically reduce the man-hours it currently takes for us to draw information from the raw ballot. A mock-up of the annotation UI is attached below.
Notice
ALL BALLOT IMAGES ARE AUTOGENERATED BY A COMPUTER FROM A SINGULAR SAMPLE BALLOT.
THESE BALLOTS DO NOT EXIST PHYSICALLY AND ARE NOT INTENDED TO BE SUBMITTED AT A
POLLING LOCATION OR BE SENT IN THE MAIL.
The generation script (generate.py) enables the generation of semi-randomized
ballots that fit certain satisfiability criteria. We use these sample ballots
as tests for model functionality.
Link to test files:
https://tinyurl.com/ballotprooftests
Attributions
A huge thanks to HackGT for setting up this great event, the opportunity to
compete, and the great events over the weekend.
We thank the OpenCV guide for getting us started for in-browser image analysis.
Built With
django
geocod.io
heroku
html
javascript
opencv
pil
python
Try it out
ballotproof.herokuapp.com
www.ballotproof.tech | BallotProof | Voting made faster, smarter, and more secure. | ['Pratham Soni', 'Ethan Shaotran', 'Koushik Sridhar', 'Devrath Iyer'] | ['Top 8 Overall'] | ['django', 'geocod.io', 'heroku', 'html', 'javascript', 'opencv', 'pil', 'python'] | 4 |
10,371 | https://devpost.com/software/helptag-oi5cek | Providing users various crowdsourced resources to enable participation in different movements.
Providing users methods to input new resources into the crowdsourced database.
Inspiration
“I want to contribute to #BlackLivesMatter, but I don’t know where to start.”
That statement served as the starting point for our team’s hack this weekend. In the past few months, the world has seen several high profile social or political movements and causes arise from social media and remembered through hashtags: #MeToo, #BlackLivesMatter, #HKProtests. Despite its shortcoming, social media is indeed a powerful tool that can be used for the common good. Twitter is a good place where you’re exposed to what’s happening in the world. However, when we come across such hashtags from the comfort of our homes, we feel a certain degree of helplessness watching the events unfold.
“Actions speak louder than words.”
In addition to engaging in the conversation online, people could act on issues that matter to them. Depending on the cause, these could be donations, volunteering opportunities, real-time events, or even reading resources. However, this information often isn’t known to everyone or is accessible in a way that is quick and effortless.
Every single contribution matters, and we’re all facing these issues together as one society. Learning more about a cause that matters to you and providing you with information to do so is the essential value proposition of our idea.
What it does
Meet
HelpTag
! It is a Chrome extension that adds subtle enhancements to your Twitter experience which allows you to quickly browse through actionable, crowdsourced links related to a hashtag that you see on your feed. If a particular hashtag on your feed is being used for a particular movement or cause, our extension would allow you to explore ways you can contribute to what’s going on out there. Categories such as ‘Donate’ and ‘Volunteer’ allow you to browse through links within the contribution method of your liking.
Want to donate to a protest relief organization? Want to volunteer your home as a wildfire shelter? Want to know more about the protests in Nigeria regarding SARS? HelpTag can point you in the right direction, instantly.
How we built it
We focused on building a simple, effective, and robust tool that is paired with a
seamless user experience
and a clean interface. Having brainstormed the idea through a
whiteboard discussion
, we were able to define the scope and value propositions of our project early on. We created mockups early on using Figma to explore directions in the visual and interaction design of our solution.
We created the interface by injecting
HTML, CSS, JavaScript
into twitter's DOM element through a
Chrome Extension
. Several libraries were used to achieve the required interaction patterns. These included
bootstrap, jQuery, fontAwesome
.
We used
Google’s Firebase
to create a cloud-based
NoSQL Database
storing all of our crowdsourced information on resources. The data is stored as
JSON
and synchronized in
real-time
to every connected user at all times. We relied heavily on
Google Developer Tools
for troubleshooting and deployment of the extension on the browser.
Finally, we spent two whole days online on Twitter.
Challenges, accomplishments, and reflections
We ran into several challenges while developing the tool. Understanding the front-end deployment of Twitter was challenging, but necessary to make the necessary UI adjustments to the interface. Deciding what theme to tackle was a challenge as well. We decided to prototype the solution for one theme for the scope of this hackathon. Another challenge was considering the business goals a solution like this could accomplish.
The team is proud of what they come up within the span of two days. The tool solves a real problem faced by our acquaintances. The team accomplished a good level of attention to detail with the solution.
In hindsight, we would have wanted to start working on the solution earlier. We had to pivot from another idea because we found this idea more exciting, but we lost a significant chunk of time pursuing another idea.
What's next for HelpTag
Based on our initial brainstorm, there were a few ideas that seemed beyond the scope of the hackathon but added essential value propositions to the product. If we spend more time on building the extension, we have a mini product feature map ready:
Personalized recommendations. (ex: location-based: events near you)
Light and Dark modes to match the display options on Twitter.
Link aggregation using correlation scores for various hashtags.
Built With
bootstrap
chrome
css3
firebase
html5
javascript
jquery
twitter
Try it out
github.com | HelpTag (Team Ohana) | Learning ways to contribute to a movement or a cause that you see on Twitter. | ['varnit jain', 'Arpit Mathur', 'Aditya Kundu', 'Jay Modh'] | ['Top 8 Overall'] | ['bootstrap', 'chrome', 'css3', 'firebase', 'html5', 'javascript', 'jquery', 'twitter'] | 5 |
10,371 | https://devpost.com/software/bizviz | BizViz: Powering Small Businesses to Make the Best Financial Decisions
HackGT 7 Hackathon Submission
BizViz is a financial business visualization tool that gives small business owners insight into different ways to keep their business operating during difficult times like the COVID-19 global pandemic. Instead of having businesses collapse due to owners continuing to spend more money to keep themselves growing, our application takes that same monetary value and instead shows what would be a reasonable return if that money was invested into different types of stock market portfolios. All this data is then presented to the user to allow them to better gauge whether it would be worthwile to divert funds into investments while the pandemic is active to potentially make a profit to keep the business operating for longer.
Some of the technologies we used include:
React - Frontend
IBM Watson Cloud - Storage and deployment of stock forecasting model onto the cloud
Flask - Web App hosting and custom API routing
Scikit-learn - Creation of machine learning ensemble and stock forecasting model
How it works
When the user first visits the site, they will be prompted to enter some data about the business: ENTER THAT HERE. Then, the user will submit an excel/csv file that has the total companies monthly costs (fixed + variable costs, advertising, wages) and their monthly revenue for the past 10 years. This data is then parsed and processed for training of our machine learning algorithm that is chosen from an ensemble of models that is optimized for our data. This model then outputs predicted revenue based on the business' performance.
