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10,522 | https://devpost.com/software/fitspace | Problem Statement
A potential challenge during the pandemic outbreak like COVID19 is overwhelmed hospitals. At present, the hospitals don’t have the capacity for large number of incoming patients. There is a need for a technology platform which is capable of remote-monitoring and allowing for the engagement of patients in their homes. The capabilities also facilitate communication between quarantined people and the healthcare service and maintain visibility of those recently discharged. The capabilities to monitor the chronic patient
Proposed Solution
It offers an ideal way to monitor patients while they are in quarantine or at home. The platform offers an end-to-end solution all the way from devices to central command center dashboard and analytics along with managed services. The device hub include those that measure vital body temperature, heart rate, blood pressure, SPO2 level in the blood. If the patient clinical situation deteriorates, the system, supported by health-workers oversight, can respond rapidly through central command center and decide if they need more intensive levels of medical care. At the same time, providers are at no risk of exposure to COVID-19 when they manage a patient remotely. It is highly important to preserve a healthy clinician workforce at any time and especially during a health crisis like COVID-19. During this public health emergency, it is imperative that the Government and healthcare system adapt as the situation warrants to act upon measures to save lives.
Implementation
If small Patient Monitoring could be connected to a network wirelessly, patients would be able to move around freely while their physiological signals are monitored. Thus, medical personnel could be informed about a patient’s critical condition regardless of their whereabouts and they could be treated promptly if an emergency occurs. Furthermore, portable devices can be integrated into the Healthcare environment and used to develop novel applications. Thus, we will develop a portable embedded device that can monitor the condition of patients in real time using biomedical sensor network such as sensor is pulse oximeter (SPO2), thermometer, respiration, blood pressure (BP), and provide various physiological signals via wireless communication so that the physiological signals may be monitored remotely Based on the graphic display (android Smartphone) and web, using Web Server and Database subsystem we can take physiological signals data any where in the word at any time and this device detect emergencies and inform medical personnel when they occur. Thus, medical personnel could be informed about a patient’s critical condition regardless of their whereabouts and they could be treated promptly if an emergency occur
Expected Result
Thiswill help to ease of access to patient data. It will help to deliver high quality care to the more patients. It will help to exposure to healthcare staff. RPM is a patient monitoring system. It collects the physiological signals of patients using biomedical sensors network and processes them so they can be interpreted easily by medical personnel. Unlike conventional patient monitoring, RPM is small, portable, battery operated, and based on wireless communication. Thus, our device could be useful in a Healthcare environment where the remote monitoring of patients is essential.
What we built during this hackathon
Backend - Node.JS
Database - Google Firebase
UI - HTML/CSS/JS/Bootstrap
DevOps - Docker
UI/UX design of watch
Challenges I ran into
Firebase Admin to register users, save and fetch data
Setup Google VM instances, especially configure firewall rules for the VM
What I learned
Creating Google VM insances, HTML, Bootstrap, CSS and Data visualization.
Action Plan after the Hackathon
After the Hackathon, we will develop the idea further and standardize decisions regarding supply and distribution with the platform. With adequate funding, we will launch this product within 5-6 weeks after the hackathon
Built With
bootstrap
css
data-science-toolkit
docker
domain.com
ejs
firebase
google-cloud
html
javascript
node.js
ui
ux
Try it out
GitHub.com
rheain.invisionapp.com
35.223.13.234
fitsafe.space | FitSafe | Monitoring the vital signs | ['Vineet Ranjan', 'Manish Dwibedy', 'Ekta Gupta'] | [] | ['bootstrap', 'css', 'data-science-toolkit', 'docker', 'domain.com', 'ejs', 'firebase', 'google-cloud', 'html', 'javascript', 'node.js', 'ui', 'ux'] | 52 |
10,522 | https://devpost.com/software/lexconnect-wio92b | Title
Main Screen
Send Text data
Recieve Text data
Inspiration
Let's start with a story
When a stranger asked Lexa if her if she could send a file she did so and that was the beginning of a nightmare. Vulgar calls from multiple numbers at ungodly hours... The constant
dread
when the phone rings.... Like Lexa thousands are
traumatized by cyber bullying
. If only Lexa had shared the file without leaving her digital footprint....
Enter LexConnect
LexConnect is an open-source tool developed by Hrishikesh P with the vision of
NO STRINGS ATTACHED
data transfer. LexConnect transmits data using audio which makes it easy and safe to share it with strangers as it
leaves no digital footprint
if used wisely.
No more fear
of the stranger getting your phone no: or email id or even taking the risk of allowing them into your LAN. As of now,
text
and
music
can be transmitted.
LexConnect is also a
data-broadcasting
app which allows you to easily send data to a room full of strangers.
Motto
The motto of LexConnect is to help
reduce the risk of cyber-bullying
and
increase women safety
.
LexConnect also aims to make
data-broadcasting
easier.
Creativity Factor
LexConnect is the
ONLY
app of it's kind. As it uses sound as a medium it is compatible with all electronic devices having a microphone and speaker. This also makes plausible digital footprints like phone no:, email id, LAN etc. unnecessary. Thus, transmissions can be 100% anonymous with no way of tracing the source back to the sender.
What's next for LexConnect
Being open-source I hope LexConnect will be able to transfer more kinds of data. I myself shall work on
predictive audio-based image compression
in the coming days. The goal is to make LexConnect the Xender of the audio world.
Tech Stack used
Tech stack comprises of React, JS, & plain old HTML.
How it works !
Data is first encoded using a Rot cipher and then converted to respective audio signals which is then compressed using Fast Fourier transforms. These signals are then transmitted via the sender's speaker. The signals are captured via the receiver's microphone and are decompressed and the encoded text is obtained which is then decoded using an inverse Rot cipher.
Challenges I ran into
Where should I start ;) This is my first React project. I spent ours trying to figure out the enmity between github pages and React routes :(
I had a lot of trouble figuring out the
optimum data-transfer method
that could be implemented in a day! I spent a lot of time figuring out a way to make the audio unique but finally realized that a better algorithm would be to make the data encoded and the audio ordinary. This makes the app accessible irrespective of the speaker and microphone specs at the same time making the data secure.
Accomplishments I'm proud of
Building something that helps in making the world a
safer place for women
and making an effort to reduce cyber-bullying these are the 2 rewards I have gained during this hackathon. Nothing compares to helping others and
that is a reward in itself
.
What I learned
I have
tasted the joy of social service
. This was my first React project and I learned the beauty of the Virtual DOM. The renders are so satisfying !!!
Built With
javascript
react
Try it out
github.com | LexConnect | Prevent cyber-harassment of women using anonymous data transfer | ['Hrishikesh P'] | ['Best Anti-Cyberbullying Project'] | ['javascript', 'react'] | 53 |
10,522 | https://devpost.com/software/media-tracker | Inspirationfrom general
What it does
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for Media tracker
Built With
python | Media tracker | It is used to track media | ['SUMIT Sumit Lovanshi'] | [] | ['python'] | 54 |
10,522 | https://devpost.com/software/dart-nfc-reader | dart-nfc-reader
Read the activation date from a DART NFC pass.
Built With
android-studio
java
xml
Try it out
github.com | dart-nfc-reader | Read the activation date from a DART NFC pass. | ['Mann Ashish Bhatt', 'Corey Rowe', 'Tobechi Maduchukwu', 'Karl Zhu'] | [] | ['android-studio', 'java', 'xml'] | 55 |
10,522 | https://devpost.com/software/phrasor | Japanese
Korean
French
Inspiration
I always enjoyed learning different languages as a kid. In elementary school I printed a book of common phrases I found online based on languages I wanted to learn.
While this program is just used to display common phrases for languages such as; German, Japanese, Korean and French. Users will be able to look up a certain term based on their input.
I built the script the script using Pycharm using def and numerous if statements.
A few challenges I ran into were in the if cases. Originally a user would be able to select their language and type in the phrase they would like to translate into a selected language all using string.
When a user tried typing 'hello'
it would display 'hello' for all the options instead of one.
I am really happy how it turns out - i've never used python before so being able to complete this personal project made me super happy
Phrasor's next step is to not depend on if statements and use a translator api that will allow a user to add their on phrase and pick from multiple languages.
Built With
python
Try it out
github.com | Phrasor | Want to be able to look up a phrase in Japanese or Korean or French or Germen this script is for you | ['Taylor PB'] | [] | ['python'] | 56 |
10,522 | https://devpost.com/software/linkhub-event-app | Search Screen
Login Screen
Home Screen
Profile Screen
The Problem
Ever since the pandemic, we have become out of touch with each other as it relates to socializing. We crave conversation, the joy and laughter but we are trapped inside with no one to contact except a group of friends.
Proposing the Solution
LinkHub is the application that allows users to create virtual events to host online parties. These parties can be public to everyone or private to a reserved list. Each user is able to create an event, search for an event and view trending events.
Project Scope
A user must be able to create an event.
A user must be able to view an event.
A user must be able to search for events based on categories (Gaming, Networking, Partying).
A user must be able to share a livestream link to a third party service (Twitch, Youtube).
A user must be able to edit and delete events.
Design
I created the mockups using Figma. I have included them in this posting. I also wiredframed the application with pen and paper to determine how much I could implement within this period and what the full scale of the application would look like.
Tech Stack
The proposition was to use React as it would be fast to use Material UI to create the interface, then use Google Firebase to host the service and use cloud functions to make the app come to life. React is an optimal tool as Vanilla JavaScript can become tedious to maintain when scaling. React also has support for Material UI to make the website look more modern (though this could be achieved with Bootstrap in Vanilla Js). Server-side programming would be challenging so GCP services would be used to leverage the work of having to create server endpoints and consume APIs to get a similar result to a Google Cloud Platform service like Cloud Functions and FireStore. Not to mention, creating a custom backend also requires a database. Why create just a cloud database when I can also use the cloud platform to ease development
Challenges
Internet connection was a huge problem. The Material UI Kit I wanted to use did not work and I was struggling with just the UI for the majority of the hackathon due to my poor front end skills and the lack of documentation and tutorial videos. I am not the best at creating UIs so I figured using a template would speed things up, but it ended up costing me the project. I was not able to implement Firestore or Cloud functions because of the limited time. If I could go back in time, I would've stuck with basic CSS and JSX.
Evolution
In the future, I plan to implement authentication as well as third party links to Discord, Zoom, Skype and Google Teams meetings for the virtual events. I also intend to achieve the full scope of the project requirements over the course of six months.
Closing remarks
I thank the GrizzHacks team for this opportunity to participate and I look forward to your critique!
Built With
firebase
html
javascript
react
scss
Try it out
github.com
linkhub-events.web.app | linkhub-event-app | The application that allows users to create virtual events for strangers to attend for networking, gaming and partying. | ['Mark J'] | [] | ['firebase', 'html', 'javascript', 'react', 'scss'] | 57 |
10,522 | https://devpost.com/software/linkup-yr67x5 | Inspiration
In a time of great isolation, people are yearning for social interactivity and for things to get back to normal. Seeing the rise in mental health issues, we asked ourselves how we can provide a fun way to connect people back together.
Our passion for sports and the
research-backed
claims of physical activity improving mental well-being, led us to build - LinkUp. The platform that brings people together and encourages physical and mental well being.
Our app was built with a focus on fulfilling the needs of many. We not only wanted to promote mental well being by encouraging physical activities but we also wanted to help people make new friends through our app and form life-long connections.
We wanted to reach people who didn’t know many people around them or people who just moved to a new area and want to know if anyone plays their favourite sports or even people that just wanted to try a new sport. LinkUp was built with everyone in mind!
What it does
LinkUp is a Mobile app that bridges the gap between people and sports allowing them to meet up, become friends and enjoy sports together! LinkUp offers the users to enter in their favourite sports and allows them to create or join events for it.
The mobile app looks for nearby events and finds users the perfect sports event they would be interested in. It does this by filtering the events to match their interests, age group, gender and location.
Once users join or create an event, they can chat with others who are attending and get to know them before they link up. LinkUp allows users to add others as friends after they have played with them. Friends can then invite each other to future events and get together to have a great time.
How we built it
We knew from the beginning that this project would be an undertaking. So we prepared with a mockup (using Figma) for what the mobile app would look like and created a Trello post for all our ideas.
We decided to leverage Firebase and Firestore to handle our authentication and backend storage solutions. This allowed us to develop quickly and get many features done without needing to write REST endpoints for basic data retrievals.
Our front-end mobile client was built using Quasar and Vue.js. We use cordova plugin to build and deploy our mobile apps. Quasar also supports deployment to desktop and web, and so our app supports multiple platforms.
Challenges I ran into
While most of us were experienced with basic web app development, only one of us used the framework we decided to use which was Vue.js and Quasar. This was challenging for us in the beginning, but with our collaboration and guidance by our experienced member, we were able to quickly learn the basic and help out.
We also ran into problems when it came to geo-encoding location data with OpenCage, but one of us figured out how to encode it back to address form and that provided us with the proper format for parsing.
Accomplishments that I'm proud of
We are proud to have built an end-to-end solution using real backend and geo-encoding APIs like Google Maps and OpenCage to provide real and relevant data. Despite being new to the framework Vue.js we were able to build something that not only works but also provides value by solving problems of many.
What I learned
Working with Vue.Js with Quasar, Figma. Integrating Firebase Auth, Firebase database with Quasar and Vue.js. Importance of UI/UX. And non-technical things like collaboration, teamwork and supporting each other when faced with challenges.
What's next for LinkUp
We believe that LinkUp can truly help bring people together to form life-long connections through a common interest in sports. That is why we plan to finish the mobile app with all the features and add some features that we were not able to finish such as:
Providing daily challenges to keep users engaged and promote a healthy lifestyle
Gamify challenges among friends and given rewards if friends plan X amount of event
Assessing machine learning models to improve event suggestions and connect people with similar interests and background.
Built With
figma
firebase
firestore
javascript
quasar
vue
Try it out
github.com | LinkUp | LinkUp is a Mobile app promoting physical and mental well-being by bridging the gap between people and sports - allowing them to meet up, become friends and enjoy physical activities together! | ['Amitesh Thind', 'Shardool Patel'] | [] | ['figma', 'firebase', 'firestore', 'javascript', 'quasar', 'vue'] | 58 |
10,522 | https://devpost.com/software/motivational-website | Inspiration
During these trying times it may be hard to get the motivation needed to have a positive day. Some people don't have super positive affirmations that may push you to having a better day. I feel very inspired reading various quotes and I feel like other people do too.
What it does
Right now all there is a basic UI layout that links to a few pages that need to be implemented later.
How I built it
I used react.js and node js for the front end development. I plan to learn how to do backend development and use go to link data to databases. I am curious to see where this project will go. I want to get more familiar with web dev apis. I would like to set up a API call that sends automated emails.
Challenges I ran into
While learning my first project in web development, I was confronted with many choices on how to go about doing so. I googled coolest tech stack to start off web development. I saw that react and node js was the way to go😁. After going through hours of tutorials I am happy to say I am familiar with the front end development portion of web development. With this newfound knowledge I will continue to work on this project and many more.
Accomplishments that I'm proud of
I am happy on how pretty my first website turned out. It is a little rough around the edges but I am proud that I stuck my way through.
What I learned
I learned that trying new things when it comes to technology is necessary to keep up with technology. I also learned that it is beneficial to learn new things about tech while still focusing on more traditional computer science classes.
What's next for Motivational-Website
I will add more features as the days go on. I hope to host a domain and get users on the site. I would like to use this website to spread positivity in small portions.
Built With
css
html
javascript
node.js
react
Try it out
github.com | Motivational-Website | This is just the homepage for a website that focuses on motivating messages. Eventually I would like for people sign up via email or text messages to receive positive messages every day. | ['David Rodgers'] | [] | ['css', 'html', 'javascript', 'node.js', 'react'] | 59 |
10,522 | https://devpost.com/software/grizzly-bears-and-quines | Original image, credits to where it's due to University of Oakland.
The final result in all its pixel glory, plus the lyrics of Oakland's Fight Song
Inspiration
I'm proud t' say that be GrizzHacks 5 is me first GrizzHacks exped'tion. 'tis is such a pleasure t' experience thar thrill and exc'tisement as did me otharr friends who have experienced previous GrizzHacks exped'tions. In commemoration, me crewmate and I decided t' Pillage one o' our favor'tise quirks in programming: quines that be are shaped int' something.
What 'tis does
Basically, a quine is a "self replicating" program that be takes in nay input, and outputs 'tisself. Here, I t'ok thar GrizzHacks bear mascot and converted 'tis int' ascii and put 'tis inside thar quine and made 'tis print 'tisself in thar terminal. Ye can see all thar code and thar final image in thar terminal just by running thar python program. 'tis's that be simple.
How I built 'tis
A quine is classified as a program that be takes nay input and outputs a quine. Hoour jolly crewver, a quine should nay use any 'open()' function t' print out 'tiss source code, ratharr 'tis must print out 'tiss own code via print statements or otharrwise. Using an 'open()' function would be considered cheating, in a sense. What I did was t'ok thar ascii image o' thar GrizzHacks mascot and put inside a string. tharn, I tried t' duty out thar character escapes and nayation inside thar string t' be printed, so that be 'tis can print 'tisself. dis is perhaps one o' thar easiest ways t' create a quine: t' define a string, tharn put thar string inside 'tisself w'tis' string Fermatting. Unaybfuscated, Ye can clearly see thar GrizzHacks bear mascot
as our jolly crewll as
thar code used t' make 'tis. o' which, include thar character escapes, thar string that be is printed, and thar variable st'ring that be string.
Challenges I ran int'
Fer one, I wanted t' do something different than otharr quines, something more extravagant and pretty. I tried looking Fer glyphs that be might help me in representing thar bear in a fashionable way. I used tharse wh'tise glyph blocks which had varying levels o' intens'tisy t' paint out thar full picture. Regrettably, 'tis still is nay how I wanted 'tis t' look like, but naynetharless, 'tis does thar job our jolly crewll.
Accomplishments that be I'm proud o'
I'm proud t' have joined dis exped'tion and participated thar likes o' which nayne o' me otharr friends have done so. I've participated in thar miniVoyages, thar talks... Everything was a blast and I'm proud t' have made dis quine in commemoration.
What I Looted
I Looted how t' create a quine, how t' output text in color in thar terminal and how hard 'tis is t' create a true quine that be is shaped and looks like something discernible.
What's next Fer Grizzly Bears and Quines
I plan t' utilize what I Looted about terminals, quines, and shaping o' quines t' try t' make 'tis animated. If tharre's one thing everyone is nay doing, 'tis's making quines animated. Can Ye believe how hard 'tis actually is? 'tis's mind bogglingly hard. But I still plan on animating Grizzly Bears and Quines, just watch me try and inev'tisably fail.
Built With
ascii
bears
python
quines
Try it out
github.com | Grizzly Quines | When the big GrizzHacks bear meets quines... | ['Shaedil Dider'] | [] | ['ascii', 'bears', 'python', 'quines'] | 60 |
10,522 | https://devpost.com/software/teleclinic | Appointment Creation
Zoom Call
Appointments and Schedules
Inspiration
COVID-19 has impeded doctors from providing safe and quality healthcare.
With over 6.8 million cases and 200 000 deaths
in the United States, including
1 000 frontline healthcare workers
, this pandemic has posed a serious issue to the wellbeing of society. Teleclinic hopes to curtail the spread of coronavirus by reducing contact between patients and doctors. A system that allows clinical appointments and checkups to be conducted remotely is necessary in our current times. Although there are strict sanitary policies at hospitals and clinics, there is still risk involved for those who visit due to the concentration of sick people. We wanted to limit exposure especially for those who are at risk for coronavirus.
What it does
Teleclinic provides users with a convenient platform to schedule medical appointments, enter queues for walk-in appointments, and connect with their doctor through Zoom. Users first register with their emails and health card numbers and log in. Afterwards, they are able to schedule an appointment by going to the online calendar and selecting a date and time. If they need more immediate care, they can see estimated wait times for walk-in appointments and add themselves to the queue. Once a doctor is able to see them, they will be sent a Zoom link that connects them to the automatically generated Zoom call and can remotely receive quality healthcare.
How we built it
A variety of frameworks and technologies were used to create our web application. The frontend was built with the Vue.js web framework as well as Vuetify to help create the UI. The backend made use of Node, Express, and SQL to handle database queries and general logic. We used the Zoom API to automatically create a meeting for the doctor that is password protected for each patient.
Challenges we ran into
There were many CORS errors that we had to debug during the integration of the frontend and backend. There were issues with Zoom permissions that we had to work around as Zoom required for our app to be verified by them to give us full access.
Accomplishments that we're proud of
Integration of the Zoom API is something we’re proud of as this is the first time we’ve been able to use an API by solely relying on documentation without watching other tutorials or finding code online. We also learned and were able to integrate oauth2 and understand the authflow for the Zoom API. The UI also turned out quite well and is another thing we are proud of.
What we learned
We learned a variety of things such as Oauth2 authflow, different time formats such as Unix, ISO standard and how to obtain the different values, how to make efficient requests and manage a PostgreSQL database, and how to use these databases to connect clients through an automatically created zoom call.
What's next for Teleclinic
In the future, we plan to scale to project to allow multiple organizations to register with our application and have their own scheduling.