Taking into account the projected revenue, we created another ML model to forecast the projected values of simulated portfolios if the specified amount was invested in the stock market instead. We then used the IBM Watson cloud to upload and deploy our ML model so it can be used for other applications in the future. This gives us great flexibility in the predictions we wish to perform.
The custom stock portfolios have 3 categories: Low Risk, Medium Risk, and High Risk. The low risk is composed of non-volatile options such as index funds and bonds, while the high risk option is comprised of stocks with high volume, high market cap, and other indicators of volatile stocks.
The predicted revenue, and the predicted growth of the 3 suggested stock portfolios are plotted on a graph to provide the business owner with a simple and effective way to decide whether it could potentially be beneficial if they invested in the portfolio instead of putting that into the business.
Team:
Yash Patel (
@yashp121
)
Nishant Ravi (
@NRavi01
)
Varun Lakshmanan (
@varunlakshmanan
)
Pranav Pusarla(
@PranavPusarla
)
Built With
flask
ibm
ibm-watson
javascript
python
react
scikit-learn
Try it out
github.com | BizViz | Powering Small Businesses to Make the Best Financial Decisions | ['Nishant Ravi', 'Yash Patel', 'Varun Lakshmanan', 'Pranav Pusarla'] | ['Top 8 Overall'] | ['flask', 'ibm', 'ibm-watson', 'javascript', 'python', 'react', 'scikit-learn'] | 6 |
10,371 | https://devpost.com/software/hemohelper | A friendly home screen
One-time entry of your emergency contact/healthcare provider information
Real-time blood oxygen level tracking
Inspiration
In light of the pandemic, we wanted to create a product that would reduce fatalities related to Covid-pneumonia. One of our member's fathers suffered from suddenly low blood oxygen levels and we quickly learned the importance of blood oximeters in caring for the sick, elderly, and even athletes.
What it does
This is an Android app that connects via bluetooth to a wearable blood oximeter (such as an Apple watch, Fitbit, or ring). The app immediately calls 911 and notifies an emergency contact in the event that the user's blood oxygen level dips below a risk threshold. Additionally, the app tracks the user's location.
How I built it
We used an Arduino Uno with a bluetooth module to generate blood oximeter data and built the app through Android Studio and various Android APIs.
Challenges I ran into
We are 3/4 emerging and 3/4 non-CS engineers, so we had a lot to take in! The workshops and mentors at this event were extremely helpful.
What's next for HemoHelper
Ideally we would have liked to include a more seamless user interface. We also would like to be able to allow users to create personalized texts and play audio on outgoing calls. A resource page, including nearby healthcare providers and patient history would also fulfill the user's medical needs.
Built With
android-apis
android-studio
arduino
bluetooth
java
Try it out
github.com | HemoHelper | An app that notifies emergency services when a user's blood oxygen levels are low. | ['Michelle Vo', 'Frank Ketchum', 'Katherine Lang', 'Amanda Lang'] | ['Anthem: Personalized, digital medicine in the age of COVID and beyond', 'Top 8 Overall'] | ['android-apis', 'android-studio', 'arduino', 'bluetooth', 'java'] | 7 |
10,371 | https://devpost.com/software/draw-your-way | Initial Loading Screen
Main Menu
Envision mode
Import mode (featuring the same build from the previous photo)
Draw mode
Sample user profile
Web version of app ("Envision" mode)
Mockup of 2D object mode
Mockup of Draw/Add Image mode
Sample - Grocery Store Mockup
It is common to find yourself in a new and unfamiliar place where you have to ask others for directions. From college freshman to new employees, it can be difficult to traverse a building while juggling first day anxieties. Therefore, we created Draw Your Way, an app that can help users illustrate directions in smaller spaces. There are few maps for places like buildings or college campuses that are simple enough for anyone who is unfamiliar with the area to understand.
With Draw Your Way, you can use 2D objects and the drawing feature to guide friends and strangers alike through buildings, campuses, and cities. The app allows users to create a simple visual guide then share it, making it the perfect guiding aid.
We created the mobile application primarily using Android Studios and Flutter. We coded the app using dart and added 2D pixel art made from Photoshop. The different aspects of the app we focused on were the user interface, the drawing program, and the object dragging program for adding visual aids. We also set up FireBase for backend data storage.
Some challenges we ran into were initially setting up Android Studios and connecting it to Flutter. The process was lengthy and some missteps or mistakes would take a while to fix because we are new to app development and do not know the typical issues people would run into during setup. However, we were able to fix or work around issues and ended up with a functional app!
At the start of the hackathon, none of us were familiar with app development, but we used the experience to learn about the process of making an app. We learned a lot about troubleshooting setup components and using the Dart language with Flutter, which had commonalities with Python and Java.
As we continue our journey creating Draw Your Way, we would like to add augmented reality to the mobile application so users are able to scan their surrounding and assist others using real images of the location. Additionally, we would like to store the share code in a database with corresponding ID numbers so that the user share code can be simpler and easier to share. We would add more direction icons in the "Envision" option for more functionality. We would also iterate the design of the mobile application to fit users' needs and ensure customers are happy with the app's function and features.
For HackGT 7 Judging:
We would like to be considered for the Emerging Hackers: Best Overall, Best Design, Most Creative, Most Impactful, and Best in Curriculum for App Development and Web Development.
Built With
android-studio
dart
firebase
flutter
intellij-idea
photoshop
visual-studio
Try it out
github.com | Draw Your Way | A mobile guiding app that uses 2D graphics to help users explain directions visually. | ['Sarah Miller', 'Allison Kwan', 'yu-pan-cpu .', 'Cynthia Wang'] | ['Emerging Hackers: Best Overall'] | ['android-studio', 'dart', 'firebase', 'flutter', 'intellij-idea', 'photoshop', 'visual-studio'] | 8 |
10,371 | https://devpost.com/software/deploy-kfhl37 | Inspiration
Zarya - "While trying to conduct a local BLM protest, we had to utilize several types of tools to consolidate volunteer management and communication. We felt that using a singular tool that prioritized privacy and a streamlined user experience would better assist community organizers at large to be able to use tech to help them spend less time on managing and more on what they do best."
What it does
Provides a portal to manage volunteers and tasks to put on community events (specifically in the realm of advocacy). Done in a way that doesn't record any identifying information about volunteers and prompts them to use aliases so that they are less at risk of being targeted for participating in events such as protests.
How we built it
Midfidelity prototype using Figma detailing the task flows of both the community organizers and the volunteers
Challenges we ran into
From a hackathon perspective, being able to get farther than prototyping on time was a struggle considering our inexperience with the technology we would have needed to use to set up an actual site with this level of complexity.
Accomplishments that we're proud of
Having something to submit! After the trials and tribulations of making grand plans and then realizing having to learn tools on the go and implement them well wouldn't really fit with the timeline of the event, not to mention lack of sleep making it hard to process things.
What we learned
Setting up github repositories, using Figma, general understanding of what goes into a web app stack at a very high level.