Built With
express.js
javascript
node.js
postgresql
sql
vue
vueitfy
Try it out
teleclinic.netlify.app
github.com | Teleclinic | Online medical clinic for your appointments and walk-ins. Get your appointment today! | ['Nithin Muthukumar', 'Nick Liu', 'Zhehai Zhang', 'Anish Aggarwal'] | [] | ['express.js', 'javascript', 'node.js', 'postgresql', 'sql', 'vue', 'vueitfy'] | 61 |
10,522 | https://devpost.com/software/hashhack | Inspiration
There I was, hunched over my laptop at 2AM when divine inspiration hit me. In my sleep-deprived state I had entered in the wrong password in the "confirm password" box for the fourth time in a row. In my sleepy-stupor I grumbled at my computer, who was just doing its job,
"Incorrect password... It's
my
password, I know it's correct. I'm not an imposter, just let me in! What do you know anyways, dumb computer, you don't know my passwords..."
I paused for a moment... surely it did have to know my passwords, or else how was I ever able to get into my accounts?! That's when the idea of HashHack hit me. I wanted to learn how passwords were stored and secure, so why not make my project out of it!
I've wanted to go into cybersecurity for awhile now and I figured why not try my hand at a simple Python project using some cybersecurity concepts? I chose Python because it is simple and widely used in cybersecurity, so I was happy to get some experience in it.
Also I wanted to call myself a hacker, even for just a day.
What it does
This code right here is a piece of machine magic. It's a mind reading machine that can crack the passwords of anyone! Anyone who uses bad passwords, that is. But, as a humble and generous woman, I decided to bestow that knowledge unto others. Weep not, for you too can learn the ways of hash hacking.
This comprehensive collection of condensed and concise colorful code explains to the user what hashes are, and then takes them on a demo of the three most common hashing methods.
It individually explains hashing methods in an interactive way, and shows how passwords can be found using brute force attacks. In HashHack v2.0, I will implement AI so the program will even ask you about your day. So thoughtful!
How I built it
Python, Google, and a whole lot of patience. And love <3.
I started HashHack as a more personal learning project, mostly to see how different hashing methods worked and what outputs they gave. Then I stopped being so selfish and decided to give back to every wonderful person who also wanted to learn about hashes! (or whoever would be forced to judge this).
As I worked, it evolved into the glorious teaching tool that it grew up to be, and I am so proud of my child.
Conveniently, other people must like hashes too and decided to make some Python libraries for it, which made my life very easy.
Challenges I ran into
I don't pretend to be a programmer, so given my lack of hardware to use instead, I expected this project to crash and burn. Boy was I wrong! Look at this thing! It's glorious!
Starting out, I didn't know anything so I was just running around in a room full of purple Google links. Eventually, I gained more knowledge and resolved any errors or glitches that I had.
The two main factors that almost spelled my defeat were time and fatigue. I frantically ticked and tapped at my keyboard, looking at the clock periodically, watching time fly by. My eyes demanded rest, and my fingers refused to respond. But I pressed on! This project was too important to waste time doing menial tasks like "sleeping" and "eating". NO! I MUST TEACH THE MASSES ABOUT HASHES!!!
Accomplishments that I'm proud of
I DID IT! I fully expected to give up halfway through and further my stance of hating coding. But I loved this and the concept and I'm so happy I took the time to learn this and commit to the project. I did my first Hackathon and I did it solo!
I'm gonna print out my code and pin it on my fridge :)
What I learned
During this project, I learned how to love. I didn't think I would ever feel about anything the way I feel about HashHack. Its functions, its inputs, its dark theme (client-side, but still counts). It is pure perfection.
HashHack has taught me so much, it's funny to think that we just met yesterday. Ah man, the good ole days, back when they only had three lines of code and was still on light theme. Hah! HashHack has taught me about hashes in such a deep and personal way that I'd swear that
I
was a hash if I didn't know any better!
Good thing I'm not a hash though because brute force attacks would be scary. Imagine being compared to so many other inputs all the time, it can't be good for mental health...
They also taught me about their home, Python. Such a beautiful, simple place. Much nicer than other places I've been like Java, or worse C++ (shivers). Working in Python is so nice, it is laid out so simply and has so many tools ready to be used, I don't know how I was ever anywhere else!
What's next for HashHack
Please. Just a drop of GUI. I beg you. I love HashHack, but my eyes hurt from looking at it.
Built With
love
python
Try it out
github.com | HashHack | Demonstration tool for how hashes work and how to break them using brute force attacks | ['Stephanie Moyer'] | [] | ['love', 'python'] | 62 |
10,522 | https://devpost.com/software/musera | Main page of Web App
Second Page of Web App
Inspiration
We were driven by the passion to share popular music across history and engage users with our platform.
What it does
Using the top 100 weekly hits from the Billlboard Hot 100 amassing about 326,000 entries. Out of these, there are about 30,000 unique songs. The result, on Musera's website, it would output the five random songs on individual pages with the corresponding album artwork, 30-second song snippet and track title.
How we built it
Using pandas, we compiled the .csv of songs into data-frames which were then randomly sorted to produce five songs. Using Spotify's web development service we created an API in which we searched and gathered data provided by Spotify. This included cover art, audio snippets, and track titles. All of this has been performed on python. Using Django, the scripts would be hosted on Google Cloud and would interact with the front-end of the program on HTML.
Challenges we ran into
The biggest challenge we ran into was designing the API, and trying to use Django on the backend of the web application. Especially trying to run our python scripts using on-click actions on our HTML website.
Accomplishments that we're proud of
We were especially proud of this project because programming is new to half of our group. Especially designing algorithms and backend web development. It is very exciting to have gotten this far on what would be the first project for many of us.
What we learned
We learned that staying positive and working on a time crunch brings the best out of all of us. The hysteria of staying up late into the night working on a website is a tall task for most, but we were persistent and overachieved all expectations we had in the beginning of the weekend.
What's next for Musera
What is next would be trying to get django to work and host the website successfully on google cloud servers. More importantly, trying to have python programs run using HTML on-click events.
Built With
css
django
google-cloud
html
javascript
lamp
pandas
python
spotify
spotipy
ubuntu
Try it out
github.com | Musera | Musera's goal was to provide a listening experience to all music hits from the 1950s to the present day. Using a user-friendly interface and weekly Billboard Hot 100 records.. | ['Timothy Nguyen', 'Anthony Nguyen', 'Kimberly Nguyen', 'Sydney Nguyen'] | [] | ['css', 'django', 'google-cloud', 'html', 'javascript', 'lamp', 'pandas', 'python', 'spotify', 'spotipy', 'ubuntu'] | 63 |
10,522 | https://devpost.com/software/dogdegame | Inspiration
I wanted to build something for Grizzhacks this year
What it does
it is a simple game
How I built it
I initially wanted to do something else like make a website, but I got tired of that real quick. So instead I made this. I spend a few hours reading about html and javascript and found examples and stuff around the internet and then just did it.
Challenges I ran into
Positioning, getting the tiles to generate and fall, motivation
Accomplishments that I'm proud of
creating a usable product in a short length of time
What I learned
a lot about timing and motivation, and some more about a couple new languages
What's next for DogdeGame
not much, probably will do something different for next time
Built With
html
javascript
Try it out
github.com | DogdeGame | Quick Simple Game that one person could play by himself or herself. | ['Raymen Shu'] | [] | ['html', 'javascript'] | 64 |
10,522 | https://devpost.com/software/termtext | Inspiration
We wanted to be able to send SMS text messages from the command line, using a VoIP backed solution.
What it does
Sends and receives text messages. You can add a new number. Switch through conversations.
How we built it
We used critical thinking and problem solving skills. We used python as the language and Twilio as the backend API. Vim was the text editor used.
Challenges we ran into
We had a bug of duplicating messages in the conversation window. It was fixed after talking with a mentor. We also ran into some layout issues, that were fixed after looking at our working examples.
Accomplishments that we're proud of
We created a working application. We can now send and receive SMS text messages from the terminal. Creating a viable ncurses interface.
What we learned
How to create ncurses environments for terminal applications.
What's next for TermText
We want to add the functionality to add number to the "phone book".
Built With
ncurses
python
twilio
Try it out
github.com | TermText | Terminal Twilio Texting application | ['Austin Daniell', 'Sal Trupiano'] | [] | ['ncurses', 'python', 'twilio'] | 65 |
10,522 | https://devpost.com/software/hello-world-3hr26x | Inspiration
With the current situation in the world, I thought it would be great if I could create a project to encourage people to learn about other countries of the world and feel like they are still exploring the world even while quarantined at home.
What it does
The website is simply an interface where a user can select a country of the world, and then details, such as capital, population, area, and flag, pop up. There is also a link to view the country on Google Maps.
How I built it
I built the website using HTML, CSS, and JavaScript. I first make a call to the REST Countries API to retrieve a list of all countries around the world. Then I display the country names in a dropdown for the user to select. When the user selects a country, I make another call to the API to retrieve information about that specifc country and display it.
Challenges I ran into
I had trouble sizing the background images with all the flags. Also, I was stuck trying to design the UI style since I didn't want the text and dropdowns to be lost amongst the colorful background. To help with this issue, I decided to add a lot of contrast (black and white, borders) to make the content stand out.
Accomplishments that I'm proud of
I am proud that I completed a project and became more familiar with how to make API calls and connect Javascript and HTML elements.
What I learned
I learned how to connect Javascript with HTML elements. I also learned how to make API calls and parse the information to display in the HTML.
What's next for Hello World
Since the world is much bigger than planet Earth, I think the next step would be to expand Hello World to include information about various planets in the solar system.
Built With
css
html
javascript
rest-countries
Try it out
amyweitzman.github.io
github.com | Hello World | Learn information, such as the capital, population, area, and flag, about various countries around the world. | ['Amy Weitzman'] | [] | ['css', 'html', 'javascript', 'rest-countries'] | 66 |
10,522 | https://devpost.com/software/robot-rumble | Enter Player One
Inspiration
Over lockdown, we played a board games together. One of our surprise favorites was Robo Rally, a game where players "program" robots to navigate to check points and avoid each other. We wanted to see if there was a way to bring that same level of fun into a safe, real-world environment, and allow for huddling around the table with friends from the comfort and safety of one's own home.
What it does
Our project allows a player to use our website to play a game about robots with real robots! Watch your robot navigate the gameboard on the screen and then watch your robot follow those same commands in real life as they drive about our ultra-sized playing area, competing against each other. Control your robot via a handy web application for remote play possibilities.
How I built it
We broke our project into three key components. The website, the host micro-controller, and the mini-bots playing the game. For both our host and the bots we used an ESP-32 as the microcontroller since it has inbuilt WiFi and connectivity capabilities. For the connectivity side of things, the ESP-32s have a mesh networking feature built-in that allow them to pass data between themselves, which we used for a master/slave set-up to act as an interface between the robots and the Internet.
Challenges I ran into
Building several bots this small was a first for us, so we had several failed 3D prints before finally getting something that worked. Also, this was our first project tackling communication between JavaScript and microcontrollers, our first project regarding web development, our first project that involved a proper journey into graph theory, and our first hardware hackathon during these crazy times. Having all these new things, plus a tendency to bite off a little more than we can chew, made this project exceptionally difficult. A stretch goal of ours was to utilize the RGB sensors we successfully installed, implemented, and calibrated to determine the relative location of each of the robots on the field, which is just about done but not tested.
Accomplishments that I'm proud of
Creating two miniature, self-contained robots ready for anything is pretty cool. Being able to control them from the web is even cooler. Plus, this project contained a little bit of everything. Product development, app development, web development, manufacturing, iterative design, circuit design, all these things were learned and/or honed over this hackathon, which we find pretty impressive.
What I learned
Setting up mesh networks for data transfer is pretty easy once you know what you're doing. Never underestimate the awesome power of cable management and a thoroughly though-out design. Always stop and ask yourself if what you're working on is crucial to the development of the project.
What's next for Robot Rumble
Ideally, Robot Rumble was designed as a framework for games with robots instead of people. We got most of the way there during GrizzHacks, but there is still a ways to go. Developing more robust robots, strengthening the communication protocol, and enriching the web app experience are all things on our to-do lists.
Built With
3dprinting
adafruit
apache
arduino
blender
c
c++
esp32
html
javascript
node.js
xml
Try it out
github.com | Robot Rumble | Self-positioning mesh-networked robot platform for remote tabletop gaming. | ['Ian Matthews', 'Andreas Eickhoff', 'Nicholas Musienko'] | [] | ['3dprinting', 'adafruit', 'apache', 'arduino', 'blender', 'c', 'c++', 'esp32', 'html', 'javascript', 'node.js', 'xml'] | 67 |
10,522 | https://devpost.com/software/pizza-for-good | In case the Github repo links don't work for some reason, here is our repl link:
Version below displays tips at the end of the game when you deliver 10 pizzas (move over the tables multiple times and try not to hit the asteroid obstacle):
https://repl.it/@MysteriousHatte/GrizzHacks2#main.py
The Github for this code (linked in the Github field below) is registered to Supergeek57.
Version below is in the demo video:
https://repl.it/@SwabhanKatkoori/GrizzHacks#main.py
The Github for this code (linked in the Github field below) is registered to usermiia.
Why This Hack? Our Inspiration
What’s the worst part of picking up a delicious pizza on a Friday night? The place is packed, and you end up waiting in line for half an hour with a bunch of other grumpy, hangry customers. This hack was designed to solve that pressing problem by providing a new source of entertainment to take everyone’s mind off food (well, sort of) and doing some good in the community, too! During the COVID-19 pandemic, it’s important to follow social distancing protocols to keep everyone in the community safe, and we teach this in our hack by integrating a penalty when the player’s avatar collides with another person.
What Does It Do?
Our hack is a fast-paced, retro-style pizza delivery game that involves running, jumping, and dodging obstacles to get hot pizzas to hungry customers on time. During normal times, the game would only be playable in a Little Caesars store while waiting for a carry-out order, but during the pandemic, it would be available when a customer ordered directly through the Little Caesars website (not when ordering through Doordash, etc., as an incentive to order through Little Caesars). Successfully delivering a pizza to a customer by hitting the customer’s target will give the player $0.05 in tips. If a customer has to wait more than 5 seconds for an order, he/she becomes hangry, and $0.02 worth of tips are lost for that customer. The player also loses $0.02 in tips if they collide with any other people (this simulates the 6’ social distancing requirement during the COVID-19 pandemic.) The goal of the game is to deliver 10 pizzas while hitting as few obstacles as possible (each collision with an obstacle will cause the player to “lose” one pizza, increasing the number of pizzas to deliver by one unless that number is already at 10 and subtracting the most recent tip earned). At the end of the game, the amount of “tips” earned from successfully delivering pizzas will go toward either a monetary donation for a charity of the customer’s choosing, or a free pizza for a local food bank.
How we built it and how it works
We created the game in the repl.it IDE using pygame, because repl is a convenient, browser-based IDE that allows everyone on the team to collaborate on the code. Pygame is a user-friendly, easy-to-learn platform for building games in Python, which was the preferred language for our team since we all had a moderate amount of experience in it. Because we were all comfortable with the language we used, we could spend more of our time learning how to effectively use the tools within Pygame rather than reviewing Python’s syntax. In our program, we use the coordinates of the asteroid obstacle (astx and asty) and the targets (destx, desty, dest2x, and dest2y) to create a “collision test” for each of those objects. Within the “while true” loop that continually updates the game’s screen, we perform the tests and then use “if” loops to increase or decrease number of pizzas to deliver and tips accordingly. We also use “tick” within the Clock object in pygame to get the number of milliseconds since tick was last called (we call tick when the game starts and when a collision with a target occurs) in order to evaluate whether a customer is “angry” (this occurs after 5 seconds). If the time since tick was last called is more than 5000 milliseconds, the tip earned from that delivery will be decreased by 0.02.
Challenges we faced
Because most of our code needs to be within a “while true” loop in order for the screen to update properly, it was difficult to get the values for number of pizzas to deliver and tips to increment only one time for a collision. One attempted fix used the variable “times,” which used an if loop with the intent to only increment the “tips” value when “times” was less than one. “Times” would increase by one at the end of every collision loop, so that the player would have to go to a different target when they had collected the tips for that target. When all targets had been collected, all of their “times” values (times, times1, etc.) would be set back to zero to allow for more collisions. This seemed to have no effect--the “tips” value continued to increment multiple times on one collision.
Accomplishments that we're proud of
Three out of four of the members of our team weren’t familiar with Pygame before this hackathon, and we did tutorials, researched documentation, and taught ourselves enough Pygame to make an awesome pizza game in 36 hours!
What I learned
Throughout this challenge, we learned a ton about the logic and syntax of pygame, as well as the science of creating a positive user experience. This hack definitely gave us a better appreciation for how hard it is to iron out bugs from huge programs that run complex PC or mobile games.
What's next for Pizza For Good
Some refinements we’d like to make to this hack:
Add a place where customers can see their process toward a monetary goal
Add more levels, obstacles, and a vehicle component (the player’s vehicle gets upgraded, allowing them to move faster, if they spend tips throughout the game).
Add a time bonus or free vehicle upgrades for referring other customers with a unique referral link
Built With
figma
piskel
pygame
python
repl.it
Try it out
github.com
github.com | Pizza For Good | A pizza delivery-themed game that entertains hungry customers while raising money for local food banks | ['Ava Chan', 'Abu Bakarr Bangurah', 'Holland Henderson', 'Swabhan Katkoori'] | [] | ['figma', 'piskel', 'pygame', 'python', 'repl.it'] | 68 |
10,522 | https://devpost.com/software/us-police-shootings | US Police Shootings by Data
Coding Overview of Data Visualization
Inspiration
We tried to look at relevant information as it pertained to the real world, so we thought what better to crunch data on than the most prevalent hot topic:
Policing.
What it does
This project takes the total number of deaths by police in the United States and visualizes the data to break it into a few categories: Deaths by race, gender, state, age, mental illness, fleeing, and threat level.
How I built it
We used Anaconda version of Python to utilize Jupyter Notebook, which then allowed us to use libraries such as Pandas and Matplotlib.
Challenges I ran into
This project started with two go-getters and quick learners with only problems. There were no plus sides as we both nearly 9,000 miles apart completed all of these tasks via only text messaging and had the basic understanding of python. We tackled and learned every function and command line as we went, so when locating challenges, everything was a challenge that we fiercely defeated!
Accomplishments that I'm proud of
We are proud that have utilized downloaded the Anaconda version of Python which allows us to utilize the libraries. Most importantly, this was the first and successful data science project we have completed! It visualizes the data just as we have hoped for it too.
What I learned
We learned how to import libraries in order to visualize the data which was also imported from excel. We were able to clean the data, however, it was not necessary at all. We then learned to visualize parts of the graph to display the columns and variables we wanted.
What's next for US Police Shootings
What's next is that data never lies, it should be utilized by government officials, public speakers, and people in general to have the facts of policing in the United States by case for the past 4 years. Decisions should be made from visualizations of the graph and the data that it is derived from.
Read more about the issue at:
https://www.washingtonpost.com/graphics/investigations/police-shootings-database/
Built With
jupyternotebook
matplotlib
pandas
python
Try it out
github.com | Data Science: US Police Shootings | In the recent turmoil of the United States, it is brewed primarily by racism that has been fueled through Police brutality. We take a deep dive into the data science of police shooting in the USA. | ['DiekshaPriyaa', 'Omar Faruk'] | [] | ['jupyternotebook', 'matplotlib', 'pandas', 'python'] | 69 |
10,522 | https://devpost.com/software/fggfgfg | Testing
Built With
testing> | <test post | <test post of test posting> | ['Sebastian Sannes'] | [] | ['testing>'] | 70 |
10,522 | https://devpost.com/software/workder | The logo
The database workflow
Inspiration
Having submitted many work orders for my terrible dorm room, I've been quite interested in how work orders are processed, specifically on the management side. How is it that a worker can show up the next day with exactly the right tools for the job? For this hackathon, I decided to create a mock version of a work order manager with a customer side user interface.
What it does
Workder allows customers to fill out work orders and track them in real time. They fill out a form that then gets sent to FireStore where an optimized query takes place to determine the appropriate worker to send for the job. Then the worker is notified of the work order via SMS and the customer sees this information in real-time.
How I built it
Workder is built with a React Native framework with several other APIs.
Firebase was used for user authentication (and a failed attempt at hosting)
FireStore was used as a realtime database for data management
Stores Data and User Information.
GitHub was used for file management.
Netlify was attempted to be used for hosting.
Radar.io was used to target workers who were closest to the job.
Challenges I ran into
React Native is one of those tools where a lot of APIs don't really have support so everything is community made and with that comes it's own challenges. For example, I was using a dropdown component that was 4 years out of date and it had a bug where the entire app would not connect because some module was missing, but there wasn't any documentation on it. After hunting around, there was a stack overflow post saying to change the import statement to say v2 and everything fixed itself. That entire issue took an unhappy 3 hours to track down.
Another fun problem is that React Native is constantly changing and features that I may have used a year ago are now deprecated and held up by community remakes. Navigation between screens was something that I had to relearn from scratch as the update from v4 to v5 completely rewrote how navigation was done.
Deploying things that are still in beta is hard. React Native offers support for Web, but that doesn't mean there's good documentation on how to deploy it. After several failed attempts at Firebase hosting, I went with Netlify which is hopefully loaded and working by the time you see this.
Accomplishments that I'm proud of
FireStore works! I've used FireStore before, but only to query the user's name so that it could be displayed. I learned how to query a database and how to return values from it to display in my app. Coming from no database background, this was pretty fun.
What I learned
The values and perils of community built libraries.
What's next for Workder
Better integration with Radar.io
Real-time tracking of workers as they arrive
Worker user interface so that they aren't reliant on text messages alone
Admin user interface to see all the datas
Ability to submit invoices through the app
Actual deployment!
Domain.com entry: workder.online
Built With
firebase
firestore
radar.io
react-native
Try it out
github.com | Workder | A way to track work orders | ['Ramya Challa'] | [] | ['firebase', 'firestore', 'radar.io', 'react-native'] | 71 |
10,522 | https://devpost.com/software/rogue-bots-lite-72g0ef | Built using agora and unreal
First Screen
Game Play
Inspiration
Video games were once widely perceived as inherently anti-social. However, the World Health Organization, which has warned about the risks of too much gaming, recently launched #PlayApartTogether, partnering with major gaming studios to encourage people to stay home.
Around the globe, people's lives have been turned upside down by social distancing measures and even more stringent lockdowns put in place to slow the spread of the coronavirus. Some people are using isolation to explore new hobbies or finish up long-delayed household projects.
In the first couple of weeks of social distancing, I was pretty hungry for simple video chats, just getting together with friends, but over the past few weeks or so, I've really wanted some new ways to spend time with friends.
So I build this really fun game to play with friends.
What it does
It is a top-down shooter game with an only goal for the player to survive from the dangerous bots trying to reduce your health. With entering the same channel name and encryption key two players join a game. It has multiple power gadgets that help you during your game, like using the blue balls you can regain your health while the green balls help you shoot three bullets at a time, the bots keep on respawning and you have to dodge or kill them in order to survive
How I built it
With the help of Agora plugin, I was able to embed real-time video chat into my game created using Unreal Engine 4.
Challenges I ran into
As Agora SDK for Unreal is still in beta figuring out it's working was a bit catchy
Accomplishments that I'm proud of
I really enjoyed playing the game which I made with my friend, as previously my game did not use to have a video call which made it really boring for me and using Agora I got a chance to integrate video call in my games making my game more immersive and lively
What I learned
Learned about Agora SDK will use it in my future projects
What's next for Rogue Bots Lite
I will be adding a feature where players can be given an option to broadcast their gameplay directly to streaming platforms like twitch
Built With
agora
unreal-engine
Try it out
drive.google.com | Rogue Bots Lite | A super fun top-down shooter game built using Unreal Engine | [] | [] | ['agora', 'unreal-engine'] | 72 |
10,522 | https://devpost.com/software/space-pizza | Inspiration
We really love pizza
What it does
How we built it
Challenges we ran into
Accomplishments that we're proud of
What we learned
What's next for Space Pizza
Built With
css
html5
javascript | Space Pizza | Pizza in Space | ['Adam Anderson', 'Ethan Ankley'] | [] | ['css', 'html5', 'javascript'] | 73 |
10,523 | https://devpost.com/software/how-green-are-you | Inspiration
We were interested in creating a way to check if a person is making environmentally friendly choices and to provide resources. The concept was inspired by "The Good Place" and the point system in place for tracking actions.
What it does
The program runs the user through different scenarios they may encounter in their daily life and tests their knowledge of eco-friendly choices.
How I built it
We used python functions and pieced them together.
Challenges I ran into
We originally wanted to experiment with renpy but decided to use python instead.
Accomplishments that I'm proud of
It works!
What I learned
There were two Intro to Programming students on the team and they got to learn some new python skills!
What's next for How Green are You?
Maybe a translation into renpy to make it more game-like?!
Built With
python
Try it out
github.com | How Green are You? | This project walks through different daily scenarios where you can test your eco-friendly knowledge. | ['Julia Hartnett', 'Kirby Assaf', 'Maude Elovitz'] | ['Best Educational Hack'] | ['python'] | 0 |
10,523 | https://devpost.com/software/next-chapter | Inspiration
My family and I moved to America about 4 years ago and when we came here, we knew nothing. We didn't know where to shop, where to go to find a job, how to find a doctor, where to go to take out a driving license. Even the simplest task was hard for us because we had no idea. Sometimes we do hear about things but don't exactly don't know what they mean, for example, we had heard about Walmart but we didn't know what Walmart really was, is it where we shop groceries? clothes? Both? Do they high-end stuff or things we can afford?
I know that it wasn't only my family that went through this so I decided to make an app to help immigrant like us, or just people here on temporary visa.
What it does
It provides you with articles about how to do the things we need to do in our day to day life like shopping, taxes, taking out driving licenses, where to find resources to learn English, etc.
It also asks for your status, for example, if you are permanent resident or you are here on student visa or if you are here on H1-B, etc. Then, it suggests articles based on your visa status.
How I built it
Since we did not have enough time, I made a prototype using Adobe XD.
Challenges I ran into
I couldn't decide whether app would be more useful to website but I went for app for now. If this project would be completed someday, having a website too would be more efficient.
Accomplishments that I'm proud of
How it all came together
What I learned
It is hard to decide what kind of items to add to it.
What's next for Next Chapter
Make an actual app using this prototype
Make a website too for more convenience
Add more features like sorting
Built With
adobe-xd
Try it out
xd.adobe.com | Next Chapter | There are thousands of immigrants coming to America every year and not all of them know how to find the services they need, so this app provides them help to get settled in America. | ['Pragyee Nepal'] | ['Best Social Good Hack'] | ['adobe-xd'] | 1 |
10,523 | https://devpost.com/software/corona-simulator | Unity
Inspiration
Want to educate people about the pandemic and the lifestyle during it
What it does
It is an RPG-style game where the player moves around and interacts with objects
How I built it
My team and I created the game through Unity and C#
Challenges I ran into
Working with teammates on the same file
Accomplishments that I'm proud of
Working NPC
What I learned
Working on the same Unity file with others is difficult
What's next for Corona Simulator
Further development of the game, including more levels and object interactions.
Built With
c#
unity
Try it out
github.com | Corona Simulator | A 2020 rendition of The Oregon Trail where you are in an apartment during the COVID-19 Pandemic | ['pkim1334 Kim', 'Jared Antoine', 'Rylee Hooftallen', 'dsl11598'] | ['Best Storytelling Hack'] | ['c#', 'unity'] | 2 |
10,523 | https://devpost.com/software/web-design-a1wirn | Reimagining methods to create profitable sales for an artist during COVID. Since concerts, meet & greets, and other physical bookings aren’t available sources of income, the idea is to create a digital environment that can take its place.
My plan was to create an interactive UI/UX website for an album release. If this was real life, this website can be a part of Merchandise’s digital exclusive CD.
Built With
figma
Try it out
www.figma.com | Web Design | Since concerts, meet & greets, and other physical bookings aren’t available sources of income, the idea is to create a digital environment that can take its place. | [] | ['Best UI/UX Hack'] | ['figma'] | 3 |
10,523 | https://devpost.com/software/covid-caution-4aifrp | Inspiration
In order to respond effectively to global crises such as the COVID-19 pandemic, robust tracking on the number of cases in a given area must be implemented for the sake of public health. As states begin to reopen, it is imperative for data on local cases of COVID-19 to be widely accessible to the public.
How might we design an application that allows users to easily track COVID-19 data in their current location?
What it does
It allows users to check local COVID-19 stats easily while also providing tips and information for people who are planning to leave their homes so that they can be as safe as possible while completing necessary tasks.
How we built it
We used Figma.
Challenges we ran into
For some of us, it was our first time creating a design project.
Accomplishments that we're proud of
We are proud of our ability to quickly create a robust project under such harsh time constraints.
What we learned
We learned a lot about the design process.
What's next for COVID Caution
Higher-fidelity prototypes, integration with real datasets.
Built With
figma | COVID Caution | A way to make local COVID data quickly accessible to people who need it | ['Ramisa Murshed', 'Sarinna Sung'] | ['Best Use of COVID-19 Data sponsored by BroadStreet'] | ['figma'] | 4 |
10,523 | https://devpost.com/software/election-rush | Inspiration
Election time is around the corner, and we wanted to raise awareness about voting and voting early. This is a glimpse into the story and thoughts of crucial swing voter in the 2020 elections — Hurricane Maria refugees.
What it does
This game story walks us through the story of Angel, a Hurricane Maria refugee and a critical swing voter in Florida for the 2020 election. Angel wants to be heard in this upcoming election, and makes decision points along the way, including whether to mail in the ballot or vote in person, and more(!).
How we built it
We used Godot Engine and coded in gdscript.
Challenges we ran into
We started off deciding to use Godot Engine because of a teammate's famliarity with Unity (which is very similar).
While none of us had any experience with Godot or writing in C and Gdscript, we were up for learning. We also started out with a crew of 3, then onboarded a new member for a total of 4 members. But the initial member who was gung ho with Godot Engine didn't end up showing up after the initial brainstorming, and another team member dropped out in the last few hours, so we were down to two.
We also had a team member who would've been perfect to take on the storytelling role based on experience with coding, except that this person is an international student who isn't as aware of US politics to be able to tell the story.
Accomplishments that I'm proud of
We learned some of the in's and out's of a popular free game engine having had no experience. Most of us are also first-time hackathoners!
What I learned
We had a lot of ideas to add to the game and kept focusing on creating the MVP. By focusing on the MVP, we were able to continue paring down our idea to the basics of what we were able to accomplish.
What's next for Election Rush
Creating the basics
Built With
gdscript
godot | Election Rush | A game story about voting early -- before the rush | ['Anita Yip', 'Shristi Chapagain'] | ['Best Failed Hack'] | ['gdscript', 'godot'] | 5 |
10,523 | https://devpost.com/software/mental-health-in-quarantine | Home
Tips, Team, and References
Studies
Stats
We created an educational hack on mental health in quarantine to highlight the detrimental effects that the pandemic has made on students and people in the workplace, and to give some brief tips on handling productivity and work life balance.
Built With
css
html
Try it out
mental-health-covid.glitch.me | Mental Health in Quarantine | An educational hack on mental health in quarantine to highlight the detrimental effects the pandemic has made on everyone. | ['Anke Hao', 'Annie He', 'Megan Sin', 'alim2babson'] | [] | ['css', 'html'] | 6 |
10,523 | https://devpost.com/software/story-time-x6eazo | Inspiration - Dokii Doki literature club
What it does - There are multiple routes that have different actions that you can choose. Your actions directly impact the path of your story!
How I built it - Built it in java, using atom. This has a scanner to pick up what the user is typing and has nested if, else, and else if statements to have every scenario planned.
Challenges I ran into - Time was an issue. We could not finish every scenario, having 3 different routes per question.
Accomplishments that I'm proud of - Proud that we have a main story line that works and does exactly what we want it to do.
What I learned - I learned how to create a functioning game that uses the users inputs in order to change how their story is.
What's next for Story Time - Continue on the different scenarios.
Built With
javascript | Story Time | Choose your own adventure story where you are the main character! | ['Patrick Smurla'] | [] | ['javascript'] | 7 |
10,523 | https://devpost.com/software/covid-data-mask-plotter | Inspiration
Wanted to see impact of masks on covid
What it does
Shows how masks affect covid
How I built it
Used django to make a webserver , python to try to manipulate data and political data to see state masks laws
Challenges I ran into
Integrating data into a graph
Accomplishments that I'm proud of
We created a webserver using django
What I learned
More research necessary
What's next for Covid Data Mask Plotter
Try to make it work
Built With
django
html
javascript
python | Covid Data Mask Plotter | Many people sick, wanted to try to show number of covid infections versus usage of masks in states | ['Daniel Kantor'] | [] | ['django', 'html', 'javascript', 'python'] | 8 |
10,523 | https://devpost.com/software/course-taker-tracker | Inspiration
I haven't declared my major so the courses I find out that I needed to take come by a surprise, so I thought having something like this would allow me to plan my schedule as I graduate.
What it does
It tells a student what remaining courses they need to take base on their intended major.
How I built it
Using Python and VS code
Challenges I ran into
I ran into thinking about whether or not to add courses that have electives or not. I also ran into thinking about the semantics of how the whole program should be.
Accomplishments that I'm proud of
I woke up at 5:30pm and finished it after my nap
What I learned
Learned more about applications of Python lists
What's next for Course Taker Tracker
Adding more courses and making it more complex and using pygame library for a better User Interface
Built With
python
visual-studio-code | Course Evaluator | It is a resource to help students plan their schedule as they graduate. It is especially beneficial to first generation college students like me! | ['Eliana Lopez'] | [] | ['python', 'visual-studio-code'] | 9 |
10,523 | https://devpost.com/software/break-down-your-brick-wall | GIF
Inspiration
We were inspired to build "from the concept of a "Wall of Awful" by Brendan Mahan. This is the idea that for people who have ADHD, and people in general, there is a mental wall of all of the bad things that are blocking you from doing what you need to do the when you are procrastinating and avoiding starting something.
What it should do
It begins with a wall of bricks symbolizing the "wall of awful" and, brick by brick, you click the wall away. Each brick reveals a tip for combatting procrastination and staying motivated.
How we built it
We used Atom and wrote in Python with pygame. We also used Figma to draft our design and layout.
Challenges we ran into
We were unable to have text appear after a brick was clicked.
Accomplishments that I'm proud of
We were able to get the bricks to disappear. We also are proud that each of us learned something new.
What I learned
We learned about Figma, Atom, Teletype, more about Python. We also explored pygame, and learned that it can get complex very easily. In addition to the technical learning, we were able to research strategies to combat procrastination.
What's next for Brick By Brick
We hope to get to a place where the program displays inspirational and informative messages about how to combat procrastination.
Built With
pygame
python
Try it out
github.com | Brick By Brick | Break down your wall of awful with encouraging and helpful tips! | ['Emily Gitlin', 'tabmiles'] | [] | ['pygame', 'python'] | 10 |
10,523 | https://devpost.com/software/coivd-19-infection-rate-by-density | What we did
We found a way to compare the positive cases in each state through a common ground by accounting for population size.
How we built it
We took the supplied COVID-19 data and cross-referenced it with the US state population density from the 2010 Census. We used Kaggle to work collaboratively and develop our visualizations.
What we learned
We learned a lot about accessing data frames in Python, along with how to calculate and add our own columns!
Challenges
We found that a few of the states reported a negative change in positive tests even though the data was labeled as cumulative.
What's next for COIVD-19 Infection Rate by Density
If we had more time we would analyze a larger section of states as well as use statistical tests to determine if these findings are significant.
Built With
pandas
python
Try it out
www.kaggle.com | COVID-19 Infection Rate by Population Density | Analyzing the COVID-19 infection rate based on population density | ['Josephine Summersett', 'Celia Morral'] | [] | ['pandas', 'python'] | 11 |
10,523 | https://devpost.com/software/sad-community | Inspiration
Winter is coming, and we're all stuck inside and feeling isolated. We're losing sun every day and it's getting colder and colder. Seasonal depression is among us, and due to COVID-19, it's been even harder for people to come together. With SAD Community, we want to create a virtual safe space where people can still be around others and feel seen. We hope that in the midst of what's happening to citizens in the U.S. socially, emotionally, mentally, physically, and politically, SAD Community can be a space where people can truly come together to find common ground and support and just be present with people going through the same issues.
Our team includes Shayla McJunkin, a psychology student, who expressed a passion for making safe spaces for students at Simmons. Hearing her story, Eva Lynch, a computer science major, has teamed up with her to make this dream come true.
What inspires us the most with this project is that we can create a place where everyone is equal, everyone is going through the same general things, and that everyone feels accepted, appreciated, and feels like even though a lot of us may have different backgrounds and specific issues going on in our lives, we can still find commonality within ourselves--even in these drastic times.
What It Does
With SAD Community, we want to provide people in the U.S. with resources so they can learn about how the changing seasons impact their mental health, learn how to get help through therapy, find informative resources that don't require having insurance--such as finding somewhere to get vitamin D supplements or a light therapy lamp--, receive weekly wellness tips and tricks, and provide forums where people can make their own support groups and talk with each other in a therapeutic way and have a sense of community without any financial restrictions.
How We Built It
Given the rapid pace required by this mini-hack, our top goal was to create a working prototype to act as our foundation for future iterations. With this in mind, we elected to focus our technical efforts on adapting a Wix website template to serve the needs of our projects.
Along with our Wix development, we researched and collected links and materials for our 'Resources' page of the website. We sourced from credible mental health institutions, educational institutions, and national help lines.
Challenges We Ran Into
The compromises required by operating on a strict deadline presented tough design choices. Ultimately we decided that we would focus on collecting mock data for our prototype's community members versus sinking time into recruiting sign-ups.
Accomplishments That We're Proud Of
We’re especially proud of the forum part of SAD Community. Creating this space where people can share their truth and their experiences with others who are going through the same thing can be a very therapeutic process and can really help bring unity in this time of chaos. In addition, we’re proud of the newsletter aspect and hope that as people sign up and make their own profiles, individuals will receive very insightful and helpful information on how to cope with seasonal depression and stress on a day-to-day basis through our weekly newsletter.
What We Learned
We’ve learned that although there are a lot of negative things going on currently in the world, if we just tackle some of these issues step-by-step and piece-by-piece, it can make all the difference. We’ve realized that by changing the lives of just a few and hopefully inspiring people to connect and support each other, this will be a great step in the direction of bringing people together as one and making the world a better place.
What's Next for SAD Community
Our next challenge for SAD Community is to use the interests that people have stated in their profiles to match them with community members of common interests and create a network of pen pals to send each other weekly encouragements. We also hope to provide monthly care packages for our members that will be filled with items such as SAD Community face masks, adult coloring books, stress balls, etc.
Built With
wix
Try it out
evaslynch01.wixsite.com | SAD Community | Creating a safe space to access proper educational resources and support groups during this socially, emotionally, mentally, and physically draining time. | ['Eva Lynch', 'Shayla McJunkin'] | [] | ['wix'] | 12 |
10,523 | https://devpost.com/software/ordinateur | Ordinateur was inspired after reading an article about the Seattle struggles for students to gain access to computers. I felt intrigued by the problem and wanted to see if I could do something about it. Like most people, I use my computer every day, whether its for school or for fun. At Ordinateur, it is our mission to provide students with computers and tablets through a donate and give solution. First, a donator will contact us through our website and send us the information regarding the laptop/tablet and their contact information. We will then determine whether the electronic fits our needs and is still in good condition. We plan to partner with school districts across the country who have trouble accessing government funds. We will then directly ship the computers from the donator to the user with no cost to the donator and school. Expanding our company, we can give donators a tax back as an incentive to give back to the community through our website.
One of the main things that I found myself wondering when I first decided on the idea, was what is a electronic without wifi. After some research, I found that XFINITY has set up free hotspots across the US. Not only that, people using xfinity can volunteer there house to become a hotspot for free wifi.
In such a short time, I didn't know if I had enough time to develop a full blown website which is why I decided to use Figma to plan out my website and design. I discovered Figma through a youtuber and since it was free, decided to test it out today. After getting used to the basic features, it was fun and sparked a creative knob that I didn't know I had. After using the documentation, I also discovered Figma can easily covert your designs into full fledged hard code. In the upcoming days, I will try to use my designs to actually build a website in HTML and CSS.
Link here:
https://www.figma.com/file/uoeZ1ERkKMG35niV9gLPnh/Ordinateur?node-id=0%3A1
A few challenges I faced included figuring out how to mask an object over another and drawing different shapes using the pen tool. After playing around, I eventually figured it out.
Built With
figma
Try it out
www.figma.com | Ordinateur | Education Amid COVID - 19 | ['Jason Zhu'] | [] | ['figma'] | 13 |
10,523 | https://devpost.com/software/med-speak-zrchab | Purpose: What is Med Speak?
Prompt
Due to COVID, many doctors and nurses are stretched thin, balancing the growing numbers of COIVD cases. It's now common that doctors and nurses are unable to see their regular patients without a scheduled appointment. Non-COVID Patients face several problems. They are frustrated by the lack of accessibility to make an appointment. A great solution to the problem would be calling the medical office, but all medical officials are redirected to focus on urgent medical calls relating to COVID. A runner-up solution would be doing a walk-in appointment, however, those options are no longer available due to hospitals wanting to limit the chances of contracting COVID.
Data
Before COVID
Workload
Doctors on average work 51 hours a week and see 20 patients a day.
Panel size
More recent studies have found “current panel sizes ranging from 1200 to 1900 patients per physician.
After COIVD
Fewer than 20% of the usual visits are now in person.
1 in 5 COVID patient in need of hospital care
About 70,000 people are hospitalized
DESIGN QUESTION
How might we create a platform that allows patients from around the USA to easily book appointments and minister medication in a way that feels personal, impactful, and efficient?
Problem to solve:
How can patients schedule appointments via online?
Description
Med Speak consists of services for English and non-English speakers who can readily access their doctor via telephone. The app features include booking a doctor's appointment, bookkeeping of prescribed medication, and a track record of the patient's medical info.
Steps
Research: Background research, Surveys, and Competitive analysis
Define: Personas, Problems, and Needs
Ideate: Brain Storming, Sitemap, User flow
Prototype: Wireframing, Hi-Fi prototyping
Questions to frame a solution:
Who am I designing for? Who is the target audience?
Why would users want to use the app?
How might we be able to improve the medical onboarding experience?
How do we bridge the gap between the user and their goals?
Using Lemers Method
Learnability
: How easy is it for users to navigate the app or web service to accomplish their needs?
Efficiency
: Once they get a grip of the app, how quickly can they perform tasks? How many clicks?
Memorability
: After not using the app for some time, how easily can they navigate through the app?
Errors
: How easily can Users recover from the errors?
Satisfaction
: How pleasant is it to use the design?