What's next for Deploy
We think this is a cool idea and we'd really like to explore it in the future when we have better grasps of the web dev tools we'd need.
Built With
figma
Try it out
www.figma.com | Deploy | A tool to help grassroot organizers and volunteers connect while protecting volunteer privary/anonymity. | ['Sydney Cook'] | ['Emerging Hackers: Best Design'] | ['figma'] | 9 |
10,371 | https://devpost.com/software/fresca | wow look at our logo
wow look at these palettes
"Urban Jungle" - the generated fit
"Spooky Szn" - the generated fit
"Fireboy and Watergirl" - the generated fit
Inspiration
Whenever we went shopping, we were overwhelmed by the variety. Our tool allows businesses to help uncultured people like us figure out what we should buy and wear, based on designer color palettes that the user can browse and choose from.
What it does
Fresca generates color-coordinated outfits from extensive clothing catalogs. Our tool matches clothes with an aesthetically pleasing color palette to generate personalized outfits for the user.
How we built it
Began with accumulating Uniqlo catalog pictures
Wrote a script to write prominent color RGB values from catalog pictures to a CSV
Wrote algorithm to match colors from a color palette to items in a catalog, optimized as needed for nice lookin' fits
Made a front-end app in Android Studio to showcase the results of our color extracting and matching algorithm in a sleek UI, generating easily scrollable outfits with displayed price
A lot of “what the f-” in-between
Challenges we ran into
Parsing background colors from clothing colors
Comparing clothing color to palette color
Getting the color algorithm to generate more diverse outfit sets that better represented the chosen palette
Literally anything in android studio, it never does what you think it should do or what you want it to do :(
The app works seamlessly in the emulator but runs into issues on some android devices. We are still in the process of figuring out why so fair warning if you decide to try to the apk :)
Accomplishments that we're proud of
It kinda works :)
Created a mostly successful color matching algorithm
Expedited our workflow with various data processing techniques that just made our lives easier
The palette color names
What we learned
How to apply data science techniques to sort through clothing catalogs
How to compare colors through numeric values
Became proficient an Android studio
The process of designing an algorithm can be kind of rough
What's next for Fresca
Currently, the app works seamlessly in the emulator but runs into issues on some android devices, and it would be pretty epic if it worked on all those devices
Enhance the user interface with swipes and dropdowns and more wardrobes
Create a palette generator to generate more palette options to choose from upon scroll
Improving consumer experience by allowing users to insert their own wardrobe and custom palette into a custom database for the app to choose a fit for the user
Display multiple versions of the same chosen wardrobe from multiple retailers to allow consumers to make economic choices for their
Built With
android-studio
colorthief
glob
java
jupyter
numpy
pandas
python
r
Try it out
drive.google.com | Fresca | Makes picking the fit simple by generating aesthetically pleasing color coordinated outfits in one tap. | ['Shalin Jain', 'Edward Chen', 'Viraj Singh', 'Joshua Kim'] | ['Emerging Hackers: Most Creative'] | ['android-studio', 'colorthief', 'glob', 'java', 'jupyter', 'numpy', 'pandas', 'python', 'r'] | 10 |
10,371 | https://devpost.com/software/excessible | Excessible Logo
Home Page
Map with Foodbank and Grocery Store Markers
Technologies Used
Inspiration
Within the past year, food banks across the country have reported a 40% increase in the need for emergency food assistance. To help cater to this need, we thought of Excessible.
What it does
Excessible allows food banks to send a request to a grocery of items that they are need of or allow a grocery store to send an announcement of food they are no longer in need of. Based on their inventory, the grocery store or food bank can choose to accept the request , and the foodbank can pick it up from its nearest one. To do this, we have provided a map that the food bank/grocery store can look at and decide which to choose.
How we built it
To build our platform we used JavaScript, HTML, React, Google Firebase Realtime Databases, and Google APIs.
Challenges we ran into
While coding, we ran into many problems with getting the API to function exactly in the way that we wanted. There were numerous bugs and default settings that hindered our progress, but we were eventually able to overcome them through much debugging. We are proud that we were able to work through our bugs, especially on the back-end with saving user information, and logging it. This took us a long time to maneuver and understand, so we are really happy that we ended up getting it to work. On the Google Maps front, we learned how to load and integrate
Accomplishments that we're proud of
We are extremely proud of how much we accomplished in such a short time and how we were able to integrate all the APIs from Google Maps to Firebase within our project seamlessly.
What we learned
We learned a lot about web development as a whole, how to use a frontend framework and connect it to a backend, and how to use the Google Maps API.
What's next for Excessible
Since surplus items are contingent on expiration dates, we want to include an object detection framework to label different grocery items and keep track of expiration dates in our database. In addition, merging trips to/from food banks by optimizing delivery times would help reduce the number of trips and save on CO2 emissions. Lastly, if independent donors want to get involved, they can keep track of their receipts with an embedded scanning application.
Built With
css3
firebase
google-cloud
google-maps
html5
javascript
react
Try it out
github.com | Excessible | Excessible works to connect grocery stores with food banks in need and makes excess food accessible! | ['Shreya Santhanagopalan', 'Kartik Narang', 'Anvitha Veeragandham', 'Aayush Seth', 'Shreya Santhanagopalan'] | ['Emerging Hackers: Most Impactful'] | ['css3', 'firebase', 'google-cloud', 'google-maps', 'html5', 'javascript', 'react'] | 11 |
10,371 | https://devpost.com/software/k-bbq | Inspiration
We are a team of four international students from three different countries: Myanmar, Mexico, and South Korea.
One thing we have in common was that we totally love the sweet and greasy American food.
But almost every time we went out to eat in restaurants around the States, a serving was way too much to finish in one meal. Sometimes we took the leftover food and re-cooked it, but it wouldn't taste the same. In worst cases, the food spoiled and we just had to wast the food.
We've also found that a lot of people had the same problem and many restaurants around the state were facing the issue of food waste. People usually could not finish their plate and a lot of food went to waste.
We’ve also found out that food wastage was a very big problem in the states. More than 80 billion pounds of food were thrown away each year and 40% of the US food supply is wasted each year.
So we came up with this idea:
Foodie Buddie.
What it does
Foodie Buddie is a food sharing app that connects the customers and restaurants. Using Foodie Buddie, customers can make a personalized order where they can adjust the amount of food they would get from the restaurant. If they choose less amount of food than one serving, they will receive points.
They can either accumulate the points and use the points to purchase food later on or sell the points to others.
People who eat more than a serving can buy the points can use it to order food more than a single serving. Therefore, foodie buddie will be connecting those who eat less than a serving and those who eat more than a serving.
In that way, food waste will be reduced in both sides and also for the restaurants.
How we built it
Foodie Buddie is an application built mainly using flutter. The application is designed to limit food waste as well as positively impact the environment.