Challenges I ran into
Solution: Even though I could not move forward with my original body map design, I still had to create a feature that solves the problem for users who want to schedule an appointment. Going back to the drawing board, I had to come up with a new two-screen design solution, where users can fill in a form with their reason for requesting an appointment, listing their symptoms, and a drop-down list component selecting from a list of body part terminology that correlates to the symptoms.
Built With
figma
ui
Try it out
www.figma.com | Med Speak | Helping doctors and patients interact with each other online. | ['Chelsea Bishop'] | [] | ['figma', 'ui'] | 14 |
10,526 | https://devpost.com/software/m-clippy | m-Clippy Logo
Integrated in Cumulus App
m-Clippy Onboarding: customer define their preferences
m-Clippy Onboarding 1/2
m-Clippy Onboarding 2/2
m-Clippy Tips 1/6
m-Clippy Tips 2/6
m-Clippy Tips 3/6
m-Clippy Tips 4/6
m-Clippy Tips 5/6
m-Clippy Tips 6/6
Challenge 1 - Migros
We want to help people with allergies and people who wants to consume products in a sustainable way. We build an add-on to the Cumulus App and the Store-Scanner, later to alert in the Shop if a product is not healthy or not sustainable. Additionally you can check how good was your shopping cart with your preferences.
Our Presentation (PDF)
https://www.dropbox.com/s/0l5ew2oidy19wqy/hackzurich2020-m-clippy.pdf?dl=0
Inspiration
Food intolerance or allergy is a significant and widespread medical problem. Food allergy can cause severe symptoms in sensitive individuals and may be life threatening. In many instances the offending food is easily identified however milder forms of food allergy may be more difficult to diagnose.
Food intolerance is a neglected area of medicine because of diagnostic difficulties, non-specific symptoms and the relatively mild nature of the resulting illness; however repeated irritation or inflammation of the gastrointestinal tract may have serious consequences including malabsorption syndromes, small bowel overgrowth, coeliac disease and bowel cancer.
Based on resarch from Migros around 2 mio people in Switzerland are suffering from food intolerances and allergies.
m-clippy is an extension to cumulus App that has access to all cumulus data of its customers shopping cart and products. Additionally the customer is able to enter his eat habits and preference and based on all this information m-clippy provides deep insights int
m-clippy help everyone who has to stick to a restricted diet because of food intolerances or allergies.
m-clippy supports consumers eating habits like
Bio,
vegan,
vegetarian, ....
but also support customers who want to eat more
National,
Regional or
outside Switzerland
and with m-clippy the customer can choose from upto 17 different allergens to get tips, insights and recommendations.
Vision
Customer would get a visual or sound alerts on Migros scanner Subito and a realtime reports / tips in the cumulus. m-clippy displays for the custome, how good or how he/she can improve his/her consumer behaviors (=Gamification this would be also at this time that we can propose them more suitable and alternative products) and will get great recommendations
What it does
Customers need to select their preferences in Migros cumulus app (intolerance, eating habits, allergens )
Customers get insights through recommandation, tips and alternative products based on the preferences.
How I built it
Backend in .NET 3.1
https://dev.azure.com/m-clippy/m-clippy/_git/m-clippy
Frontend in SwiftUI for iOS. 14
https://dev.azure.com/m-clippy/m-clippy/_git/m-clippy-app
We use Migros API, Azure Cloud
Challenges I ran into
We both learned new technologies at beginning of HackZurich 2020: iOS, SwiftUI and .NET
We would have love to find a door in time to add more features.
Accomplishments that I'm proud of
We love our design, even if we are not UX specialists/designer! our App is using the Migros API realtime with great speed while invested much in caching and optimizing.
What I learned
Cédric wrote his first lines of .NET on Friday 22:00 PM
Lolo improve and had a lot of Fun with iOS Swift UI - sometimes Grrrrr, sometimes enlightment
We were pair programming both on m-Clippy all the time.
What's next for m-clippy
tbd
Built With
.net
figma
ios
react
swiftui
web
Try it out
dev.azure.com
dev.azure.com
www.dropbox.com | m-clippy | #1 Migros - we help people with allergies and for the ones that want to consume in a sustainable way. While giving tips advice in the Store-Scanner if products is against your allergies or locality. | ['Lorenz aka Lolo Hänggi', 'cédric walter'] | ['#1 Workshop: Migros'] | ['.net', 'figma', 'ios', 'react', 'swiftui', 'web'] | 0 |
10,526 | https://devpost.com/software/carbon-foodprint-sob6el | Burger
Soup 1/2
Stew
Salom
Soup 2/2
Rice
Inspiration
Society has become increasingly aware of the long-term legacy of humanity on Earth. We want to support the next generation in making conscious consumer decisions. This is achieved by raising awareness with respect to the enormous carbon footprint of many ingredients that are shipped across the world or consume huge amounts of resources during production and help with a carbon reduced cocking experience.
What it does
Carbon Foodprint keeps track of your food pictures (on Instagram) and lets you know in case there is an easy way to improve your carbon foodprint. Pictures of meals are analyzed using a deep learning model and the ingredients and the recipe is jointly extracted. In case there are ingredients with a very high carbon footprint, the app suggests fitting alternatives with a smaller footprint. In addition, recipe instructions for a new and optimized meal are generated and the user can cook with the updated recipe.
How we built it
We're running a Python backend which regularly checks the user's Instagram profile for new posts. In case we detect a new post, the image is fetched and analyzed using one model that is trained to classify the meal, detects the potential ingredients and is also able to generate a recipe. In the next step, we match the ingredients to their respective estimated carbon footprints and also map ingredients to potential alternatives.
The final step consists of letting the user know that we've found a good alternative by pushing out a push notification using Firebase Cloud Messaging and presenting the user the carbon saving alternatives.
Built With
flutter
python
pytorch
Try it out
github.com | Carbon Foodprint | Get immediate feedback about your personal carbon footprint when sharing pictures of your food on social media. | ['Kolja Esders', 'Patrick Deininger', 'dzimmerer Zimmerer'] | ['#2 Workshop: IBM & SwissRe'] | ['flutter', 'python', 'pytorch'] | 1 |
10,526 | https://devpost.com/software/smart-trucking-in-nigeria | SmartNavigation
EventMap
Seasonal Influence on Driving Events
Dangerous Traffic Situation where the road condition decreased heavily
Part of the street where a high number of events occurred
Visualization of Events
Inspiration
During a Hackathon, according to our team the mission should be to solve a pressing real word problem by diving deep into the problem domain and figuring out which challenges need to be solved.
During this year's HackZurich, LafargeHolcim Maqer provided a challenge, which impacts the lives of all people that will be living in the third largest country in the world by 2050 according to
https://www.worldometers.info/world-population/nigeria-population/
.
Its population will rise from around 200 million people today up to 400 million in 2050, with an increase of urban population by 200%.
To solve the issues connected to that, it is crucial to support construction companies, like the one mentioned above, to build the mega cities of tomorrow.
Starting Point in this Hackathon
To tackle this huge problem, we started by looking at cement trucks and their distribution in Nigeria. As road conditions are not best and there are several influencing factors that could make trips delay, as well as new requirements like reducing the amount of emitted CO2 or recognizing and avoiding unsafe routes, we analyzed driving data and build a dashboard to route tracks through the country depending on the current needs and focus.
What it does
Our product is a web application that aggregates telemetry data of the trucks, of which 500 drive through Nigeria every single day. We pay attention to event data, like harsh braking, harsh acceleration, overspeeding and more and join them with historical weather data to draw connections.
Out of those data sources, a holistic view on influencing factors of each driven route can be gathered to improve routing for the current operations and therefore build a sustainable, save and fast distribution of trips.
This is done in two modes. Our EventMap allows to display all event data refined through custom filters like the area of interest, the time span and weather conditions. By hovering over an event, additional information like the vehicle or driver ids are displayed. Hereby traffic planners can easily get an overview of the risks and benefits of certain routes and areas.
To support the route planing even further, we implemented a SmartNavigation system. After inputting a start and destination, it proposes a suitable route and predicts the length (time and distance), CO2 emissions and safety of that route. Our system allows to chose each of these categories as the priority metric so one can search for either the fastest, eco-friendliest or safest route. Critical events along that route are also displayed to allow a better risk assessment and prepare drivers for possibly dangerous route segments.
How we built it
We used Python and Kotlin for data analysis. Afterwards, we built routing and scoring algorithms with Python and aggregated the data. With the help of the Flask framework, an API was built that serves our Angular frontend for the routing platform.
On a more in depth level, we aggregated three data sources. The transportation data, which includes telemetry data and event data, weather data and Open Street Map data. Each driven truck route is mapped on real world streets. Each event is also connected to the trip it matches best. The weather data is connected to each event to use correlation between weather conditions like heat waves and driving behavior.
Each driven route on the map thus can be assigned a count as indication how often it has been driven and events. Connecting both information, based on the different event types the safety conditions of a path can be measured.
What we learned
Domain knowledge is extremely helpful during data cleaning. By speaking to several experts from the partner company, we gained insights on different attributes and their importance to tune our analysis and base them on useful data.
What's next for Smart Trucking In Nigeria
After the Hackathon, developing the project further with the project partner could make sense to solve the problem and roll out a first MVP after some iterations and discussions with further domain experts.
Built With
angular.js
flask
javascript
kotlin
openstreetmap
python | Smart Trucking In Nigeria | We support concrete transportations businesses by providing structured visualizations of traffic events and propose routes that positively impact the travel time, carbon footprint and safety. | ['Hendrik P', 'leon-schi Schiller', 'SimonWiet', 'Ben-Noah Engelhaupt', 'Goreg12345 Lange'] | ['#3 Workshop: LafargeHolcim'] | ['angular.js', 'flask', 'javascript', 'kotlin', 'openstreetmap', 'python'] | 2 |
10,526 | https://devpost.com/software/netty | Offset
Share Plugin
Tips
Transaction Overview
Push
Inspiration
We tried to solve a problem that we had for a long time: Tracking your carbon footprint is a cumbersome and time-intensive task. We see a lot of apps that are well designed and include gamification.
But would you open this app every day for ten minutes to meticulously track your carbon emissions? Probably not.
Go carbon neutral, effortlessly, with Netty.
What it does
Open your credit-card or banking app and export your transaction history as a PDF.
Share the PDF with the
Netty
App
Our classifier now extracts all transactions from the report, categorizes them, and calculates the carbon footprint of every transaction.
To further improve the accuracy of the calculations, the user can add details to each transaction e.g. a picture of your supermarket receipt.
Based on your carbon footprint, we give you tailored tips and tricks on how to reduce your emissions.
Once switched on, we periodically offset your carbon footprint based on the projects of your choice.
How we built it
Ionic, Angular, NodeJS
MyClimate API, Berkeley API
Challenges we ran into
The classifier is the core feature of our product and needs a lot of training data to accurately rate transactions with their correct carbon emission.
Sharing transaction reports from your banking apps with our app was quite complex to implement
We see an increasing amount of carbon emission data and APIs out there but getting correct and consistent and reliable data is hard.
What's next for Netty
Use open-banking API to get transaction details in a more structured way than with the PDF
Bring it to the app store
Built With
angular.js
ionic
node.js
Try it out
github.com | Netty | Netty automatically analyses your money transactions and helps you offset the carbon emissions of everything you do. | ['Johannes-Engler', 'Simon Flepp', 'Adrian Krebs'] | ['#4 Workshop: Accenture'] | ['angular.js', 'ionic', 'node.js'] | 3 |
10,526 | https://devpost.com/software/fit-fit-qfg1t3 | Skeletal Detection and Comparison (In Game)
Correct (In Game)
Incorrect (In Game)
"Killer Queen!"
Pose
Pose
Pose
Pose
Pose
Pose
Inspiration
A love of leveraging technology to improve life quality!
What it does
This app allows you to learn a new language while doing exercise, in a fun and gamified AR environment (thanks to the Huawei HMS SDK)! You are presented with a word in a foreign language, which you must translate. If you do not know the translation of the word, you instead have to perform a specific comedic yoga position in order to pass the round and earn a point.
How we built it
With patience and coffee :)
Challenges we ran into
The hardest part of the challenge was actually setting up the environment and finding a framework that worked for us. We spent half of the time setting up the environment.
Accomplishments that we're proud of
We persevered, even when nothing was working. Although we only got most of the work done through the last night (without getting a wink of sleep), we preserved without losing hope, and all learnt something new.
What we learned
Android Studio, Java and using the HMS Core!
What's next for FIT FIT
Adding a multiplayer mode (competitive mode)
Improving the integration between voice recognition and position matching
Making the user interface more beautiful
Adding a larger database of languages and vocabulary
Built With
android-studio
hms-core
hmscore
java
xml
Try it out
github.com | FIT FIT | Fit for Mind. Fit for Body | ['Tian G', 'Yelan Tao', 'Semion Rozov'] | ['#5 Workshop: Huawei'] | ['android-studio', 'hms-core', 'hmscore', 'java', 'xml'] | 4 |
10,526 | https://devpost.com/software/tim-the-team-plant | Tim the Team Plant
Highlevel Architecture
Dashboard Preview
Inspiration
Teams are the way people collaborate in almost any organization today. Thanks to research we know that what drives positive outcomes in these units is not the skills or productivity of any single individual, but the health of the team as a whole.
Team health and bonding have always been an elusive concept, but the recent abrupt shift to remote work has aggravated many of the existing problems, such as disruption of communication and feeling of isolation.
How do we know how our team is doing when we sit alone at home? Who’s up for a promotion and who needs some extra nice words because they got dumped by their girlfriend?
What it does
Tim the Team Plant is a gamified way to visualize your team’s health. It plugs into the tools your team already uses to communicate and helps you understand how your team is doing. If you as a team score well on parameters such as equal speaking time, speaker rotation and information flow, Tim will thrive. If your team is low on any of the scores, Tim will be sad and give recommendations on how to improve your score and therefore your team health.
How we built it
We built Tim using snap camera to display the plant on any video conferencing call. We used Slackbot to integrate Tim into the messaging app and we built a web dashboard to present Tim's aggregated data based on clojure. The design and prototype was built using Flinto and Sketch.
Challenges we ran into
Displaying the imagine in conferencing calls and collecting the relevant data from the various modes of team communication (video conferencing, chat, email) was a challenge due to the time constraint and limited API capabilities.
Accomplishments that we're proud of
The gamification concept is consistent and we think the plant is a great way to make an abstract concept such as team health tangible for everyone.
What we learned
Based on feedback from Randstad we learned not to rely solely on sentiment analysis or NLP for our tool but rather on discrete scores such as speaker time and rotation.
What's next for Tim the Team Plant
Keep on growing and fertilize a flourishing remote working environment! ;-)
Built With
clojure
clojurescript
flinto
google-closure-compiler
python
react
sketch
slackbot
snapcam
Try it out
hackzurich2020.netlify.app | Tim the Team Plant | A gamified way to visualize your team health. | ['Severin Candrian', 'David Pham', 'Christoph Weber', 'Dominique Kunz', 'David Ackermann'] | ['#6 Workshop: Randstad', '2nd Overall Prize, HackZurich'] | ['clojure', 'clojurescript', 'flinto', 'google-closure-compiler', 'python', 'react', 'sketch', 'slackbot', 'snapcam'] | 5 |
10,526 | https://devpost.com/software/trainline | VeilAway Window
Inspiration
Imagine yourselves sitting in a cozy seat of the scenic world-heritage railway track of the Rhaetian Railway, driving over the iconic Landwasserviaduct. You sip a cup of hot tea while it is raining cats and dogs, so much you can't really spot the beautiful landmarks. What is for you a bad coincidence can be daily business for railway drivers. They can't see the track side safety elements such as signals and signs. Reducing the reaction time of the driver, bad weather can have fatal consequences, if no precautions are taken.
What it does
Reducing the speed of travel doesn’t come at the desired consumer satisfaction. This is where we present VeilAway, an augmented reality assistant to the train driver. By showing nice-weather pictures with overlaid information of the next signals, the train driver can make well-informed decision about accelerating or decelerating the vehicle.
How we built it
With passion!
Challenges we ran into
No Snacks and Pizza (except for Noah, which was on site 😇)
Accomplishments that we are proud of
Leveraging the open-source mapping data available on
OpenRailwayMap
(ORM), the dataset giving the relative position of the signals and other specific objects was extended with other GPS coordinates of the track. This extension provided a relative distance for all points extracted from ORM (calculating the geodesic distance between successive points), and allowed to complete the missing GPS information for all objects (using linear interpolation between the relatively dense ORM point set). The combined dataset was then used as a lookup table, to map the images (which contain approximate GPS coordinates in their EXIF metadata) to relative positions along the paths (using a kD-tree to find out what the nearest neighbour on the track is).
The relative position is used as a central value in our application, scheduling the whole system. This is also relevant for a real deployment, because the distance measurement can be measured in a more stable fashion (especially in tunnels) than the GPS signal. The "drift" issue (distance from start not accurate anymore, which could happen just by doing manoeuvres on the track) can be taken care of by using the GPS signal, but ensuring it is of goodquality.
What we learned
VeilAway improves the safety of railways during bad weather conditions while maintaining high service reliability. This is why we think VeilAway belongs into each train drivers’ cockpit.
What's next for VeilAway
The App was tested on a small dataset of a track between Filisur and Thusis. However the train network is much larger and new data must be acquired. Since it is prototype a production environment should be choosen to have more control over some elements. For example the access to the map functionalities are quite limited due to the implementation through folium. Furthermore, the app could not just show an image of a signal but also indicate its state to the train driver and try to mark it on the image.
Built With
bootstrap
css
drawio
folium
html
json
python
qt
Try it out
github.com | VeilAway | Into each life some rain must fall. But let us rain on weather's parade and lift the veil! | ['DevDanR Rieben', 'AleksandraTimofeeva Timofeeva', 'Daniel Raimundo', 'Noah Hütter'] | ['#7 Workshop: Siemens Mobility'] | ['bootstrap', 'css', 'drawio', 'folium', 'html', 'json', 'python', 'qt'] | 6 |
10,526 | https://devpost.com/software/doctor-sugar | Inspiration
Diabetes is the 7th largest cause of death worldwide. It costs more than 320 billion euros to the world’s economy. But the worst, it robs us of our most precious gift. The years in our lives. Increasing the risk of early death by 2 times globally.
What it does
The problem is even worse in developing countries. with overall lower smartphone affinity, unstable internet connectivity and bad accessibility. Our target audience is the type 2 diabetes patient in the age group of 40-60 years.
Doctor Sugar is a lightweight assistant to monitor your glucose while increasing engagement through education, and deriving useful insights from your historical data.
How we built it
We build a chat/voice bot that provides results and tips about diabetes. Uses Dialogflow by Google, Mongo DB along with the resources and expertise provided by Roche to simulate engagement and behaviour change.
Challenges we ran into
Integration between the different platforms (i.e. Telegram, webapp, slack, facebook etc.)
Accomplishments that I'm proud of
We got a working prototype with a database connection including a dashboard and a functioning android app, ios app, telegram integration along with feasible text message(SMS) support.
What we learned
How to create a simple and very light application in form of a chatbot to be used in resource constraint environments and how to look from customer's point of view.
What's next for Doctor Sugar
Lets conquer the world ;)
Built With
android
chatbot
ios
javascript
telegram
Try it out
github.com | Doctor Sugar | Keeps your sugar in check with light weight app/integrations | ['akshitgupta95 Gupta', 'Michael Seeber', 'Levin Moser'] | ['#8 Workshop: Roche Diagnostics'] | ['android', 'chatbot', 'ios', 'javascript', 'telegram'] | 7 |
10,526 | https://devpost.com/software/bounce-get-back-into-your-creative-flow | Inspiration
During these last couple of months, we've had an especially hard time finding inspiration.
Hand-in-hand with the pandemic came isolation and our processes, which rely heavily on iteration and feedback loops, suddenly stood still.
We took this weekend to figure out a way to give creative professionals back their flow.
What it does
Our site allows users to upload general ideas or fully-fletched concepts and matches them with another creative pro - either with a colleague inside their company or a stranger in Australia.
Any creative stuck in a rut can log into our tool and request someone else's opinion on either a small portion of his work or an overall idea.
After completing a short onboarding users immediately get the chance to share their work. Their session is then matched to another creative from the requested expertise. The canvas allows for notes, free drawing, creating visual aids by using shapes, and adding pictures.
The sessions can be saved and reaccessed at any point in time.
A painless and beautifully packaged tool to reinspire creatives to collaborate.
How we built it
Bounce was built with scalability in mind. We chose Firebase as the backend for our application because it provides a wide toolset of real-time optimized APIs, like the Firestore database.
The Platform lives in the web and is touch-optimized, making it easy to switch devices and to work from afar.
For easy deployments and hosting, we make use of Firebase Hosting.
Accomplishments that we are proud of
We are really delighted with how our product turned out. We had a great time building it and we are excited to see where it goes from here. We especially like our UI/UX Design and think our web app turned out beautifully.
What we learned
Since we are still studying we definitely learned a lot. Working together - especially on too little sleep - can be challenging but definitely makes it more interesting.
What's next for "bounce - get back into your creative flow"
Our proof of concept is finished and running live
here.
We would love for our platform to help other creatives out and inspire new crafts as well as new connections.
Ideas for expansion:
Real-time collaboration on the canvas
Notify feedback matches via push notifications
Chat feature (& Video calls?)