The UI is managed via flutter and dart. With a flutter, we were able to create a responsive UI for our app. In addition to our UI implementations, we also used NCR BSP API to assist with the communications between the user and the restaurants. By using this API, the application will be able to carry out the major points of sales processes, such as payments.
Challenges we ran into
As emerging Hackers, we faced several major challenges.
The first obstacle we faced was trying to familiarize ourselves with flutter and dart. Dart and Flutter was a new language / library for all of us to work with during this two-day hackathon. However, we tried to seek help from our emerging mentor as much as possible. By the help of the workshops and mentors, we were able to go through it very well.
The second obstacle we faced was trying to implement NCR APIs into our product. The APIs were advanced and we had to invest a lot of our time trying to understand how the APIs worked.
The last obstacle we faced was trying to work across different timezones. Since our team is composed of individuals from three countries, time difference affected the way we cooperate with our team. We had to respect our teammates' personal wellbeing and at the same time also focus on our product for this hackathon.
Accomplishments that we're proud of
As an emerging team, we are really proud of learning how to create functional UI for our product and implementing the BSP NCR API. In addition to the technical accomplishments, we are also proud of the concept of our application.
We came up with an application that promotes the sharing mindset, while at the same time limiting food waste in the world. With COVID19, some people have been struggling more than ever with finding food for themselves. We are proud that this application also provides a helping solution for those people by giving an incentive for the user to donate their acquired points to needed people. They, then, can exchange the points for a warm meal. All in all, with the sharing and caring mindset being promoted, we believe that a positive impact is sure to be generated.
What we learned
From very scratch, we were able to create a flutter application. Through this process, we learned both hard and soft skills.
Hard Skills:
From not even knowing the syntax of dart, self-learning flutter within 24 hours allowed us to develop the skill of how to effectively understand and use language documentations.
This essential skill allows us to be a fast and adaptive learner in today's rapid technological world. Throughout our learning journey, we also gain some insight into how well-known companies apply the language for professional application development.
Soft Skills:
Gaining soft skills are as important as gaining hard skills.
Being a diverse group, we learned how to collaborate and communicate efficiently with people from different cultural backgrounds. In order for this collaboration and communication to be successful, we had to use several collaborating platforms, such as slack and github.
Throughout all the meetings and shared documents, the most important lesson we learned was how to efficiently split the workload between teammates that live in different time zones.
What's next for Foodie Buddie
Our ultimate goal is to develop and spread our app so that the people who eat less and the people who eat more can swap in real-time and decrease the amount of food wasted in the U.S. as much as possible.
We plan to gather restaurants and customers who are interested in preserving the earth environment by reducing food waste to join our app. As more and more people join Foodie Buddie, the better our world will become.
Built With
android-studio
bsp-api
dart
firebase
flutter
Try it out
github.com | Foodie Buddie | save the earth with food sharing :) | ['Sugju Choi', 'Jongin Jun', 'Khin Phyu Khine'] | ['Emerging Hackers: Best in Curriculum Track'] | ['android-studio', 'bsp-api', 'dart', 'firebase', 'flutter'] | 12 |
10,371 | https://devpost.com/software/optimizing-news-recommendation-algorithms | Ranked Spreadsheet of Website URLs
Inspiration
Reading through the NewsQ challenge, we found the real-world applications of the project really interesting. Because our team had members with interests that branched out from computer science, the idea of creating back-end code
What it does
It takes into consideration a variety of factors which are assigned weights based off their relative importance. The weighted values for each factor are used to calculate a final rating for an article. The articles are then arranged according to the ratings.
How I built it
We used Python as the framework for working with different API's to pull data
Challenges I ran into
Collecting website data, using effective APIs for our algorithms, debugging for various errors when utilizing API and dealing with data
Accomplishments that I'm proud of
When we were almost done with our project, an API stopped working and we felt doomed for a short time. When we were able to work through these issues, there was an amazing sense of accomplishment that came over the team, and it lifted our spirits. Accomplishments like this are a large aspect of what makes hackatons a good time!
What I learned
We learned data scraping the web with multiple APIs, developing algorithms to quantify that scraped data, and outputting that data in a spreadsheet
What's next for Optimizing News Recommendation Algorithms
Finetune the algorithm and add more factors to make the article ranking more accurate (ex: check amount of ad content, utilizing a UK fact checker, etc.)
Utilize machine learning by creating a training set and applying attributes known to make an article more or less reliable
Create a front end interactive user-friendly interface to allow users to browse unbiased and trustworthy articles of their interest
Built With
media-cloud-api
newspaper3k
python
sentiment-analysis-api
Try it out
github.com | NewsQ Challenge: Optimizing News Recommendation Algorithms | Creating a better algorithm for recommending news articles based on a variety of criteria with different weights | ['Matthew Gebara', 'Andrew Ouyang', 'Daniar Tabys', 'neilhpatel'] | ['Emerging Hackers: Best in Curriculum Track'] | ['media-cloud-api', 'newspaper3k', 'python', 'sentiment-analysis-api'] | 13 |
10,371 | https://devpost.com/software/hackgt2020-fvrymo | Inspiration
We wanted to make a game to help COVID patients deal with social isolation during the pandemic. The natural choice was to make a game involving voice chat.
What it does
The player controls a character using keyboard commands and uses voice chat to ask Watson to interact with the levels. The voice commands allow Watson to help the player solve the puzzles that appear in the levels.
Challenges we faced
Fine-tuning the voice commands for the Watson AI was a bit tricky initially, but it didn't take long to get it implemented. Much of getting the game mechanics working and coming up with level designs came down to trial-and-error work that just took time to build. The final build into a standalone version also took some troubleshooting to finish.
How it was built
This game was built in Unity using the IBM Watson API with the Unity SDK. The scripting is written in C# and the game was formed entirely using assets within Unity.
What we learned
I was personally fairly new to Unity, so I learned a lot about the process it takes to go from ideation to finished product. A lot of the internal elements of Unity that we used for this project were new to me as well. As a team, we learned a lot about how to coordinate pushing changes to GitHub and how to distribute work on a game design.
Built With
c#
ibm-watson
unity
Try it out
github.com | Bob Was A Rectangle | A game of solving puzzles with the IBM Watson AI. This project is aimed at COVID patients dealing with social isolation. | ['Kauri Salonvaara', 'James Reilly', 'Jake Smith', 'PL3B3'] | ['Emerging Hackers: Best in Curriculum Track'] | ['c#', 'ibm-watson', 'unity'] | 14 |
10,371 | https://devpost.com/software/hackgt2020 | Landing page.
Explore important issues.
Explore previous debates within an issue.
Two users on a call, with live transcripts and analysis.
The transcript is added to the explore page.
Login/Signup page, with email verification and password reset.
HackGT 2020
Rohan Agarwal
\
Arjun Verma
\
Anthony Wong
Inspiration
It is clear to see that today's world is a fractured one. Even in this day and age where everyone can talk with virtually anyone, any meaningful conversation is rare. Instead, people turn to places like Twitter, Instagram, and Facebook as outlets for mudslinging and creating conflict, with society in a worse state than before they started. The effects of such a confrontational and close-minded society can be felt and have been for several years. Ever since the 2016 election, the nation has been on a downward spiral, almost to the point where it's nearly impossible to debate without a fight. With our application, we hope to revive what the forefathers valued so much: Civil Discussion.
Solution
For us, this application is more than just a place people can talk about various topics. We want to fundamentally change the way people approach contentious issues. As firm believers in the idea that positive change only comes from constructive conversation, we have developed a platform that not only allows for telephone-style debates, but also transcribes and analyzes the conversation, creates text posts, and cultivates a space for meaningful, productive discussion.
First, if a user wants to have a discussion, they will sign into their account and search for the issue of their choice. They then can click the call button and wait for someone to match-up with. As they debate, their conversation is transcribed and arguments are analyzed and flagged if they are unsupported by evidence, claim a fact, or are opinionated/emotional. We were careful to consider psychology--this way, discourse always remains civil and productive, without bias or a disdain of being corrected. When the call ends, everything is automatically uploaded as a post for all to access and explore different, thorough perspectives on important issues.
Technical Details and Challenges
We used React to create the entire front end, Firebase and Firestore for authentication and data storage, Google's Web Speech API for speech-to-text, Express.js and Socket.io for our real-time server, and our own original algorithm for live argument analysis.
All of us were relatively new to React, Express.js, and Socket.io, making this project challenging overall. The high quality presentation and the many features we strove for also added to the challenge. We had particular trouble with the nuances of converting speech-to-text data with traditional chatbox text into a single transcript with proper timing and accuracy. However, we pulled through with our own speech timing system, which also managed the timing of our flagging system.
Accomplishments
As students who are cognizant of the things going on in the world around us, we know the country is becoming more and more divided by the day. We are happy that we took the opportunity to create something that could be the start of real change. We are also proud of the technical skills we have developed, the polished final product, and the experiences we have shared as a team.
Next Steps
One major step we want to take is to make the generated content from debates more discoverable with a custom feed for each user. Another step is to allow more than two people in a call, allowing for a wider exchange of ideas in each discussion. We may also want to create a more robust flagging system. We could also implement a business model; one possibility is to compensate users who record lengthy, high-quality debates and charge users for reading lots of transcripts, while another is to sell the software to schools and other organizations. To bring this to the real world, we would first approach classrooms and then move on to the general population.
Built With
express.js
firebase
google-web-speech-api
javascript
react
socket.io
Try it out
github.com
docs.google.com
salon-hackgt.azurewebsites.net | SALON | Realtime public debate platform @ HackGT 2020. | ['Rohan Agarwal', 'arjun11verma Verma', 'Anthony Wong'] | ['Emerging Hackers: Best in Curriculum Track'] | ['express.js', 'firebase', 'google-web-speech-api', 'javascript', 'react', 'socket.io'] | 15 |
10,371 | https://devpost.com/software/hackgt7 | Fizz
Your Personal Financial Consultant
Made by: Robert Bloomquist, Ashish D'Souza, Ananth Kumar, and Sharath Palathingal
What is Fizz?
Fizz is an interactive personal financial consultant perfect for providing the beginning investor with insight rivaling that of financial experts. Fizz offers numerous services, whether that is analyzing users’ current portfolios, simulating the outcomes of potential transactions, or even advising users to implement simple yet effective risk management strategies.
What We Used To Implement Fizz:
BlackRock Aladdin API
for asset risk data
Finnhub.io API
for stock pricing, history, and analysis
ReactJS
for UI/UX
Flask (on PythonAnywhere)
for as our application framework
Google Cloud
Dialogflow Natural Language Processing (NLP)
for the chatbot's responsivity
Firebase
for storing profile data
Apache Cassandra - DataStax Astra
for transferring data between front-end and back-end
How It Works:
A user opens Fizz and is greeted by a prompt to fill out and upload their portfolio and current holdings. Once uploaded, Fizz analyzes this data and is ready to interact with the user. The user can ask a variety of questions, ranging from "Should I buy stock ABC?" to "Tell me about my current portfolio." Fizz, pulling data from various public APIs and expert recommendations, provides relevant and effective answers to the user's questions.
Visit
https://stonkify.xyz/
to use Fizz!
Resources:
https://www.blackrock.com/tools/api-tester/hackathon
https://financialmodelingprep.com/api/v3
https://cloud.google.com/dialogflow/docs
https://www.datastax.com/products/datastax-astra
Built With
flask
javascript
python
react
Try it out
github.com
therealsharath.github.io | Fizz - Your Personal Financial Consultant | Fizz is an interactive personal financial consultant perfect for providing the beginning investor with insight rivaling that of financial experts. | ["Ashish D'Souza", 'Ananth Kumar', 'bobbybloomquist', 'Sharath Palathingal'] | ['BlackRock: Give us your best chatbot!'] | ['flask', 'javascript', 'python', 'react'] | 16 |
10,371 | https://devpost.com/software/abu | Abu - for you
ABSTRACT
Our goal behind this project is to lower the cost of entry to financial markets by providing people with the tools and knowledge to make informed decisions with their money. Given the rise of chatbots, we felt that this was the best avenue allowing quick interactions and a direct flow of information to the user. We made many stylistic and design choices throughout our process to create a friendly, useful UI many of which you can see and experience.
INSPIRATION
In the Disney movie “Aladdin” the Kleptomaniacal monkey Abu is an inquisitive character. Hence, sticking with the Aladdin theme inspired from the name of the blackrock API we chose to name our chatbot “Abu.”
WHAT IT DOES
Abu helps users obtain vital information about the financial market and their portfolio while maintaining a human-like conversation experience. Some functionality of Abu include:
Portfolio Management:
•Graphical and tabular representation of the customer’s portfolio.
•Classification of portfolio in terms of security type and sector data.
•Top and bottom performers in the portfolio.
•Personalised information about specific securities within the portfolio.
Market Search:
•Search the entire stock market based on tickers.
•Provide top performers per sector in the stock market.
•Overall market performance through S&P 500 and DOW indicators.
Custom Investment Portfolio:
•Recommend stocks based on consumer goals.
•Show top and bottom performers safe, medium, and risky stocks.