More types of content and markup tools
Built With
fabric.js
firebase
vue
vuetify
Try it out
bounce-ideas.web.app
github.com | bounce - get back into your creative flow | We strive to make it easier for creative professionals to collaborate. Our platform matches creatives with one another and allows for painless feedback opportunities | ['Hanna Lisa Franz', 'Pascal Hostettler', 'Dario Breitenstein'] | ['#9 Workshop: Logitech'] | ['fabric.js', 'firebase', 'vue', 'vuetify'] | 8 |
10,526 | https://devpost.com/software/insurework | 1. Challenge
Your task is to build a model that can predict the extent of damage that has been done to a building after an earthquake, quantified in five grades. For this purpose, you can leverage information such as:
Structural characteristics of buildings
Building ownership and use
Municipality demographic information
Predicting damage severity will allow recognizing the buildings that will be more affected by the quake and hence help authorities to minimize the loss of life and property in the event of such a disaster happening in the future.
2. Model Insights
The model insights need to be translated into clear recommendations. Our approach, model insights and recommendations help in documenting the data processing, feature engineering, final model, and recommendations.
We conducted the analysis by identifying the dataset's loopholes and normalising the skewed variables so that they don't give a variance to the dataset allowing the model to fit faster on it.
Data Processing:
Removing count family variable due to missing value at 260294 position
Converting variables into categorical variables and integer values
Removing location data (district_id, ward_id)
Normalising the data using log transformation (for district ID and other location ID, age_building, height_ft_pre_eq, plinth_area_sq_ft
The best model we obtained was using Random Forest without any feature engineering by simply just merging the datasets by building_ids, removing the column for building_ids and running it. However, the more stable model was obtained using C5.0 after normalising the variables to and integer and numeric system and fitting the model over it
Feature Engineering:
We carried out the following methods to analyse the dataset
Correlation Test
PCA Analysis
Gradient boosting method
Tree representations
We implemented the following machine learning models for carrying out our multi-class classification
Tree based classification
Ridge-Lasso Regression
C5.0 Implementation
Random Forest
Questions
3. What did you learn from the data?
Correlation between different variables with Damage Grade as can be seen using the correlation plot. Parameters that play the most important role when training a machine learning model for classification for the given task.
4. How could we make buildings safer?
Superstructure plays important role in determining the damage grade along with floor material and foundation material. Also the repair age ~ 20 years to ensure their damage grade doesn’t goes up with with time. Location plays an important role in damage grade.
5. How should we rebuild the houses?
Duration of 20 years and without mud mortar stone superstructures. Foundation type and ground floor type has significant influence on damage grade.
6. What types of houses should we rebuild?
Houses with different floor type = RC or Timber and floor type is also Bamboo Timber, Cement-Stone/Brick
Houses having more than 20 years of age
9.1. Parameter Correlation
Premiums also differ widely by location, insurer and the type of structure that is covered. Generally, older buildings cost more to insure than new ones. Wood frame structures generally benefit from lower rates than brick buildings because they tend to withstand quake stresses better. Regions are graded on a scale of 1 to 5 for likelihood of quakes, and this may be reflected in insurance rates offered in those areas. The cost of earthquake insurance is calculated on “per $1,000 basis.” For instance, a frame house in the Pacific Northwest might cost between one to three dollars per $1,000 worth of coverage, while it may cost less than fifty cents per $1,000 on the East coast.
9.2. Unkown Risks
While the insurance industry has become more resilient financially, it has also let a significant portion of risk go uninsured. The evolution of natural disasters and changing climate calls for increasingly sophisticated catastrophe models and pricing approaches. Increasing climate risk will quickly intensify and challenge the insurability of entire regions: the P&C insurance industry can address this issue by forming an industry-wide coalition and collaborating more closely with governments and regulators.In high-risk areas, insurance may need to become mandatory, as it is in several countries, to significantly increase financial protection. At the very least, an opt-out option rather than the current opt-in would significantly increase insurance penetration, as behavioral science has shown. Rather than artificially suppressing risk-based rates, governments and insurers will need stronger public–private partnerships (PPPs), including government insurance voucher programs to address affordability issues.
https://www.mckinsey.com/industries/financial-services/our-insights/state-of-property-and-casualty-insurance-2020
9.3. Market Exposure
Many insurers are seeking broader market exposure than has historically been available via third-party managers – in terms of both sector and geography. Many third-party managers, particularly in Europe, have typically been boutique, focusing only on certain sectors of the market or specific regions, and Many investors’ capital constraints have led to them seeking co-investment capabilities, which have historically been in short supply.
https://www.globalreinsurance.com/viewpoints/coming-full-circle-why-insurers-are-turning-to-real-estate-investing/1428567.article
10. What's next for InsureWork
InsureWork Co. thrives to keep providing market insights for the real estate as a reliable insurance provider. We are also looking to expand our audience and business partners, especially with the booming real-estate sector of no established institutional insurers since this area of the world is a known seismic zone which has until now discouraged other foreign competitors
Built With
python
r
sql
Try it out
github.com | InsureWork | We create a framework to expand the a real-estate insurance business in a seismic zone. | ['Oscar Pitcho', 'Shreyasvi Natraj', 'Shachindra Kumar', 'Olivier Cloux', 'Danni Li'] | ['#10 Workshop: McKinsey'] | ['python', 'r', 'sql'] | 9 |
10,526 | https://devpost.com/software/datasoundsnicetome | Single User Activity over Time. Fraud instances can be visualized for the admin.
Global Transition Matrix. Probability of an activity (row) to be followed by another activity (column)
Activity Time distribution - Activities have well behaved distributions, except the daily exercise that has not been recorded correctly.
Number of User Activity distribution - showing exponential distribution while, due to the nature of distribution, power-law is expected.
Age-hour of usage correlation matrices
Inspiration
We were quite intrigued by the current reward system that Helsana has in place, as well as with the problems they face with this program. We wanted to take advantage of the real dataset provided to add value to the customer and the company, using our favourite data analytics techniques!
What it does
This client facing web app consists of a history of the activities that the user has accomplished. To enrich this experience, we used some data analytics and statistical inference to provide recommendations on what activity the user should do next, based on their past preferences. We also mark suspicious activities uploaded as the user, which could be fraudulent, using the entire database to detect abnormal activities. Once a fraud is detected, we can deduct some points, hoping that the user would avoid providing false information in the future.
This way, we want to encourage users to be honest, as well as give them a chance to correct or provide additional proof. This mechanism promotes values of transparency and trust between the client and the company. Having an automatic way of checking potential frauds allows the system to be more scalable and sustainable in the long term, such that more clients could benefit from the program.
Apart from the main functionalities mentioned above, we also implemented a simple login page where the login form is fully validated as well.
How I built it
Front end development
The front-end was built using React.js. Tech stack included JavaScript, HTML, CSS.
Back-end development
The back-end was implemented using Django, Django REST framework and connecting directly to MSSQL
Model analysis
Considering the participants' choices to be markov-chains, we obtain the transition matrix of the activities. By aggregating all of the transition matrices we create a global activity transition matrix.
We take into account a user's last activity type and focus on its corresponding row in the transition matrix.
We perform a
Multinomial logistic regression
using a softargmax function on the row to recommend one of the activities to the users.
Note 1.:
Daily exercise
activity is excluded from the matrix, since it will be independently recommended to the user everyday.
Note 2:
Bonus achieving activities
will be included in the matrix, as they have correlations with other types of activities, but they will not be recommended to the users. (they are excluded from the columns)
We also used statistical analysis to detect outlier activities for the fraud detection feature.
Challenges I ran into
The first challenge was to be able to coordinate between the different team members, as three out of four of us were participating remotely in three different time zones! On the technical side, making use of the data provided to us was quite a challenge, as the dataset was very heterogeneous and the number of features given to us was limited. It was also quite challenging to come up with the fraud detection system as no activities were already labelled fraudulent or not.
Accomplishments that I'm proud of
Being able to run statistical analysis on a relative small dataset with few entries for each participant.
What I learned
We learned how to deal with raw data and extract value out of it. We also perfected our frontend, backend, devops and database analysis skills!
What's next for DataSoundsNicetoMe
Suggestions for data-collection processes:
Categorize activities into different categories for example nutrition, fitness, recreation, and loyalty (including bonus programs) so you can analyze data effectively.
Create a dataset of fraudulent activities
Deployment and login
The application was deployed to a micro EC2 instance on AWS. Since it's a demo project, it's running on the embedded Django dev server (hence port 8000)
When logging in, use the following user IDs to log in (the password is always
test
)
63803693
: This user has a lot of activities
586550651
: This user has two fraudulent activities
Built With
django
pandas
python
react
Try it out
34.247.81.219
github.com | -DataSoundsNicetoMe | Fraud Detection and Recommendations for Fitness Activities for Users | ['MathieuChevalley', 'xx xx', 'Neeha Hammad', 'Sina Sajjadi'] | ['#11 Workshop: Helsana'] | ['django', 'pandas', 'python', 'react'] | 10 |
10,526 | https://devpost.com/software/corona-scare-map-app | Inspiration
Current global situation and implications it has on our perception of everyday issues
What it does
Shows scare and cases level based on available data
How We built it
Using NLP and ML techniques, with API created in Python and a browser client
Challenges We ran into
Preprocessing and classification of data (medium accuracy), integration of our modules, size of data
Accomplishments that We're proud of
Created a ML model which is able to classify sentiment of an article based on its TF-IDF vectorization, fast processing on backend side with lots of data, nice style of presentation in browser client, ability to see the site on mobile devices without a problem
What We learned
Some tools for integration and cooperation, new Python libraries for NLP and API, integration of React and OpenStreetMap
What's next for Corona Scare Map App
We can try to develop the app for more countries and their administrative territorities, create better predictive model for article sentiments, add more languages to sentiment prediction (e.g. English), add more data sources
Built With
api
azure
ibm
python
react
scikit-learn
Try it out
coronascare.switzerlandnorth.cloudapp.azure.com | Corona Scare Map App | Switzerland coronavirus scare map that shows scare and cases levels in cantons based on articles, tweets and confirmed cases and deaths | ['Łukasz Lepak', 'Miłosz Dźwigała', 'Norbert Pietrucha-Kacprowicz'] | ['#12 Workshop: SRF'] | ['api', 'azure', 'ibm', 'python', 'react', 'scikit-learn'] | 11 |
10,526 | https://devpost.com/software/hackzurich2020 | HackZurich2020 Contribution
Challenge Goal:
Read and understand building automation plans
Visualize a graph of the building equipment
Main Link
How
We used pattern matching to detect all the symbols in the plans and then used an connected component algorithm to check how all the detected nodes are connected.
After building a graph representation, we can then use this to visualize the data in every way we want using a small web app.
Built With
python
Try it out
adrian-hirt.github.io
github.com | Team Sus vs. Graph The Building | Understanding and visualizing building automation plans using pattern matching | ['Pascal Wacker', 'David Enderlin', 'Adrian Hirt', 'trabilitaet Ritsch'] | ['#13 Workshop: Siemens Smart Infrastructure'] | ['python'] | 12 |
10,526 | https://devpost.com/software/social-map-on59mh | Do you remember the last time you went to drink coffee with your best friend? How did your behaviour change during Corona?
This change hat a significant influence on your Barista. With a social-map, we give him the possibility to use new opportunities and avoid the risk, especially in uncertain times.
We combined the density and mobility data from 20 million Swisscom users, with corona mentions in newspapers, the corona cases and the weather in your area. Using Data Analitycs, we offer a particular solution for Shops that are directly dependent on the mobility of the costumers.
Built With
c#
flask
html5
javascript
pandas
python
sklearn
Try it out
hackzurich20.herokuapp.com
github.com | Social-Map | Help small shops to predict customer behaviour using data-analytics individualized to their needs. | ['Exs345', 'Jann Demond', 'ivasio'] | ['#14 Workshop: Swisscom'] | ['c#', 'flask', 'html5', 'javascript', 'pandas', 'python', 'sklearn'] | 13 |
10,526 | https://devpost.com/software/toby-bot | get started
scan ticket
confirm
Redeem points
Restaurant
Order
confirmed
Inspiration
Only 37% of consumers believe current loyalty programmes are effective in earning their favour. 95% of UK shoppers want brands to seek new ways to reward their loyalty.
Offline purchase won't always allow us to access to the apps loyalty programs.
Toby is a virtual assistant that rewards your purchase of products by scanning your shopping tickets and getting rewarded directly from brands!
What it does
The virtual assistant rewards through our AI Loyalty program, all your purchase of products such as: food, beverage and many others products.
How it works? Testing Instructions 🤖
1) As simple as starting the conversation with Toby:
https://t.me/TobyHackathonbot
2) Take a picture of your purchase.
3) Get points!
4) Redeem your points instantly!
How I built it
Through NLP entities we extract users intention from the conversation, and guide them about our loyalty program on how to get rewarded and where. We also integrate to the model a computer vision (OCR library) to extract the text from the image and identify: products, brands and purchase patterns. For the messaging service, we built it on top of a end-to-end encrypted platform, with the goal of procuring the privacy of the users data.
Challenges I ran into
Multilingual models.
Accomplishments that I'm proud of
Live Bot:
https://t.me/TobyHackathonbot
What's next for Toby Bot
MassChallenge Switzerland Program 2021
User Documents validation
Growth the Affiliated Brands to the Loyalty Program
Built With
natural-language-processing
Try it out
t.me | Toby Bot | Toby is a smart assistant that rewards your purchase of products by scanning your shopping tickets: Powered by Image Recognition & NLP Models! | ['Tamara Koliada', 'Leandro Camacho'] | ['#16 Workshop: Philip Morris International'] | ['natural-language-processing'] | 14 |
10,526 | https://devpost.com/software/active4swag | Inspiration
We have a lot of meetings and forget easily to do sports if we don't do it regularly. How can we motivate and encourage you to do more exercise?
What it does
We analyze your calendar and propose to do more exercise. These are either longer exercise session or a simple walk. Another way is by proposing to take the bicycle or to walk to the next meeting destination, we will remind you early enough.
How I built it
We built a simple web page to show the events and recommendation and a backend which connects directly to your calendar, in our case we focused on Google Calendar.
We analyze the events in your calendar and propose an exercise on a busy day or a walk to the next meeting.
Challenges I ran into
We tried to use the Azure API to calculate the distance across two points, but struggled with several issues and eventually decided to use the Google service.
What I learned
Parsing dates in Python is hard.
Producing a video in the morning is fun.
Built With
flask
google
python | Active4Swag | Tired at end of the day? Forgot to do sports? We will remind you to take a walk! | ['Kiru Poopalasingam', 'Martin Stypinski'] | ['#17 Workshop: CSS'] | ['flask', 'google', 'python'] | 15 |
10,526 | https://devpost.com/software/myclimatepal | Logo
Easily add track your emission. Either by searching for items or by finding them in their respective categories.
See and edit your emissions!
The dashboard gives you a sleek overview of your carbon footprint
Inspiration
While we generally know that eating meat and flying hurts our climate, it is hard to take effective action. Is it better to stop eating meat or to take the train instead of an airplane?
We believe that understanding the effects of our actions is key for improving them. This is why we built MyClimatePal to be the easiest way for everyone to gain a deep insight to ones CO2 footprint.
What it does
MyClimatePal lets you easily track your carbon footprint from multiple sources such as food, travel and housing. Using data from recent research [1], it empowers everyone to directly see the consequences of their consumption and evaluate their daily choices. Further, MyClimatePal provides you with statistics that help you to become greener.
How we built it
We aimed for a minimalistic and efficient user experience. To make tracking your footprint possible everywhere we built an intuitive iOS app using SwiftUI.
Challenges we ran into
Getting data on all types of CO2 emissions is extremely hard. Not only are emissions dependent on so many variables, they are also often hidden, and it is hard to find reliable data. Have you ever thought of the emissions from the constructions of your current home? To maximise the impact of MyClimatePal, we focused on collecting CO2 emission data on categories where small changes of each individual can really make a difference.
Accomplishments that we are proud of
While there remain many features to add, we believe that we have built a sleek app that is intuitive for everybody to use and already provides real value. As newcomers to iOS programming (especially the new SwiftUI framework) we are highly satisfied with our result.
What's next for MyClimatePal
Making it easier for users to track their emissions will be the main focus. From giving the user the choice between the imperial and metric system to making it possible to automatically track their daily travels, there remain many features to improve the app.
Further, we would like to cooperate with NGOs focusing on carbon offsetting to directly give the user the ability to compensate for their emissions.
[1] Clune, Stephen, Enda Crossin, and Karli Verghese. "Systematic review of greenhouse gas emissions for different fresh food categories." Journal of Cleaner Production 140 (2017): 766-783.
Built With
api
ios
mac
swift
swiftui
Try it out
github.com | MyClimatePal | Climate awareness begins with realizing how much CO2 you produce. Take your emissions in your own hands. Track your CO2 footprint and get an insight on how YOU can help our earth with MyClimatePal! | ['Moritz Wolf', 'KorbinianBstrtr Abstreiter', 'Valentin Wolf'] | ['#18 Workshop: Zurich Insurance'] | ['api', 'ios', 'mac', 'swift', 'swiftui'] | 16 |
10,526 | https://devpost.com/software/in-episode-topic-search-for-podcasts | Detecting topics in a podcast episode, e.g. where Elon Musk and Joe Rogan talk about a certain topic.
In-episode topic-chapters detection
Inspiration
We love long-form podcasts, but searching for various segments within an episode is very difficult and cumbersome. Want to listen to the segment where Elon Musk smoked weed on the Joe Rogan podcast? Good luck finding it in a 2h40min long episode.
With state of the art AI techniques we will solve this challenge.
What it does
Allow the podcast listener to use a natural language search to find segments within an episode which are of interest to him.
UX/ Frontend WANTED! :)
Want to join our team? We are looking for
UX/Frontend developers
with experience in Python-based frontend development. Our plan was to build a simple UI with dash, but if you have a better idea (and the skills) then we're happy to change that :)
Still to come
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for AI-Search for spoken audio
Built With
dash
gcp
gpu
numpy
pandas
python
pytorch
Try it out
bitbucket.org | AI-Search for spoken audio | In-episode topic search for long podcast episodes like Joe Rogan, Lex Fridman or the Knowledge Project. | ['Ferdinand Langnickel', 'Kevin Smith'] | ['1st Overall Prize, HackZurich'] | ['dash', 'gcp', 'gpu', 'numpy', 'pandas', 'python', 'pytorch'] | 17 |
10,526 | https://devpost.com/software/climate-karaoke | front page
karaoke time!
Inspiration
Living in an era of information, we all have developed a high degree of resistance towards the influx of news about melting glaciers and pictures of plastic in the sea. This makes it ever harder to raise awareness of the climate, which we all contribute to - for the better or the worse. But what if there was a way to reach people of different ages and backgrounds, and to make it a fun and pleasant experience? Music has proven to be a very effective carrier of messages, being interwoven with many social movements throughout our history. A catchy tune can spread like wildfire, reach beyond the scope of the internet, not to say that it can get stuck in our heads for the next day. By combining it with a call for environment awareness we hope to boost the impact of the message and to reach a greater community.
What it does
The web application lets you sing your favourite songs in a different way. While the music stays the same, the lyrics are adapted to stress the beauty of nature and encourage a more sustainable lifestyle.
How we built it
The web application was built with ReactJS for the frontend and Flask for the backend, where we used the Youtube and Genius API for the extraction of audio files and song lyrics. For possible matches, we assembled a small database with lyrics of songs which focus on environment and climate change. To expand this data set, we used a natural language generator (GPT-2) which we fine-tuned on the collected lyrics. The matching was performed based on metrics such as the pronounciation and stress patterns of individual syllables.
Challenges we ran into
The sparsity of the lyrics database a great challenge, as it is an important factor for the goodness of fit of the synthesized text with the original. Also, we had to realize that the Youtube API has a very low quota for searches.
Accomplishments that we're proud of
We were a great team with diverse backgrounds, where everyone could contribute and shine in their own way.
Built With
amazon-web-services
flask
genius
python
react
youtube
Try it out
github.com | Environment karaoke | A karaoke web app which generates alternative lyrics for popular songs to address topics such as climate and environment. | ['Reem Abdel-salam', 'Alžbeta Kubincová', 'Maja Jabłońska', 'Marta Pacuszka'] | ['3rd Overall Prize, HackZurich'] | ['amazon-web-services', 'flask', 'genius', 'python', 'react', 'youtube'] | 18 |
10,526 | https://devpost.com/software/crowdfree-6ms0bx | Brand identity - Typography
Business Canvas
Customer Journey
Survey
Persona 1
Persona 2
Persona 3
Screen
Screen
Team
We met over Slack and originally planned to work on a completely different project, but after discussions and brainstorming, we felt inspired by the Swisscom API and started planning an application around the data. During the hackathon, we found the Huawei mobile services, and the final plan for our app was born.
The fantastic team behind the app is:
Inspiration and motivation
We realized that during the COVID-19 pandemic, some new challenges have emerged that block restaurant businesses. It also became necessary to consider security and safety standards while providing customers with good suggestions for places they can go that meet their preferences. So, we wanted to build:
Crowdfree - a recommender system with a fabulous UI that can recommend great restaurants and cafes that are free from crowds
.
The Food For Thought challenge by IBM and SwissRe felt inspiring as our app would be about food and restaurant services. The Helsana challenge about enhancing digital services with data is also close to our project as we can use their data to create more targeted services for our customers.
What the app does
Crowdfree
is a mobile app for enhancing the restaurant experience during the pandemic. We have built a
Multi-directional Recommender System
. Most recommender systems only consider the user's preferences while giving suggestions, but we focus on how crowded the restaurant is as well. With this solution, we aim to offer the best and safest user experience.