HOW WE BUILT IT
The back - end is built with python with the use of Numpy, Pandas, and matplotlib to generate custom graphs and tables. The heart of the back-end makes use of the blackRock APIs, specifically the performance data, portfolio analysis, and security search APIs. Furthermore we used the Alpha Vantage API to provide real-time data to the consumer and imgur API to transfer generated graphs from the back end to the front end. The front-end uses dialogflow hosted by google cloud to train a machine learning model through intent and entity identification using natural language processing. The dialogue flow uses a webhook protocol to make JSON requests to our backend using Flask and Ngrok. These are processed in the backend and after gathering API information we make JSON responses back to Dialogflow. We chose to run our messaging on the platform Telegram as it’s simple UI and implementations made it powerful and practical. We have created a bot here which synchronously links to our Dialogflow.
CHALLENGES
Some obstacles we ran into included getting stock price data from the Black Rock API’s, integrating an image posting API, and creating a webhook connection to allow our program to influence DialogFlow’s responses. We had to be creative and use different approaches to solve these challenges.We also ran into a difficult run timeout problem which caused problems when run with the Aladdin APIs.
ACCOMPLISHMENTS THAT WE ARE PROUD OF
We were very proud of our ability to troubleshoot many of the problems we faced. We collaborated effectively to come up with unique, easily-implementable solutions. For example, we troubleshooted our timeout problem by loading much of the data on-loading rather than when requested to ensure that we didn’t run into problems while the chatbot was operational. Additionally, we used other financial APIs to supplement and validate data that we got from the provided APIs. Most of all, we are proud of one another and our perseverance and ability to stand up to challenges rather than losing the will to continue, and we believe our final product exemplifies this resilient work ethic.
WHAT WE LEARNED
Blackrock APIs, Flask, Dialogflow, Github, Natural Language Processing, Financial knowledge
Built With
aladdin
alphavantage
dialogflow
flask
google-cloud
imgur
json
matplotlib
numpy
pandas
python
Try it out
github.com | Abu | Financial chat bot using black rock API, AlphaVantage and NLP ABU: Enhancing customer service and the financial acumen of our clients through their interaction with the Blackrock chatbot | ['Ankit Mehta', 'jkalatchev7 Kalatchev', 'Rishi Bhatnager', 'Ben Woodman'] | ['BlackRock: Give us your best chatbot!'] | ['aladdin', 'alphavantage', 'dialogflow', 'flask', 'google-cloud', 'imgur', 'json', 'matplotlib', 'numpy', 'pandas', 'python'] | 17 |
10,371 | https://devpost.com/software/buzzbasket | Inspiration
America has a huge food waste problem. We waste 40% of our food each year with 80% of that being due to spoiled food. We wanted to try and help with this problem by preventing the food from spoiling in the first place. To do this, we created a bundling basket service called Buzzbasket!
What it does
First you text the bot to get a personalized selection of available baskets. Think of each basket almost like a gift basket with many different items in it. For the demo version, we focused on local coffee roasteries so these baskets would have different kinds of coffee beans (nearing the end of their shelf life) in them. Once you have received your personalized selection of baskets from our recommendation engine, you can choose which one to order. Then Buzzbasket will create an order for you in NCR Silver so that the information goes directly to the business and they can make your basket!
We also have a basket recommender for the small/local business to use. This system pulls in sales, inventory, and item information from NCR Silver in order to help the business decide what to put in the basket. It totals up the cost so they can easily see the profits it will generate as well as tries to use items that they have a large stock of that may be going to expire soon.
By using Buzzbasket, you're helping to support your local businesses during COVID-19 when they may not be getting as much business as usual.
What's next for BuzzBasket
In the future we want to utilize the delivery partner API and coupon API to expand Buzzbasket to more stores and offer incentives for consumers to buy with us.
Further down the line we can help eliminate food waste by large food chains as well. Companies like Dunkin Donuts and more throw out large amounts of inventory daily. Using NCR’s delivery API, we would be able to allow customers to order otherwise wasted food for an extremely small sum without putting a large burden on those businesses.
Built With
gcp
google-cloud
javascript
natural-language-processing
ncr
node.js
silver
Try it out
github.com | BuzzBasket | Helping small businesses thrive by reducing waste! | ['Sam Roquitte', 'Thomas Suarez', 'Noah Weinstein', 'Cameron Bennett'] | ['NCR: Develop a disruptive and innovative solution that solves at least one of NCR’s most significant problems for Banks, Stores, or Restaurants'] | ['gcp', 'google-cloud', 'javascript', 'natural-language-processing', 'ncr', 'node.js', 'silver'] | 18 |
10,371 | https://devpost.com/software/omnicart | Omnicart
Problem
70% of online shoppers won’t complete their transaction. This translates to roughly 18 billion dollars of sales revenue lost every year by e-commerce brands due to online shopping cart abandonment. Abandoned carts can happen for many reasons, including:
Unexpected Shipping Costs
Conducting research to buy later
Complex user account creation process
Coupon code didn’t work
Confusing checkout process
Value
Reduce the likelihood of abandoned carts and the risk of fraud for e-commerce
Reimagine commerce and disrupt aspects like product discovery, e-commerce, payments, and supply chain
Help merchants monitor and optimize their performance
NCR APIs Used
Business Services Platform (BSP) APIs:
Order
Selling
Sites
Catalog
Promotion Execution Service
Item Availability Service
Built With
chrome
javascript
ncr
node.js
Try it out
github.com | Omnicart | Reduce the likelihood of abandoned carts, reimagine product discovery, and optimize sales strategies | ['Aashish Thoutam', 'Otis Smith', 'Satvik Borra', 'Shreya Nidadavolu'] | ['NCR: Develop a disruptive and innovative solution that solves at least one of NCR’s most significant problems for Banks, Stores, or Restaurants', 'Capital One: Best Financial Hack'] | ['chrome', 'javascript', 'ncr', 'node.js'] | 19 |
10,371 | https://devpost.com/software/bloom-sy3816 | How it works
Chatbot
Dashboard
Inspiration
After witnessing the problems that have been hurting the world for the past few months, we felt helpless. As job security has decreased, unemployment has increased, and people feel more and more lost, financial stability and planning dramatically drop. We know banks and other financial institutions have the means to guide people to manage their money better, but many times don't have the resources to create the immense outreach necessary. After acknowledging this problem and wanting to help both businesses and consumers alike, we built Bloom.
What it does
Bloom is an all in one, personalized financial assistant that advises people on how to manage their finances. We look at spending history as well as the current state of the economy to help you invest in your interests. And we know how boring reading big blobs of text can be. So we also send users all the information they could need in descriptive graphs through both text and an easy-to-access dashboard.
How we built it
Our chatbot is powered with Dialogflow and communicates with users over text using Twilio. We store and retrieve user info using secure NCR protocols and get verbose financial data using Blackrock APIs. These all go through a Python middle layer that parses data and sends them out in an organized fashion. Our beautiful dashboard is written with React.js.
Challenges I ran into
Since our project had so many moving parts, one of the biggest challenges was figuring out how each individual service could complete its task efficiently and join in with the larger app. We had to work with a lot of new technologies such as the NCR and Blackrock APIs as well as Dialogflow.