Crowdfree
offers a fully automated service to give the best user experience when visiting a restaurant or cafe. The user starts by looking for a suitable seat to book, goes there, and checks in to get the online menu. After ordering, the user pays and checks out through the app. Finally, the user fills out a survey to improve their suggestions and share good venues with other users.
Experience:
Business Model
Customer Segments:
Crowdfree targets tech-friendly people aged between 25 - 50 that have internet access and a mobile device.
Value Proposition:
We offer a quick, easy, and customized way to finding less crowded restaurants. For this, we develop a multi-directional recommender system that considers both the user preferences and how crowded a place is. A recommended item would not be frequently recommended to other users in order to avoid crowding. The recommendations are customized based on user preferences for restaurants, gamified, and can offer a chance to win points and vouchers as a motivation to use the app. If we can convince users to use the app to check-in and check out we get more accurate information about how crowded a venue is, which benefits all users.
Channels:
We can reach the users via our mobile application. Also, we plan to advertise on social media platforms, e.g. Instagram or Facebook. For offline advertisements, we can use billboards, outdoor advertisements, and flyers to establish a strong social presence.
Customer Relationships:
We offer the users an online restaurant booking platform, an online menu with ordering, a recommender system, a check-in/check-out system, and online surveys.
Key Partners:
Vendors - restaurants and cafes
Retail shops and entertainment venues (they can offer vouchers in-app)
Swisscom - Mobility Insights for predicting crowds and improving our data
Azure - Backend hosted on Azure Cloud Services
Huawei Mobile Services - enhancing the customer journey with HMS Core APIs
Revenue Streams:
We are a B2B business and businesses can sponsor their venue via our application to reach more clients. We also have a pricing plan to suit all our customers.
PLAN A: 1400 € / month + 3% (A percentage of sales)
PLAN B: 1000 € / month + 5% (A percentage of sales)
PLAN C: 700 € / month + 8% (A percentage of sales)
PLAN D: 400 € / month + 13% (A percentage of sales)
How we built it
We have built a restaurant booking app. At first, we look for nearby pleases based on
HMS
Location and map kits. Then, we developed a system (check-in/ check-out) to know the approximate number of guests per restaurant. Based on this system and the API from
Swisscom
we guide our users to the most suitable place based on their preferences.
When the user reaches the place, we ask him/her to scan a QR code that was built with the
HMS
scan API. This QR code is attached to the check-in system and the online menu. Moreover, he/ she pays via our payment getaway and check-out. Finally, we ask him/ her to fill out a survey to improve our recommender system.
Live app debugging at Hackzurich with Huawei Mate 30 pro
The recommender system is combining collaborative filtering and content-based filtering for a hybrid system. For the content-based part we used
Zomato Restaurants Data
and we built the system with python and RESTful API to integrate it with the mobile app. On the other hand, collaborative filtering will be developed after getting users during beta testing.
Demo video
This is the user experience
Demo Video
Challenges we ran into
One of the problems that we faced is to know the number of guests along the day for each restaurant. It was challenging especially since Google Places API doesn't support an estimate of how long people typically spend at a restaurant or venue.
We are a team of 5 and 4 of us are participating virtually. To overcome this challenge we created a well-rounded workflow and divided tasks between us. We are also keeping regular meetings and collaborating over videocalls.
How to create a simple user experience with all these challenges and the tech complexity.
Accomplishments that we are proud of
We are proud that we have participated in this competition competing with people from all over the world. Furthermore, this Hackathon helped with meeting other incredibly talented people like us, working as a team, and taking on challenges that put our problem-solving skills to the test.
We have successfully created a full prototype during the Hackathon. Moreover, our system has been deployed as a real-life proof of concept, and it could be used easily. Furthermore, we made a business model, so that we can commercialize our app.
What we learned
By joining the workshops, we learned a lot about services provided by sponsors like Swisscom, Huawei, IBM, and Helsana. For example, from the Swisscom API we learned about the
Swiss special coordinate system
! Huawei helped us out by borrowing a fantastic Huawei Mate device for us to test the app on! The Microsoft team sent our team very useful documentation that helped us while developing the MVP. We learned how to use the Microsoft Azure platform to deploy our application. On the academic side we read some really useful articles about recommender systems and the necessity of improving them.
Backend deployment on Azure:
What's next for Crowdfree
Establish real customer relationships with restaurants and cafes.
Integrating more data from the Swisscom, IBM/SwissRe and Helsana data and APIs in order to improve our recommendations.
Continued development of the mobile app and backend.
Getting in touch with angel investors and plan the next steps for achieving a product that can be released.
Built With
adobe
adobe-creative-sdk
azure
design
design-thinking
flask
hms
java
python
scikit-learn
swisscom
Try it out
xd.adobe.com
github.com | Crowdfree | Crowdfree - find the best crowdfree places to go | ['Mohamed Amr', 'Francesca Sanfilippo', 'Carolina Lindqvist', 'Markus Haug', 'Sabiha Shaik'] | ['Audience Award, HackZurich'] | ['adobe', 'adobe-creative-sdk', 'azure', 'design', 'design-thinking', 'flask', 'hms', 'java', 'python', 'scikit-learn', 'swisscom'] | 19 |
10,526 | https://devpost.com/software/srf-swiss-corona-scare-dashboard | What it does
We visualize twitter and swiss news data, to show the hotspot of covid-19 related activity within Switzerland on a dashboard. We augmented this data by sentiment analysis insights and compare to reported cases over time.
All maps are interactive and evolve through time. They are presented via voila presentations of jupyter notebooks.
How I built it
We worked together on a shared Azure VM.
Challenges I ran into
We were switft with the backend part, however, no one of us has done any front end before. While we made quite a bit of headway with "dash" there was too little time in the end for us to learn how to deploy the map as a full webapp. We look forward to learning this extra skill and bring it back to HackZurich 2021.
Accomplishments that I'm proud of
The fun we had during the event
Working together efficiently
Our funny video - Trump knows, it's the greatest. The greatest he has ever see.
What I learned
Geolocation identification
Sentiment analysis
Setting up Azure VM for everyone to work on jointly
A bit of frontend and web app deployment
Working together half-remotely, half-onsite
Choreographing a funny video ;D
What's next for SRF Swiss Corona Scare Dashboard
Potentially we'll deploy the webapp that we worked on on a second branch, but could not finish until the submission deadline. But definitely, we'll go for a good dinner together (((:
Built With
dash
jupyter
python
voila
Try it out
github.com | SRF Swiss Corona Scare Dashboard | We visualize twitter and swiss news data, to show the hotspot of covid-19 related activity within Switzerland. We augmented this by sentiment analysis insights and compare to reported cases over time. | ['Valentin Anklin', 'Simon Mathis', 'Amray Schwabe', 'Aneesh Dahiya'] | ['Hybrid Team Award'] | ['dash', 'jupyter', 'python', 'voila'] | 20 |
10,526 | https://devpost.com/software/joinin-resu8t | Inspiration
Climate change is one of the biggest issues of our time. Hence, we often feel powerless to change and question habits. JoinIN will change that by challenging you.
What it does
Simply JoinIN!
Every morning we will offer you challenges to chose from. It is about doing things different, but also about inspiring others. Examples are the "The cold and amazing shower!", "The healthy and mind refreshing alternative!", "Just breathe and let us care about the rest!", "Ups I used it again!" and many more.
Every challenge has a positive impact either on the climate, your health, the society in general or on all of them.
To inspire you even more, partner companies will act as sponsors and reward you with carbon offsets for every completed challenge to amplify your action and push you towards carbon neutrality.
How I built it
Challenges I ran into
Accomplishments that I'm proud of
Doing a project in a hybrid team of five where no one knew each other before.
What I learned
What's next for JoinIN!
Reach out to us and help us to take this project off the desk.
Built With
bootstrap
python
Try it out
46.101.117.234 | JoinIN | Multiply Your Climate Action! JoinIN | ['Oliver Dressler', 'Joachim Schaeffer', 'Abdullah Hussein', 'Julius Gonsior', 'Isabelle Pumford'] | ['Hybrid Team Award'] | ['bootstrap', 'python'] | 21 |
10,526 | https://devpost.com/software/netzero-e80ts7 | Inspiration
Hack Zurich 2020 Challenge #18
What it does
Raise awareness and encourage carbon footprint reduction
How I built it
Airtable
Challenges I ran into
Idea too huge to have a demo implemented in 48 hours.
Accomplishments that I'm proud of
An app to illustrate the idea
What I learned
We are all in it and there is no time to lose. We have to aim for NetZero in our carbon footprint.
What's next for NetZero
Engage with stakeholders, complete the design, build the solution and promote it.
Built With
airtable
Try it out
drive.google.com | NetZero | Raise awareness and encourage carbon footprint reduction | ['Li Chow'] | [] | ['airtable'] | 22 |
10,526 | https://devpost.com/software/hekrboiiz-image-analyer | Problem
We asked ourselves how we could book a personal trainer online since due to the pandemic there is renewed interest in small scale and private sports lessons. We saw that there was no good option on the marked to easyily book pay and schedule online sessions.
Solution
So we propse building a platform that does exactly that. An online Personal trainer booking platofrm. This platform will focus on reducing the admin work for the Personal trainers as an incentive to get PTs onto the platform. This will be done since the PTs will bring their existing client base to the platform and enable steeper growth.
But since building such a platform is a bit boring for a hackathon we simply created a mockup of what it could look like and instead wrote a tool that ensures a high quality standard on the most important aspect of the Personal trainer profile. Namely the profile pictures.
Thus we built the hackerboys image analyzer
Product
the image analyzer is able to recognize:
How bright the image is
how colorful the image is
how many people are in the picture
If there is nudity, weapons alcohol etc. in the image
and much more.
check how "wild" the background is through image segmentation
A lot of machine learning is going on under the hood to achieve this
Summary
to summarize we propse an online personal trainer booking platform that focuses on reducing admin time for the personal trainers. This will be done in part through the image analyer that ensures that the pictures on each profile look as good as possible.
Pivot options
Alternatively if the personal trainer platform does not take off, we could pivot to provding our proprietary image analyer as an online service or focus on a differen private sports lessons like golf instead of personal training.
note
the image analysis in the video is sped up. in reality it takes about 1min to process the image.
Built With
crossplatform
flask
machine-learning
python
pytorch
tensorflow
Try it out
github.com | Hekrboiiz Image Analyer | A image analyzer for personal training booking platform | ['Philipp Hadjimina', 'Jason Friedman', 'Michael Keller'] | [] | ['crossplatform', 'flask', 'machine-learning', 'python', 'pytorch', 'tensorflow'] | 23 |
10,526 | https://devpost.com/software/legaltech-smartify | Add-In start
Processing contract
All entities highlighted
Currency highlighted with CHF conversion
Architecture
Inspiration
Working in the legaltech business, we know how hard it can be to find related information in a long contract. Lawyers usually want to understand a document but also directly make changes.
Here is where Legal Smartify comes in place.
What it does
Analyse a contract directly in word.
Edit and re process the document as many times as you want.
Converting currencies to Swiss Franc amount.
What we can recognise:
People and companies
Date information
Places, Addresses
Currencies
Phone Numbers
For some entities you also get a useful link to read more about it.
How I built it
State of the art event driven technology with WebSockets. The MS Word (TM) Add-In is written in TypeScript.
Challenges we ran into
We fixed threading issues.
We found a way to preserve the proxy object states in Office-JS.
Accomplishments that I'm proud of
We believe this tool can make the life of a lawyer easier.
Built With
python
typescript | Legal Smartify | Being in the LegalTech, we know that it is very hard to find relevant information in a contract | ['Tobias Ernst', 'Bikram Chatterjee'] | [] | ['python', 'typescript'] | 24 |
10,526 | https://devpost.com/software/legally-anonymous | Inspiration
Lawyers need to anonymise text in legal documents while sharing it in the public domain. Their existing set of tools didn't cover all the named entities in the document and required manual intervention by a lawyer, wasting precious time and resources. Since the data privacy of the users is the utmost priority of any legal firm, we decided to help them out so that their relationships with their customers could be long lasting and trust worthy.
What it does
Our tool analyzes e-mails using Named Entity Recognition. This identifies references to various entities, such as people, locations, and organizations. These references are scraped and replaced by a set of pseudonyms, such that the same entity is referred to by the same name and it all still makes sense. Legally Anonymous maintains a database of these entities and their references across the mailbox.
How we built it
We built a webapp, based on Python, Flask and the NLP framework SpaCy in the backend, and React in the frontend.
Challenges we ran into
Coordination in a hybrid-remote team, domain knowledge in the legal field.
Accomplishments that we're proud of
A clean and beautiful UI, working on a real-world use case, a moderately funny video.
What I learned
That LegalTech is a thing and in fact offers some interesting challenges and lots of potential.
What's next for Legally Anonymous
NLP and LegalTech seems like a match - we could imagine building more of this in the future.
Built With
natural-language-processing
python
react
spacy | Legally Anonymous | Anonymise names, companies, location, private info in legal docs. | ['Valentin Trifonov', 'Daniel Strebel', 'Akanksha Ahuja'] | [] | ['natural-language-processing', 'python', 'react', 'spacy'] | 25 |
10,526 | https://devpost.com/software/remoteam-workout-jmuk9y | Inspiration
Everything has changed in recent months due to the pandemic. A lot of companies have gone remote and it has become a challenge to stay connected with remote team mates without being in the same physical place. At the same time, some people have a hard time getting regular exercise due to spending much more time in their homes. We believe that with the right technology, these problems can be solved and we are happy to provide a solution for these challenges by creating "remoteam workout".
What it does
"remoteam workout" enables teams to connect in an out-of-work setting, and at the same time getting regular exercise. Teams can participate in long running challenges, such as virtual triathlons that can go on for several hours or days, and everybody can participate, each in their time zone. The concept is the one of a relay race (Stafette), where the next person starts when the previous person is done. While one person is sweating (e.g. running, biking or swimming), team members cheer them on. This gives the team a sense of achievement by working towards a common goal: staying fit together.
How I built it
We built the app using the language Dart and the cross-platform framework Flutter. As a DB, we used Firebase, and for visuals we used Material Design.
Challenges I ran into
Most of us were new to Flutter and mobile development, so it was definitely a challenge to get productive. Also, being a team of 5, we had to do some next-level project and product management to make sure everything runs smoothly and work isn't done twice.
Accomplishments that I'm proud of
We are proud that the app solves a real world problem that is currently present all over the world. We truly believe that it will help teams connect and therefore being able to provide better output in the workplace while staying fit at the same time. We're also proud that the app looks quite pretty :)
What I learned
We definitely learned some new technologies and how to do mobile development. We also learned how to quickly get productive in an international team with people we don't know. We learned that good communication and instant feedback is important.
What's next for remoteam workout
The next steps will be:
Get the app to the app store
Get companies to sponsor their employees to participate in challenges to connect and stay fit
Scale the app to be used for bigger teams
Built With
android
cloud
dart
firebase
firestore
flutter
materialdesign
Try it out
github.com | remoteam workout | Connect your team by working out together, no matter where you are | ['Shivam Goraksha', 'Lukas Elmer', 'Marco Barnobi', 'Marion Schleifer', 'Christof'] | [] | ['android', 'cloud', 'dart', 'firebase', 'firestore', 'flutter', 'materialdesign'] | 26 |
10,526 | https://devpost.com/software/vampire-ends-in-s | Main screen
Enter your BG levels
Little exercise screen
Can I eat that?
Incorrect choice
Old wise Dr. Turtle, your very own virtual motivator!
Doggo
Ducki
Sheepi
Pengi
Inspiration
Hackathons are an opportunity to use our skills to try and create something useful whilst having fun!
Diabetes has been a taxing condition on many! We wanted to create a solution that would help ease this load.
Our inspiration to gamify a Diabetes, Blood Glucose Level tracker came from the famous 'Tamagotchi' - a virtual pet, and how everyone was addicted to it as a child. Tamagotchi is simplistic and very powerful - you want your electronic pet to be fed, happy, and healthy and you care about it more than you actually care about yourself. But what if your pet/spiritual animal
makes
you look after yourself?
What it does
We started asking the following questions to build a premise of our app:
Are you a diabetic patient in emerging countries, lacking in motivation to correctly follow your treatments?
Have you ever wanted a virtual spirit animal that motivates you to keep you healthy?
This is now possible with Dia-GO, your Diabetes-amiGO.
It is an app that gamifies diabetes-related routines, helping to create healthy habits.
Living with diabetes is an extremely hard job, so not each patient has enough will and motivation to look after themselves. That is why we gamified diabetes-related routines, helping to create healthy habits. A virtual spirit animal that we created is designed to be a patient's partner through the journey, providing support, feedback and insights into healthy lifestyle.
Thanks to Dia-GO, our users will have fun in reaching motivational goals, like regularly tracking blood glucose levels, treatment needs, and daily physical exercises. The app will also register and collect data in order to show in a dashboard the user's weekly and monthly improvements.
Patients receive feedback about the lifestyle choices immediately: blood sugar level tests they make after the lunch will either make their virtual spiritual animal happy and energetic or tired and sad. Virtual pets/spirit animals will encourage users to go for a walk and give a piece of trivia about healthier food options. All in a gentle, fun and a clear way, without complicated medical terms.
Dia-GO will inspire our users in the long run, providing rewards and tools to personalise the spirit animal as well as to get some complimentary checkups to continue keeping their viral spirit animal ans well as themselves, happy and healthy!.
Sharing:
Users can always share their success with the family and friends for even more encouragement and support!
They can also use this same private circle of friends and family in case of an emergency or when they want a little more motivation to stay fit and healthy.
How we built it
We have developed our app with our audience in mind! The app is designed and built to be lean and to maximise its offline functionality. One of the points we would like to highlight is that
iOS is used for demo only because it is the presenter's device
and our app is
hybrid and runs on both Android and iOS
.
And most importantly, built with love and compassion!
Challenges we ran into
Making a game out of such a serious topic is not an easy task. We tried to balance long-term and short-term rewarding systems in a way that even if BSL today isn't great and instant feedback is negative, our user would still get long-term bonus points: with them, we reward overall self-improvement aspiration.
Putting the app together :)
Accomplishments that we're proud of
Designing and developing an app within the timeframe with a diverse team, completely oblivion of each other's existence, until this Hackathon!
What we learned
We realise that being a diabetic can cause unnecessary stress to the person and their loved ones. The constant relay of numbers can take a toll on one's mental health. With Dia-GO, we hope that we can bring some fun while we take care of the Dia-GO family :)
What's next for Dia-GO
The potential of Dia-GO is huge!
We could develop the following systems beyond the prototype phase:
Rewards
Emergency communication
Seasonal and festive events
More challenges!
And a special shout-out to HackZurich, Accenture and Roche!
Hey, Roche, let's bring this app to the world! One bit and one blood sugar reading at a time :)
Thank you.
Built With
adobe-illustrator
android
expo.io
ios
react-native
typescript | Dia-GO | Fighting diabetes together with Dia-GO, your Diabetes-amiGO! | ['Matas Pocevicius', 'Ankita Thaker', 'Oksana Kostiuk', 'FabianSchuessler Schüssler', 'Federica Agostini'] | [] | ['adobe-illustrator', 'android', 'expo.io', 'ios', 'react-native', 'typescript'] | 27 |
10,526 | https://devpost.com/software/excite | Our Web Extension
Work in Action. Note annotations in the bottom right
User Story
Meet Manolo -- a highly lauded lawyer who spends his days studying legal cases and keeping abreast of new developments. Do you think his life is easy? Let's take a closer look ... laws are constantly being extended, revised and amended. Libraries are filled with thick bound volumes and even a single set of laws exist in many distinct versions that have been changing over time. On the flip side, courts weigh up and pass judgement on real cases on a daily basis.
Manolo and his colleagues have to prepare by researching across a wide set of case history. This means they need to manually check thousands of documents, many of which date back several decades beyond what you may imagine. As a result, Manolo and his team pour the majority of their working hours, colossal sums of money and often their own frustration into thorough preparation. This is where automation and a sprinkle of technology comes to play. Now we can find a year's worth of documents with just a couple of clicks. Overall this means less time and resources invested, and of course Manolo will work happily and with ease.
Inspiration
The Swiss government offers an official portal to navigate and browse through the minefield of laws and regulations. Prior to starting our project, the built-in search engine was flawed and broken. A lawyer could search for a specific term and even refine their search to a specific time period but sadly these constraints were silently discarded. As a result, their search would point to a wholly incorrect result, showing only the latest version of the requested law. Not only is this mismatch confusing but it causes extra effort to track down the correct result and scroll through to find the relevant passage.
What it does
Our proposal uses a web crawler to gather all legal texts from the last century and arrange these in a form that permits efficient search. Using our index, we built a web extension for Firefox that marks references to other legal texts and gives a handy tooltip that provides links to the active law from that point in time and the most current revision. In this way, our meticulous researcher can hop over to the correct version of the law without needing to switch to interrupt their attention and switch to another crude web search. Beyond these immediate benefits, the dataset we gathered is a vital aid in building more advanced tools that understand the full structure and relationship of the law.
Built With
firefox
scrapy
sqlite
web | ExCite | A search experience to make legal precedence research smarter. Augments the case description with valuable hints and inline annotations. | ['Marina Rey Ciudad', 'Cédric Waldburger', 'Zaheer Chothia', 'Jacqueline Staub'] | [] | ['firefox', 'scrapy', 'sqlite', 'web'] | 28 |
10,526 | https://devpost.com/software/challenge-7-lift-the-veil-project | Inspiration
When driving in bad weather conditions, train drivers often cannot see signals and track-side equipment in front of their engine making the planning of the journey innacurate and increasing the probability of delays. This inability of seeing the outside is not just about drivers slowing down the engine but passengers also missing the fun of enjoying amazing landscapes.
We understand this can be frustrating based on our own experience. As a group of technology enthusiasts we believe in the power of machine learning and data-driven decisions to solve the challenges faced by any industry. For this hackathon, we have focused our efforts on an mobile app to make up for that stubborn foggy and rainy weather.
What it does
This mobile app will work in four simple steps:
1) It receives real time image frames from a camera located just in front of the train.
2) The image frames are then passed to a deep learning model which removes bad weather characteristics
(e.g. mist and rain)
3) The app shows in real time how the path would be seen in normal weather conditions
4) In addition, the app will show (also in real time) a map pointing the current train location and will inidicate the
next safe point (map location)
How we built it
Our deep learning model was built with PyTorch and is based on a CNN configuration with two phases, Encoder and Decoder. The first one comprehends the bluerring of normal weather images (mist, rain) which are passed to the decoder to make them back to normal.
Challenges I ran into
Improve prediction accuracy as the dataset we worked with was relatively small (2241 images).
Convert our Keras model into TensorFlow Lite (for android purposes) due to our lack of experience in machine learning for smartphones.
One member is in a different time zone.
Work with a multidisciplinary team (comp science, engineering and business)
Accomplishments that we are proud of
We all improved our teamworking and communication skills.
Our medicine student member became familiar with artificial intelligence in the health sector.
Our business student member learnt how to build android apps and got UI design experience.
What I learned
What's next for challenge 7-Lift The Veil project
to be completed
Built With
android-studio
java
python
pytorch
Try it out
github.com | challenge 7-Lift The Veil project | to completed | ['Diego Muñoz', 'Wilson Campoverde Carrilo', 'Lenin Cruz', 'Marcel Mauricio Moran Calderon'] | [] | ['android-studio', 'java', 'python', 'pytorch'] | 29 |
10,526 | https://devpost.com/software/project-ditr2l3nj5mu | Inspiration
We just realized how badly we suffered from spine and neck pains sitting in front of our computers at the beginning of the hackathon and decided to create our project.
What it does
Our app tracks your posture and working environment conditions(e.g. lighting) and guides you to improve them.
How we built it
We use our knowledge in computer vision, web development, and design to create an easy-in-use app that helps people to make their working environment more health-friendly.
Challenges we ran into
First of all, online hackathon was something new and unusual. For us, in-person communication is exactly what makes hackathons such a fun place.
Accomplishments that we're proud of
We are most proud of the fact that we build a fully working app from the ground up. It’s not been an easy road, but we have stuck with it and continued to grow functionality. Now we have a fully functional friendly team. It’s this desire to continue to grow and achieve that has kept us going to sort out all difficulties.
What we learned
The biggest thing we learned is how to do 24-hour projects remotely. It's surprising but slack communications and trello board are not going to help with that.
What's next for UpBack
Built With
javascript
tensorflow
vue.js
Try it out
preview.hackzurich.karamoff.dev
drive.google.com | UpBack | Computer vision for healthy and productive working environment | ['Nikita Karamov', 'Artem Lukoyanov', 'Nikita Durasov', 'Oleg Korneev', 'Oganes Manasian'] | [] | ['javascript', 'tensorflow', 'vue.js'] | 30 |
10,526 | https://devpost.com/software/corona-b2x | Company Logo
Functions Demo
Smiles and waves!
Inspiration
Covid 19 has made understanding how customers are behaving a nightmare! People are behaving erratically, choosing different days and times to go into the city, alternative modes of transport, and ordering more things remotely. As a business owner, it can be challenging to understand how demand is changing, how many roles of toilet paper should I supply? How many staff should I hire? How many people will be buying coffee? Where is the next big event taking place? …
What it does
Our solution provides a tool for you, the business owner, that helps you understand how your demand is changing in real time. We have partnered with Swisscom to develop our solution. The product provides you with an easy to use format, alerting you to demand surges and drops in your local area, all on your mobile phone.
Check it out for yourself here!
link
How I built it
We built solution with passion and love of data!
It is created on top of python, pandas and visualize prettily using dask & plotly.
We deploy our solution into a production ready stage on top Azure.
Rather than depends on tech-stack we also think really deeply on the benefit of our product to the business.
Challenges I ran into
There has been a lot of challenges during this one and a half day coding.
We are facing a problem during ingesting the data and getting the front-end ready.
The multi-dimensional data in a large amount is also challenging to be prepared for analysis and valuable insights.
Accomplishments that I'm proud of
We have learned that there is nothing impossible -- regardless the challenges and problems we are faced with and specially with the short time span & sleepiness, we are able to finish and create a wonderful product.
Even though half of our team are working remotely from all over the globe, we connect naturally and warmly,
and work harmonically together.
What I learned
We learn the value of data! it is a new oil!
We learn that data provided by Swisscom has a lot of potential for analysis beyond tele-communications. They are available for business intelligence, social/economical studies, traffic planning, etc. They can be precious to all sectors and individuals.
We also learn a lot about data visualisation and data-cleansing. What data to select/drop to be able to give insights? What data to present to our target audience? What kind of visualisations might be more understandable and straightforward? When trying to answer these questions for our audience, we also learn by ourselves about data science philosophies.
What's next for INDEMAND
We are willing to build a more mature business product from here! Be it with more/more types of data, more complex-in-model yet simple-for-perception data visualisations, smoother UI, etc. We simply wish to closer the gap between BI (business intelligence) and the non-experts.
Built With
swisscom
Try it out
hackzurich2020.webflow.io | INDEMAND | Realtime demand intelligence for your business | ['Xiaoying Zhi', 'Octavianus Surya Putra Sinaga', 'Liam Simpkin', 'Aldy syahdeini'] | [] | ['swisscom'] | 31 |
10,526 | https://devpost.com/software/zeroplastic-wdapjl | Profile page app
Peer review app
Camera app
Inspiration
We’re a team of master students in Robotics at ETH. Last Tuesday in the class of Robot Dynamics professor Hutter presented his technology venture about a cleaning robot to recover and recycle the plastic from the rivers. We investigated this topic more in depth with his help and after some research in this field, we decided to commit to the LafargeHolcim workshop about plastic waste. The idea about creating a web-app that could benefit both the users and the companies comes from the consideration that we can’t solve the climate issues only with the good intentions of part of the population. We developed the business plan in a way that could create a circular economy, keep engaged the users and the companies can achieve plastic neutrality contributing in the creation of a sustainable business.
What it does
The app connects people in countries with high urban plastic pollution and companies aiming at reducing their plastic footprint.
The user can collect plastic trash and bring it to the available collection centers to earn points. These are dependent on the weight of plastics gathered.
After level three the user can exchange points with coupons, free tickets, or money. This is possible because companies, used to waste money in plastic certifications which are not really connected to real waste management, prefer to fund people which, under the reliable e transparent supervision of our service, can actually achieve better results with a higher accuracy.
Trashes are localized when they are collected, when the user decides to take a picture of them. If so, an extra reward is given. The anomaly detection system looks for unusual patterns that are correlated to bad-behavior.
The app can then build a map of the most plastic-polluted zones and extracts useful data shared with transparency on the web page of the company. In case of anomaly related to bad waste management (such as mismatched plastic flow at a location, e.g. 20 tons incoming but only 18 leaving), an alarm signal is triggered.
A peer-reviewed system for image labeling is taken into account. The enormous number of data together with the peer-reviewing approach makes the corresponding growing dataset particularly desirable. Exploiting it, is possible to combine object detection tasks (effectively solved through modern architectures, e.g., YOLOv3), with the classifier trained on the acquired dataset.
How I built it
The infrastructure is composed by three entities. First, the landing page built with Vue.js is based on Nuxt.js. Second, the mobile app is a native app developed in Swift for the IOS system with a classic configuration based on Cocoapods. Lastly, the back-end services have been developed based on different services: the framework Nest.js, Amazon S3 for the file storage and Postgresql for the database management, Amazon Cognito for user authentication, and Amazon Codestar for the automatic deployment of the cloud services. The object recognition uses YOLOv3.
Challenges I ran into
The main challenge was to understand better the field of construction in order to make a contribution in a relevant problem that humanity is facing right now. Our background is more in Robotics and Software Engineering, but since Tuesday we interviewed different experts of the field and, after the inspirations and suggestions from the speakers of Friday night, we came up with the idea that we developed during this hackathon.
Accomplishments that I'm proud of
When yesterday evening we, components of this team, entered the same room we are still working in at this exact moment, we didn’t expect such great chemistry among ourselves. We didn’t expect entire days of mutual support and empathy. We believe that there is nothing greater than a supportive team and this is definitely the accomplishment we feel most proud of.
What I learned
The two hackathon days have been strenuous both physically and mentally. We believe the most important skill learned has been the ability to stick to the time planning we set up while maintaining lucidity.
Some components of the team have also acquired some hard skills during the competition, mentored by the most expert people in the team. For instance, a team member developed new skills in using Nuxt.js - one of the frameworks used in the process -, while another team member started out from scratch all the principles of web services.
What's next for ZeroPlastic
ZeroPlastic aims to validate the assumptions made in the building of the first version of the product in order to get a reliable knowledge foundation for further developments in the implementation of the idea. In the initial stage, we want to get as much feedback as possible from the partners of the hackathon and from other people that want to experiment with our technology.
In particular, ZeroPlastic is aiming at establish contacts with some of the immediately addressable companies and stakeholders such that CocaCola, Nestlè and Pepsico. In the meantime, the app will be published on both IOS and Android platforms in order to have real feedback from the community to get an assessment of the possible impact that this service can have in the future.
Built With
amazon-web-services
angular-other-tools:-matlab
aws-codestar
aws-cognito
css
git
html
javascript
kotlin-frameworks:-nestjs
languages:-typescript
nuxt.js
python
pytorch
sketch
swift
tailwind
tensorflow
vue.js
Try it out
github.com
github.com
github.com
upbeat-lumiere-9eafc0.netlify.app | ZeroPlastic | ZeroPlastic is a platform where businesses can finance people to collect plastic waste. In this way, companies can reduce their plastic footprint, jobs are created and the environment is safeguarded. | ['Antonio Arbues', 'Patrick Turricelli', 'Erick Turricelli'] | [] | ['amazon-web-services', 'angular-other-tools:-matlab', 'aws-codestar', 'aws-cognito', 'css', 'git', 'html', 'javascript', 'kotlin-frameworks:-nestjs', 'languages:-typescript', 'nuxt.js', 'python', 'pytorch', 'sketch', 'swift', 'tailwind', 'tensorflow', 'vue.js'] | 32 |
10,526 | https://devpost.com/software/mygusto | Our App 'MyGusto'
Functionality
MyGusto recommends personalized Migusto recipes to you, based on what you like and what you don’t like.
The app shows you new recipes and you can tell the app if you like it by swiping right or dislike it by swiping left.
Swiping
The app presents one recipe after another which can be swiped left by the user to dislike the recipe or right to like it. To get more information of a presented recipe, one can click on it to see more information. The recommended recipes will be more personalized, the more recipes the user likes or dislikes.
MyRecipes
In the panel
MyRecipes
the user can see his liked recipes and swpie right if he decides to cook it. He can choose more than one, if he knows he will be cooking those meals in the near future. All the needed ingredients will be added to a shopping list.
Shopping List
In the shopping list all the ingredients, which need to be bought are visible including a symbol if it is currenlty discounted in Migros.
Settings
Before swiping, the user can already set some preferences by marking the allergies and choosing the importance of sustainability and budget. The users preference profil will be updated continuously in the background by swipping recipes.
How does this all work under the hood?
We propose to use a recommender system, that utilizes the likes and dislikes from other users to recommend new recipes to you. As our app is new, we have little user data to work with. Therefore, we use a second network that initially proposes you similar recipes to the ones you already liked. This allows to slowly transition to a smarter system over time.
The options with such a system are limitless: For example if there is an overstock of Bananas in Migros’s across Zurich → Migros can make Banana Recipes more popular this week.
Built With
android
docker
flask
ionic
ios
javascript
postgresql
python
Try it out
github.com
github.com | MyGusto | An app to cater personalized recipes from Migusto to users | ['Steven Marty', 'RSchwan Schwan', 'Viviane Marty', 'Julian Huwyler'] | [] | ['android', 'docker', 'flask', 'ionic', 'ios', 'javascript', 'postgresql', 'python'] | 33 |
10,526 | https://devpost.com/software/socialarm | Inspiration
Need some motivation to wake up at your desired time while working from home due to Covid-19 ? Do you need to be at a football or hockey game with your team and every sunday morning thát one person is late again ?
SociAlarm is here to connect with your team while waking up!
What it does
Our app has a very clear functionality: to provide an easy to use, social, motivating and fun alarm clock for both Android and iOS. You can create a group with your friends or workmates, and everyday one of you gets to choose a song the whole group will be waking up to.
This creates a unique team building experience.
How I built it
The app was built using React-Native with some native components for the frontend framework and a GraphQL/Prisma server for the backend. This allows the app to be fully functional and easy to expand for the future. To provide the search and download of alarm sounds we used the Spotify api for access to their large collection of music.
Challenges I ran into
We ran into a lot of errors using React Native which were not easy to fix.
The native alarm API was hard to implement and the library that did, had errors in them.
Accomplishments that I'm proud of
Build a fully functional native app in a really short time.
Had lots of fun together working on it.
Fixed an error in the Alarm Library for React Native.
What I learned
We learned coordinating and working in a group that is physically not in the same place. What's more we learned how to build apps with React-Native which was not the best idea to do during a hackathon but it worked.
What's next for SociAlarm
Build a reward system for groups
Build games that can be set as alarm games with highscores
Build With
ReactNative
GraphQL
Apollo
Prisma
Built With
graphql
prisma
react-native
spotify
Try it out
github.com | SociAlarm | An alarm app that makes waking up with your friends or team easier than ever before! | ['Hidde .', 'Vince van Noort'] | [] | ['graphql', 'prisma', 'react-native', 'spotify'] | 34 |
10,526 | https://devpost.com/software/sustainable-menus | App logo
Inspiration
At a time where climate change is affecting our earth and corporations are either unwilling to accept it or do anything about it in the hope that they need to spend more money, every single person counts. If they don't want to do it then let us do our part! Finding out which food to buy while also considering which food is better for both us and the environment is no easy task, so we set out to make it easy for people like you and me to find it simply by using an app.
What it does
It scans any product that you would like to buy and compares it to other products that you were considering to check it's impact on our earth and on your health.
Do you want more energy while having minimal impact on the environment? Done.
Want to consume less protein and less fat? Done. Does it still have less impact on the environment? Done.
Just look at the status of the data to find which is good, which is okay and which is definitely bad with easy color coding of Green, Yellow and Red.
You can compare multiple such products and look at their color representation to find out which is good and which is bad.
You can also track the history of what you have purchased or scanned in a separate place to find out the impact you are having on the environment and your health
How we built it
We used eternity api's and migros dataset to get the data and after analyzing and storing it at a backend we built an Android app with kotlin while using the scandit sdk to scan for barcode to fetch the data.
Challenges I ran into
Using the dataset was difficult so we had to store chunks of dataset in our own backend server and also process it according to our requirements.
We had almost finished integrating IBM watson sdk to android to utilize it's assistant features to make the comparision easier but due to lots of data and some problems we had to stop it at the final moment.
Coordination across different timezone was quite difficult and we learned a lot about how to optimize and communicate effectively while staying at a different country
Accomplishments that I'm proud of
This maybe a simple app but the simplicity makes it more likely that you will use it for random food that you might buy the next time you are at a store.
We made it so that even a layman can utilize this application easily
What I learned
We learned about how much of impact we are having on our environment and how we can save it from further impact by taking small steps and measures.
We got to know how to coordinate in different timezones.
We found out multiple sources of datasets and SDKs which can be used in future projects
What's next for Foodify
We plan on integrating the IBM watson to include a chatbot and voice assistant with the app so you don't even have to scan the barcode and you could just ask the app to compare between let's say cranberries and xyz burger and it would tell us the impact it has on the earth as well as which is healthy for you.
We plan on increasing the processing power of our backend server to do more ML tasks to predict it and understand the impact more accurately.
Built With
android
javascript
kotlin
python
scandit
Try it out
github.com | Foodify | What should I buy? Which food is better for the environment? Is it healthy? Find it out with foodify | ['Dmytro Perekrestenko', 'Alessandro Ruzzi', 'Kartik Kulkarni', 'Mohamed Mostafa', 'Ahmed Mostafa'] | [] | ['android', 'javascript', 'kotlin', 'python', 'scandit'] | 35 |
10,526 | https://devpost.com/software/coronahackzurich2020 | Journalists, leaders and entrepreneurs need an accurate understanding about the attitudes in their societies to make good decisions.
Aggregating different data sources enables models that can describe more accurately how a diverse society feels.
Inspiration
The Covid-19 pandemic shook the world to its foundations, causing unimagined turmoil and uncertainty affecting many aspects of our daily lives. To find out how the society feels at a certain moment in time is of great interest for many - from policy makers who want to make the 'right' decisions over social entrepreneurs who want to improve the welfare of the society to reporters who want to cover the most important topics of public interest.
Therefore, the big challenge is:
How can we find out the current state of the emotional well-being of society, across all demographics?
What it does
We combine several data sources from public APIs to provide an accurate description of how the whole of society thinks and feels. Textual data from social media, on the one hand, explicitly reveals opinions, doubts and reactions. Music, on the other hand, in textual as well as acoustical form captures states of mind and emotions in several dimensions that can be quantified and yield powerful predictors of overall sentiment and preferences.
An interactive map of Switzerland plots the most recent (past 7 days) geo-tagged English/German Tweets that have been classified based on their sentiment (red: low sentiment, sadness; green: positive, happiness) over time. Free text search allows to filter Tweets related to Covid-19.
Thanks to our extendable modular architecture the application can be expanded and its self-maintained data base / webscrapers make it a valuable tool for users such as journalists.
How we built it
We currently use data from Spotify and Twitter and validated the possibility to use data from YouTube and Swisscom.
Spotify
Music streaming has overtaken other kinds of music distribution in the recent years. 55% of Spotify's user base are millennials from all social classes (
Source
).
Spotify publishes the song streaming charts on the country level on
spotifycharts.com
. Academic research shows that there exists a clear correlation between a person's mood and the type of music they are listening to (
Source
). Furthermore, we used the Musixmatch API to retrieve lyrics by songs found in the daily charts for Switzerland.
Twitter
Twitter is one of most well-known and
largest
social networks, not only but also because of the enthusiasm with which the current American president Donald J. Trump uses it.
It has a long history of being used for trend recognition - both in an academic (
example
) and medial setting.
Using Twitter in addition to other indicators proves to be stable and provides valuable sentiment insights.
Future work: Swisscom
Swisscom is the largest telecommunications provider in Switzerland, and covers the larger part of the mobile communication market in the country.
Developers can use Swisscom's API to access anonymized data about the number of people that are within given 100m by 100m squares throughout the day.
The data doesn't provide sentiment information directly - but it is possible to use mathematical properties such as the Entropy principle to infer this knowledge in a postprocessing step.
The big advantage of Swisscom's data is that it covers, unlike the other data sources we identified, everyone who owns a mobile phone - all demographics and most age groups.
Future work: YouTube
YouTube can also be seen as a social network and is more widely used than all other social networks in the US.
Thanks to the YouTube API and other
tools
, using this data for sentiment analysis is possible as well.
However, this requires extensive preprocessing as the sentiment of each video must be analyzed, which is not a trivial task.
Architecture
The architecture can be separated into three parts: Data-Mining, Backend and Frontend.
The datamining is done with Python.
The Spotify charts are scraped from
https://spotifycharts.com/regional
.
The Spotify API is accessed with the Python library 'spotipy'.
The sentiment of the songs is determined according to their audio feature 'valence'.
Song lyrics are obtained with the Musixmatch API.
VADER sentiment
, a high quality academic sentiment analysis library, is used to analyze if a songs lyrics and a Tweet is positively or negatively connotated.
The prepared data is stored in databases on Microsoft Azure.
The backend server uses flask.
The interactive map on the frontend was built using
d3.js
.
Challenges we ran into
Acquiring high-quality and relevant data seemed difficult for us. The big dataset provided by EPFL and SRF with overall 2.6M tweets related to Corona wasn't specific to Switzerland. Therefore, we had to pivot to our own tweet extraction pipeline which was unfortunately limited to the constraints of Twitter. However, we were able to handle everything life threw at us by taking a deep breath and remembering the body movement exercise from migros at the opening ceremony.
Accomplishments that we're proud of
We propose the usage of different data sources for trend and sentiment analysis in times of social and economic uncertainty such as the Covid-19 crisis. We demonstrate the effectiveness this approach has for this purpose.
What's next for CHemotion?
Add more data sources to the pipeline - for example Swisscom and YouTube as discussed before.
Built With
azure
d3.js
flask
html
javascript
jupyter-notebook
mako
python
shell
spotify
spotipy
tweepy
twitter
Try it out
github.com
chemotion.live | CHemotion | Estimating how a diverse society feels across demographics by aggregating different data sources | ['Gerome Wolf', 'Jonathan Janetzki', 'ugur sahin', 'Christoph Tittel', 'Jeremias Baur'] | [] | ['azure', 'd3.js', 'flask', 'html', 'javascript', 'jupyter-notebook', 'mako', 'python', 'shell', 'spotify', 'spotipy', 'tweepy', 'twitter'] | 36 |
10,526 | https://devpost.com/software/meal-hack | Overview
Week Overview
Explore new recepies
Cooking stress-free
Roadmap for the weekend
Ideation Nation
Work Hard
Who said hackathons were unhealthy?