Accomplishments that I'm proud of
We are proud to have made a flexible chatbot that can determine what a user wants from plain English. And we hope our users will be excited to see the amazing graphics we have customized for each of them.
What's next for Bloom
We hope to expand Bloom on other platforms besides just SMS. We also want to create a sturdy login system so each user can have access to their dashboard privately.
Built With
blackrock
dialogflow
javascript
ncr
python
react
twilio
Try it out
github.com | Bloom | Your personal financial advisor just 1 text away. | ['Ishan Arya', 'Brian Model', 'Rahul Bhethanabotla', 'Naveen Ram'] | ['NCR: Develop a disruptive and innovative solution that solves at least one of NCR’s most significant problems for Banks, Stores, or Restaurants'] | ['blackrock', 'dialogflow', 'javascript', 'ncr', 'python', 'react', 'twilio'] | 20 |
10,371 | https://devpost.com/software/junction-73w64o | Utilizing Gamification, we provide powerful incentives for users to support their local businesses
Home page of the web app built using Next.js
The welcome screen lists restaurants that are nearby, "For you" restaurants, and restaurants with low wait times
A list of restaurants nearby gives users plenty of options
Once clicked into a specific restaurant, users can very easily order food through 3 delivery options
Restaurant analytics provide tools for local businesses to see what users like to eat, who the regulars are, and types of popular deliveries
Inspiration
We wanted to create an easy to use application that does not
only
cater to consumers. Because of COVID-19, small businesses in the area are suffering, and it is hard for them to optimize their supply chain process. One of the team members went to a local donut shop and bought a few donuts early in the morning. The store owner seemed flustered and began mentioning how she has seen a recent uptick in sales for vegan donuts. She was not prepared to handle more vegan donut orders than originally predicted and wished she knew beforehand that this would be an issue. Thus, Junction was born. The goal was mainly to come up with an idea to help merchants not only gain business during a time that is tough for small business owners but also to provide merchants with data to optimize their supply planning. We created an app that can be accessed as a consumer or merchant. Both parties are benefitted by Junction.
What it Does
Consumption Junction, what is your function?
Junction connects merchants and consumers through one platform. On the merchant side, Junction tracks data of times for peak sales, commonly ordered meals, and regular orders, and displays these figures for the merchant to better optimize their supply chain needs. These metrics make it easier for a business owner to take advantage of specific foods or times that can increase their profits.
On the consumer side, the app allows the user to view restaurants and order food as usual. Additionally, users are provided with updated data regarding time to receive an order, whether it be through dining in, pick up, or delivery. Aiding small businesses at a time of need is crucial, so the app from the consumer side ties in incentives to encourage users to try eating local.
How We Built It
The prototype for the consumer side of the Junction app was built using NCR’s Figma design. Junction was then implemented for both the consumer and merchant side using JavaScript and Next.js. NCR’s business services API was used to test API calls sent into the Next.js API routes. These API routes would connect to Google’s google-auth-library to authenticate a service account with a JWT, thereby allowing us to read and write off of a Google sheet as a backend for order history. Python was used to pull consumer data from Google Sheets to visualize the data for merchants through matplotlib.
Challenges We Ran Into
Overarchingly, challenges we faced included lack of time and lack of prior knowledge. As we came up with an idea, we recognized that it would not be the easiest to achieve with the computer science we strictly learned in school. In just a small amount of time, we would not only have to finish our project, but also learn about how to implement new resources along the way. This was a major challenge for us all.
Accomplishments that We're Proud Of
This was the first time any of us have used Figma to create a professional prototype. We are also proud that we were able to learn how to utilize NCR's API and quickly use it to implement a functioning web app. Most importantly, we are all proud of how we picked up skills we needed to utilize to reach our end goal. Once we had a theme and a goal decided, we went at it with full force. On several occasions, we stumbled and realized we did not know exactly how to attack an issue. One such example was when Google's 'google-auth-library' didn't interact well with Next.js's API routing. However, we did not waiver on our topic or end 'goal' just because of a lack of prior knowledge. When we had a lack of order data in our Google sheets backend, we created Python scripts to generate thousands of sample order data to input in the sheet. When we struggled to implement an ordering system into our webapp, we researched React hooks as a solution. When we dealt with time restraints, we honed in on what really matters to Junction--providing resources for local businesses. As time went by, we learned how to use several additional resources to complete our project within the time constraint and to the best of our ability.
What We Learned
We learned important design principles from NCR’s design workshop, which were immediately implemented when using Figma. From an NCR workshop, we also picked up the importance of making apps for consumers more exciting and interactive. Gamifying was a concept we were drawn to and decided to implement in our prototype. Our ‘game’ revolves around collecting ingredients needed to bake a cookie (which is the equivalent of completing the challenge). The ingredients are only collected by completing a series of events which include ordering from local restaurants, leaving reviews, and more. After completing these tasks, the user will receive a reward such as in-app credit. We also learned React hooks, Python's matplotlib, Next.js, API routes, Postman, and Heroku hosting.
What's Next for Junction
Now that we have thoroughly thought through our idea, we know just how passionate we are about it. We aim to extend and implement the functionality shown in the prototype on Figma. This would make Junction a more comprehensive platform, and hopefully a platform that is beneficial and aesthetically pleasing. Our overarching goal, throughout all changes, is to make sure Junction caters to communities and people that we feel need the most help at this time.
Built With
api
css
figma
google-spreadsheets
googleapis
html
javascript
matplotlib
ncr-business-services
ncr-design-system
python
react
react-spring
Try it out
github.com
www.figma.com
junctionhackgt.herokuapp.com | Junction | Junction's purpose is to not only create a robust user experience for consumer food ordering but also to help local restaurants thrive in the process by providing consumer purchasing analytics | ['Aidan Donelan', 'Andrew Xu', 'Aditi Bhatia', 'Paula Punmaneeluk'] | ['NCR: Develop a disruptive and innovative solution that solves at least one of NCR’s most significant problems for Banks, Stores, or Restaurants'] | ['api', 'css', 'figma', 'google-spreadsheets', 'googleapis', 'html', 'javascript', 'matplotlib', 'ncr-business-services', 'ncr-design-system', 'python', 'react', 'react-spring'] | 21 |
10,371 | https://devpost.com/software/scrubs-improving-nursing-communication | Heat Map representing patient request patterns, made using MongoDB
Ideation
During our ideation process, one of the first things that we were able to relate to as a group is the unique perspective we share regarding the COVID-19 pandemic. All three of us have at least one family member who currently works as a frontline healthcare worker, and so we immediately bonded over our appreciation for those putting themselves at risk in order to save the lives of others. We knew coming in that there would be a lot of teams focused on building apps for contact tracing and early diagnosis, but we felt that a more powerful way to make an impact would be to make something that benefits healthcare workers and medical professionals.
Challenges
Our first challenge wasn't so much technical, but more based on the direction and scope of our project. We were tempted to build an All-In-One All-Inclusive Round-Trip type of super app but we realized that there were two problems there: One. We're not that cool. Two. We wouldn't be helping nurses and doctors in an efficient, productive way. Instead, we targeted a specific problem in nursing units that we felt caused the most distress to both nurses and patients, and that was the patient call system. Literally, some of the current paging systems in use collect dust as the unit secretaries use them. We decided to build a streamlined system that could drastically improve the workflow and communication of nursing units, and off to the races we went.
Codebase
We built the mobile app using React Native, and both the server and desktop program were built in Java. We also utilized tools such as Node.js, Express.js, and MongoDB.
Learning is cool
Through the ideation and development process, we were able to learn a lot about finding an audience and knowing that audience and what they want/need. We also learned that its important to pinpoint problems in order to develop solutions that make sense and carry impact. From a technical perspective, we were able to gain experience working with servers and sockets and all that backend jazz. We also learned that sleep is important zzzzzz.
Built With
express.js
java
javascript
mongodb
node.js
react-native
socket.io
Try it out
github.com | Scrubs | Helping Nurses Help Us | Streamlined communication platform designed specifically for health care staff, aimed to fix the outdated call system used in current nursing units for patient requests. | ['Elias Izmirlian', 'Matthew Li', 'GarrettGularson'] | ['Anthem: Personalized, digital medicine in the age of COVID and beyond'] | ['express.js', 'java', 'javascript', 'mongodb', 'node.js', 'react-native', 'socket.io'] | 22 |
10,371 | https://devpost.com/software/hospital-buddiez | Inspiration
COVID isolation has given us a sense of what patients confined in hospitals must feel like. The limited interaction and the physical barriers has inspired a solution of contactless connection among not just COVID patients, but all patients alike. Connecting people together who are able to empathize with each other's situations is incredibly valuable and may provide some sense of relief for those who cannot easily reach out for support.
What it does
Hospital Buddiez provides patients who are admitted in a hospital a safe space, allowing them to connect with other patients through forums, events, or direct messaging. It also allows them to stay up to date with recent events, find social activities, and make new friends during their stay. Past patients can also share their experience and insight about their stay, helping current patients get through a hard time.
How we built it
We created a mock up of our ideas and developed them on Adobe XD. As we expanded on details, we made use of PaintTool SAI, an advanced drawing and editing tool, to edit certain photos and tailor them to our project.
Challenges we ran into
As we were brainstorming our ideas for this challenge, we had to decide upon the scope of our app--would it be a global, country-wide, or hospital-limited application? This rose more questions we had to dissect and consider carefully such as: Who was our app really for? What are the security risks? What are we promoting? Who is able to use this app? In the end, we agreed that our audience of patients is a vulnerable population, and keeping their anonymity and comfort was our priority. On a global scale, anyone who isn't a verified patient would easily be able to target, harass, or scam patients, which isn't the vision our team had. We wish to provide a safe space, and on a hospital-limited scope, this is possible.
Accomplishments that we're proud of
That were able to apply classroom ideas to the real world
That we could cohesively develop, filter, and mature shared ideas into a single application
3AM submission
That we could have a working prototype with no back-end involved
What we learned
Prototyping and complex wire-framing
How to effectively discuss and filter ideas
Time management and accountability
Power naps increase productivity
What's next for Hospital Buddiez
As mentioned above, expanding the scope of our project from hospital-wide to global would raise several new concerns that cannot be addressed at this time; however this is a potential direction our project may take in the future, as beyond creating more functionality to our application, finding ways to include more patients outside of a hospital setting would be a goal, as physical therapy, mental health, and senior center patients are just some of the population that may find use and companionship through this app.
Built With
adobexd
paint-tool-sai
Try it out
xd.adobe.com | Hospital Buddiez | An app that connects patients across and within hospitals. | ['Heather Zhu', 'George Ye', 'Shaan Gill', 'Anna S'] | ['Anthem: Personalized, digital medicine in the age of COVID and beyond'] | ['adobexd', 'paint-tool-sai'] | 23 |
10,371 | https://devpost.com/software/anytime-healthcare | Landingpage
Patient Dashboard
Homepage
Swagger APIs
Application Architecture
Inspiration
Our inspiration for this idea stems from our passion for utilizing technology to develop solutions to remove barriers for healthcare businesses as well as expanding healthcare services to populations that are underserved. We wanted to provide more options for doctors in how they run their practice and how patients receive their care.
What it does
It cuts the overhead cost of running a traditional private healthcare practice, gives doctors and patients more flexibility, as well as provides jobs, and expand healthcare to underserved populations. Anytime Health removes the need for a physical building and administrative employees. Anytime Healthcare allows doctors to work 100% remotely by doing appointments virtually and relying on door dash-like Medical Assistant Drivers (MAD) to arrive at patient’s home’s to perform the tests that the doctor would not be able to perform virtually. Both the providers and patients get to enjoy the flexibility of picking a time slot without being restricted to the traditional 9-5.
How we built it
In order to serve the web interface/client, we have a backend layer which is going to act as an orchestration layer and help us to integrate and utilize the NCR supplied APIs to bring in end-to-end consumer/customer experience.
It helps us to perform the following activities:
1.Onboarding new doctors/medical practitioners.
Creating user accounts for people who want to use this platform for online medical services.
Medical service request management and delivering PPE kits to the customers/patients.
We want to make this an interactive platform between consumers and single medical practitioners.
Tech stacks used are :
Springboot
Docker
Java
Microservices
Postgres DataBase
What has been done :
We have implemented an end-to-end interface of how the admin is taking the input of doctors details
Challenges we ran into
Limited time, Learning new technologies
Accomplishments that we're proud of
We created a minimum viable end to end product. We received a lot of positive feedback for our idea.
What we learned
AWS Services, NCR APIs, Material UI, Springboot
What's next for Anytime Healthcare
Moving forward, we hope to implement more features including an implementation for the patient portal, a medical assistant driver (MAD) portal implementation, an Uber-like GPS System to help MADs find patients, as well as a transaction system.
Built With
amazon-web-services
bsp
css3
docker
figma
html5
java
microservices
mockflow
ncrdesignsystem
postgresql
springboot
Try it out
github.com
docs.google.com | Anytime Healthcare | Helping doctors thrive in their healthcare business while minimizing overhead costs, providing employment opportunities, and expanding healthcare to underserved populations | ['Lucas Zhang', 'Deneesh Narayanasamy', 'Himaja Sri Cherukuri'] | ['Anthem: Personalized, digital medicine in the age of COVID and beyond'] | ['amazon-web-services', 'bsp', 'css3', 'docker', 'figma', 'html5', 'java', 'microservices', 'mockflow', 'ncrdesignsystem', 'postgresql', 'springboot'] | 24 |
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