Meal Planning, by Hackers, for Hackers
Inspiration
Eating is both a necessity, and something to be enthusiastic about. For some, time is scarce as their time is better spent elsewhere. For others, the ecological impact of their food consumption matters more. Everyone has a very different relationship to food, and we wanted to capture this by making an application that everybody could use to plan their meals more sustainably, and efficiently.
What it does
The key idea was to offer users the possibility to plan their meal for the week, and easily synchronize that with an integrated groceries list - saving our users countless hours of staring at an open fridge, wondering what they'll cook that night, before settling for ordering take-out. We think home cooking should be fun and stress-free!
How we built it
We focused on developing the core ideas behind our mission statement. Therefore, we started by applying principles of user-centered design: defining typical customer profiles, and identifying what they would take out of the app. We estimated customer pain points, and used those to establish customer journeys, as well as determine what tasks should be accessible.
Saturday, after a good night's sleep, we started working on a mobile user interface in flutter, and strived to create the main screens that would define the app. In parallel, we started developing the back-end required to power our idea. We used a MongoDB database, in conjunction with a RESTful Flask server architecture. The Migros Recipe and Product APIs provide us with a great wealth of information. Luckily for us it is one of the most complete sources available! The recipe API provides us with all the information we need to be able to suggest meal plans to our users, while the information contained in the product API ensures their purchasing decisions stay aligned with their ethical and moral goals. Furthermore, we rely on the Eaternity API to compute the nutritional and ecological impacts of our recommendations.
Challenges we ran into
Our main challenge was understanding how we could help solve a problem many people have become accustomed to.
We unfortunately underestimated the amount of time it would take to learn to use Flutter. We should have chosen a front-end framework that allowed fast and efficient design iteration.
Accomplishments that we're proud of
We are proud of having thought in terms of problems and not solutions. We believe all problems can be solved, and we should focus our attention on the important ones.
We are proud of having established detailed customer journeys as well as developing a good understanding of their wishes and needs.
We are also very proud of taking the time to sleep on Saturday, even if the urge to start hacking made it very difficult.
What I learned
Luigi learned UI/UX design in flutter, and Adobe XD, as well as some state management using futures. Samuel learned more about what goes into a back-end system, and got a glimpse of the full stack. David had the chance to work on the most complicated app he'd ever designed, as well as work with a RESTful API. Danil learned how to create a full tech stack and how to manage a NoSql database. Overall we all gained experience in Systems Architecture as well as User-centered design.
What's next for Meal Hack
A clean and intuitive interface. a picture scanner, and a recommender system.
Built With
android
flask
flutter
mongodb
python
Try it out
github.com | Meal Hack | Hacking meal planning | ['David Oort Alonso', 'Danil Ivanov', 'Luigi A. A. S.'] | [] | ['android', 'flask', 'flutter', 'mongodb', 'python'] | 37 |
10,526 | https://devpost.com/software/_dummy-bk7lru | statistics supporting our cause
splash screen
results
Inspiration
2020 has changed work towards remote
. However, studies show that for many people working remote
100% is not preferrable
.
People name collaboration, communication problems, and general loneliness as reasons to return to the office
.
Looking forward we expect that more teams will follow a mixed approach, with the majority of team members coming onsite for 2-3 days. It becomes essential to coordinate in order to get the most out of it - ideally, people who work on the same projects should come in on the same day to get the most benefit. However, deciding this for many people over channels like chat is cumbersome and inefficient.
What it does
Onsite day calculator is a voting platform that takes individual preferences and returns the best possible onsite day. Under the hood it computes two scores for each day, Average Preference Score and Synergy Scores using our crafted formula. The two scores are used to produce a single number for each day which shows how good will it fit the team as the onsite day this week (day when everyone joins).
How I built it
It started with Ilya and Alex planning to work together from Aachen, Germany. We are both backend engineers with broad experience but don't have much experience in the front-end. We teamed up with Leo from North Macedonia who is a full-stack wizard and created it with python and js.
Challenges we ran into
Remote work is never easy :)
Detailing out a seemingly simple solution reveals a lot of hidden difficulty
Designing for a simple UX needs many trade-offs
Accomplishments that I'm proud of
We were building for quality, making sound design decisions and covering the application with unit tests - this helped us avoid any overhead for debugging, and increased confidence in our app. We were able to ship fast and get to a working solution that was hosted.
What I learned
That even an idea that looks simple hides a lot of challenges before it's operational. We have changed the API and data model quite a lot after making the first prototype, as it helped us understand use cases a lot better.
What's next for Onsite Day Calculator
make the app more scalable and robust to be able to serve many concurrent users but remain free
integrate with Google Calendar and Office365 to enable a simple on-boarding of new teams
use machine learning and historical data to see when actual preference of users differ from what they specify in the system. this could be a paid feature
allow for scheduling for a longer period than just one week
Built With
flask
python
vue
Try it out
on-site-day.herokuapp.com | Onsite Day Calculator | Find the best onsite day to maximize your team's synergy. | ['Leotrin Elmazi', 'Alex G', 'Ilya Kamenshchikov'] | [] | ['flask', 'python', 'vue'] | 38 |
10,526 | https://devpost.com/software/teamlife | TeamLife - Kickstart your office social life
TeamLife - Figma Design Prototype
VIDEO LINK:
https://naef.lu/TeamLife.mp4
Teamlife
Inspiration
During the pandemic meaningful social interactions with our co-workers have become more difficult than ever.
TeamLife is here to solve this!
What it does
With challenges in categories like running, reading, cooking and photography there are plenty of experiences to be had, and shared with your team members.
The challenges are supposed to help engage you and your team in experiences and facilitate sharing them with one another.
TeamLife features an activity feed, showing all the recent activities happening in your team, as well as a leaderboard, with the most active team members on top, as well as an overview of the currently on-going challenges and a place to log your activities.
How we built it
First off we created a
UI/UX prototype with Figma
, here we could quickly create different stunning Views and manage the flow between them.
After this concept seemed promising, we started building TeamLife. At first, we were unsure whether to use Azure Static-Web-Apps or Flutter. Out of personal interest the decision fell on using the modern cross-platform Flutter framework, with this we will be able to easily deploy iOS, Android, Desktop and Web versions of TeamLife. The backend runs entirely on Google Firebase, using Cloud Firestore as a cloud-hosted NoSQL database. This technology stack allows fast development cycles and easy adaption to growing workloads and changing requirements.
Challenges we ran into
The first night was used almost entirely for idea finding and design prototyping, this pushed us to work as much as possible during the time left. With problems installing Flutter and Android Studio the timeline got even tighter throughout Saturday.
With no prior knowledge of Figma, Flutter or Firebase there were many questions to be answered and a lot of documentation to read! Perhaps choosing a technology at least one of us knew would have been smarter.
Accomplishments that we're proud of
We are extremely proud of having a good looking and well thought out design prototype that we managed to translate almost entirely to our functional prototype.
Also the number of new technologies we picked up over the weekend surprises us time and again and we are happy to have invested the extra effort into building our app with unfamiliar tools.
What's next for TeamLife
TeamLife has a working design and an almost finished functional prototype, however they do not quite match entirely. For a useful product features like a (video-)chat, more challenges and categories as well as the ability to create own challenges are still missing.
But thanks to easy SSO and OAuth integration with Firebase we are prepared for integration into existing company authentication infrastructure and kickstart your office's social life!
Built With
android-studio
dart
figma
firebase
flutter
ios
Try it out
github.com
www.figma.com
naef.lu | TeamLife | We aim to solve the problem of declining social interactions during home office and quarantine times. On TeamLife you can go head to head with your coworkers in small challenges after work. | [] | [] | ['android-studio', 'dart', 'figma', 'firebase', 'flutter', 'ios'] | 39 |
10,526 | https://devpost.com/software/shopwime-754jvx | Inspiration
What it does
Often you buy more than will fit in your pocket in the end. With ShopWime you can plan your shopping and see how full your bag is.
To do this, you can create your shopping list from over 130,000 products. The price and fill level of your bag is automatically displayed.
Selected filters allow you to empty your shopping list in order to reduce the filling level of your bag. In addition to sorting out large products, you can also decide based on your last purchases.
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for ShopWime
Built With
c#
unity
Try it out
link.awesome-co.de | ShopWime | Your shopping bag overflows? Organize your shopping and watch the level of your bag | ['Gerd Schmidt'] | [] | ['c#', 'unity'] | 40 |
10,526 | https://devpost.com/software/driver-assist | Thomas's new eyes
Regard to the challenge proposed by Siemens Mobility, we have developed this project to help train drivers to navigate under poor vision conditions.
Using the prerecorded videos of the rails, the clear view of the driver from the current scene is shown in the application.
Film: In this demonstration you can see the drivers view of the track on the right and the output of the application on the left. The precise output is generated by processing data from two resources: The GPS signal and the timestamp of the video frames. To overcome the inaccuracy of the time stamps the GPS signal is used.
Built With
mongodb
opencv
python
Try it out
github.com | Thomas's new eyes | A tool for train drivers inspired by the "Lift the Veil workshop" - HackZurich 2020 | ['Omid Najafi', 'Alireza Zohri', 'Ali Gorji'] | [] | ['mongodb', 'opencv', 'python'] | 41 |
10,526 | https://devpost.com/software/oho | Welcome to OHO
The OHO Team
OHO - Your shopping assistant
How OHO works
Give the OHO prototype a try!
What it does
The app provides the users detailed information about the products from the migros store.
How we built it
We used Angular as our frontend and NestJs as our Backend Framework. We also used the Migros API and Google Could Platform.
We trained the Machine Learning model on a handful of manually labelled and at the hackathon taken images of the following products:
Kult Ice Tea Pfirsich (0.5l):
https://produkte.migros.ch/kult-ice-tea-pfirsich-120299300000
M-Classic Chicken Sandwich:
https://produkte.migros.ch/m-classic-chicken
Pepsi Twist (0.33l):
https://produkte.migros.ch/pepsi-twist
Pepsi Regular (0.33l):
https://produkte.migros.ch/pepsi-regular
YOU Powerful Mix:
https://produkte.migros.ch/you-powerful-mix
Risoletto Classic:
https://produkte.migros.ch/risoletto-classic-101503600000
Challenges we ran into
We tried to connect to the eaternity API provided by the IBM/SwissRe challenge, but simply cant get the migros products processed to get useful outputs.
Accomplishments that we're proud of
Delivering an new awesome possible solution for blind customers.
What's next for OHO
There are so many possible integrations, having the digital product twin on my hand. One could integrate with some "digital pill" for diabetes, make a connection to your personal nutritionist and so on...
Built With
angular-material
angular.js
docker
font-awesome
google-vision
node.js
progressive-web-app
Try it out
hackzurich2020.thedev.de
github.com
github.com | OHO | From ah to oho in a single snap – en Güete zäme | ['Timon Schmid', 'Donato Wolfisberg', 'David Gataric', 'Christian Scharr', 'Kishan Thodkar'] | [] | ['angular-material', 'angular.js', 'docker', 'font-awesome', 'google-vision', 'node.js', 'progressive-web-app'] | 42 |
10,526 | https://devpost.com/software/silver-screen-x4aiod | Landing page
Login Page
Signup Page
Movie Details
Series Details
Movie Search
Series Search
My List
Inspiration
We are inspired by the movies created in the history of cinema. Their work motivates us to build a small movies information website.
What it does
It provides the information of different movies
How we built it
We built using ReactJS for frontend of our project and with the help of TMDB API we come to the result using firebase.
Challenges we ran into
Integration of firebase and ReactJS. We also ran into CORS error with TMDB API.
Accomplishments that we're proud of
Now we could be able to find information of any movie in our own platform.
What we learned
Team Work, Languages
What's next for Silver Screen
We would make
We would make movie recommendation system using ML.
Built With
firebase
javascript
node.js
react
reacthooks
tmdb-api
Try it out
silver-screen-76c12.web.app | Silver Screen | One Platform for all your movie related doubts. | ['DHANANJAY SHARMA', 'Vardhika Jain', 'Divyam Shrivastava'] | [] | ['firebase', 'javascript', 'node.js', 'react', 'reacthooks', 'tmdb-api'] | 43 |
10,526 | https://devpost.com/software/worky-talky | Want to interact?
Virtual office space
Let's talk!
Inspiration
Looking through the numbers and reports from remote workers, we can see that one of the most disruptive problems to tackle is loneliness. It can affect motivation and productivity and even cause mental health issues as it is really hard to feel connected to co-workers at a distance. Having this in mind, we wanted to develop a fun tool, that would serve to encourage people to connect on a daily basis and bring interactions that happen all the time in the office into the virtual world.
What it does
WorkyTalky is a realtime gamified virtual office environment, where people are represented by characters. Co-workers can interact with each other by sitting for a lunch together in the cafeteria, having a coffee on the balcony, chatting in the meeting room or just bumping into each other in the hallway. The virtual office is designed as a game, so players have fun using it and moving around. By doing so, whenever in the proximity of another player or interactable object, they are prompted to connect to other user(s) through an interactive video chat, supporting plenty of activities. The chat is automatically generated, which makes reaching out to others quick and simple. Those who want to have lunch together can then meet up in the cafeteria, or work together at a desk, or even have a workout after office hours are over. Our app makes hanging out in the office fun and easy, by which we help and encourage co-workers to do more activities together.
How I built it
We used React, Node.js, Socket.io for data transmission and Heroku where we deployed our solution.
Challenges I ran into
Too many ideas and too little time! :) We managed to implement the basic functionality, but unfortunately ran out of time to add some features for a neat user interface, like personalized characters for users, more office colors, the calendar widget, etc.
Accomplishments that I'm proud of
The app is actually running live and functioning properly :D We managed to implement the basic functionality, but unfortunately ran out of time to add some features for a neat user interface, like personalized characters for users, more office colors, the calendar widget, etc. Therefore, we currently integrated our solution with Zoom, while we'd like to create our won add-ons for the video chatting in the long term.
What I learned
As this was the first React 2D web game we ever created, there was a lot to learn about making our game engine. We are both also beginners at Node.js backend development and Socket.io, so that also took some tutorials to get it running.
What's next for Worky Talky
Uh, where to begin! We would love to enhance the game aspect of the app and add new activities, but we are also thinking about creating something like this to support personal relationships, especially friendships, as we are best friends living on two different sides of Europe.
Built With
heroku
node.js
react
socket.io
Try it out
serene-temple-32758.herokuapp.com | Worky Talky | A virtual office that brings back that "being there" factor for staying in touch with your co-workers. Move around, eat together in the cafeteria, bump into someone on the way. Second best to reality. | ['Neza Dukic', 'Patricija Brečko'] | [] | ['heroku', 'node.js', 'react', 'socket.io'] | 44 |
10,526 | https://devpost.com/software/mnjammnjam | Inspiration
The idea of the app starts from some vegetables that stayed too long in our fridge and went bad. We wanted to have one app that records our fridge status and remind us about food ingredients that we need to consume in time. Later it got developed to generate recipes according to our food storage and personal interests, due to Covid 19, cooking becomes the main activity for many people.
The online recipes often have too many ingredients that not avaliable right now. We want to use this app to help people make efficient decisions about what to cook.
What it does
We built a web app that recommends recipes to the user based on available ingredients and user's preferences. User can swipe recipes in a tinder style to the left or right, eventually finding a match based on the ingredients at your home. Further, users can add new items to available ones simply by either scanning barcodes of the products, or scanning the products themselves and can obtain nutritional scores about the items. Based on given preferences defined in the app, matches are selected by e.g. your goal to get healthier by eating less fats or your choice of cooking more challenging recipes.
How we built it
We started off with a simple story, to understand better who Bob is and what Bob needs. Bob is you and just wants to know what he can cook from the stuff on his fridge and adapt his meals to his preferences. We decided to develop a web app for our purposes and chose django framework with mongoDB as the database. We utilized the APIs for food recognition and barcode scanning that were provided during hackathon.
Challenges we ran into
None of our team members had much experience with web app development, nor with available frameworks. It turned out to be challenging to solve problems on our way while learning at the same time, given the short time.
Our team was split between onsite and remote participation and that was also not easy to keep each other perfectly in a loop, or brainstorm effectively via videochat.
Accomplishments that we are proud of
Despite that, we were happy to have learnt a lot, explore the world of web development, accomplished our minimal viable product and most of all had fun that we participated for!
Built With
django
mongodb
python
Try it out
gitlab.com | MnjamMnjam | Your dream food, just a swipe away. | ['Heiko Donat', 'Sarah Lutteropp', 'Qiusha Fan'] | [] | ['django', 'mongodb', 'python'] | 45 |
10,526 | https://devpost.com/software/di-pizza-trax72 | Welcome screen
Actual scan from a pizza
Mobile view after pizza recognition - ingredients
Desktop view after pizza recognition - ingredients
Mobile view of nutrients
Nutrients overview on desktop
Real time data dashboard
Frontend code
Backend code
Inspiration
Using computer vision we wanted to discover new ways to interact with products. We were looking for a specific use case that was doable in the short amount of time. We all loved pizza and from often checking out pictures of pizzas at restaurants, we thought we could detect ingredients and suggest the most sustainable product from the product assortment to buy it in your local grocery store to make your dream pizza! Obviously the idea would be to extend this to all kinds of food and not only specifically pizza.
What it does
One can easily take a picture or upload a picture of their favorite pizza. Then, we detect the used ingredients and find the most sustainable product from the product range in your local grocery shop.
How we built it
We built it using the API from Migros for product search, cross-referencing it with the API that IBM offered in order to get a CO2 footprint. The backend was built with python and the frontend as a webapp using javascript, html and css.
Challenges we ran into
Coordination accross timezones was not that easy, but in the end we think we successfully overcame this challenge! Furthermore, we had a lot of trouble getting an adaptable computer vision model set up in order to properly detect ingredients using state-of-the-art ML algorithms. In the end, we had to give up due to time constraints and went with plan B using a smaller neural network with faster training times. One team mate had trouble with energy supply in India, hence, we had to properly coordinate to not lose the made progress.
Accomplishments that we are proud of
We are proud to integrate a random team mate from around the globe. We are proud on the running prototype. We are proud on our organization. We are proud to be part of the largest hackathon in Europe!
What we learned
We learned to prioritize time planning such that it is possible to have an MVP asap and then keep expanding from there. We learned about MongoDb. Some of us learned about flask as a dev tool.
What's next for Di Pizza
Win hackzurich 2020!t
Built With
css
flask
html5
javascript
mongodb
python
Try it out
github.com | Di Pizza | Using our webapp you can find the most sustainable ingredients for your pizza. For this reason simply take a picture with your phone and see ingredients with their co2 emission and nutritional value. | ['Gaurav Sethia CSE-2018-22', 'André García Gómez', 'Michael Mazourik', 'Shubhayu Das', 'Severin Husmann'] | [] | ['css', 'flask', 'html5', 'javascript', 'mongodb', 'python'] | 46 |
10,526 | https://devpost.com/software/covidscare | World Map
Swiss Map
Inspiration
The pandemic is the main topic at the moment and follows us everywhere. Not all people are affected to the same extent and through this challenge, we wanted to explore feeling patters around the globe.
What it does and how we created it
World Map
We started with the Twitter dataset we had been provided with. It was relatively easy to reverse geocode the data, since we were provided with coordinates. We've used a python package called
reverse-geocode
for this process which is an offline and quick solution. The module has a set of known geocoded locations and uses a k-d tree to efficiently find the nearest neighbour. In our perspective, the main challenge with the Twitter data was to make it useable for a map/chart. Since the Twitter dataset contained tweets from all over the world, we decided to portray our results in a world map. Of course, the number of Twitter users needs to be taken into account when calculating the Scare Level of a country and since this data wasn't available for all countries, we decided to approximate the figure using the country's population. Furthermore, the Tweets per capita numbers were normalized into a scale from 0 to 100.
Switzerland
For the SDM data, we focused on Switzerland which is also the main aspect of the challenge. At first, we tried to use natural language processing (NLP) to extract location names (Name Entity Recognition). However, we weren't able to achieve desirable results with our approach: processing the big amount of data wasn't possible for us in a reasonable time. Therefore, we switched to another technique using keywords to detect locations and assign them to their correspondingg canton. Similarly, using keywords, we tried to detect news articles which were related to Corona. In the map itself, the ratio of articles that mention a specific location and Corona vs. total amount of articles that mention the location is displayed and is our interpretation of the "Corona Scare Level" in Switzerland.
How we built it
We decided to implement our project as a small web application using a Python backend (Flask) to do the data processing. On the frontend, we used the Datawrapper API to create the visualizations. Used programming languages and important packages:
Python 3.7.9
flask
pandas
reverse-geocode
scikit-learn
datawrapper
HTML/CSS
Bootstrap
Embed Datawrapper iFrame
Challenges we ran into
We were struggling a lot to achieve desirable results using Name Entity Recognition, especially due to the long processing time. Therefore, we switched to alternative techniques for basic location matching, as mentioned above.
Accomplishments that we're proud of
It being our first hackathon, we are happy that we were able to get something running and even having something to submit. The whole event was definitely a great experience and we are proud that we were able to tackle and solve one of the challenges.
What we learned
The project helped us improving our skills needed to create a web app. On the one hand, we were able to apply our knowledge on backend programming and practice the use of frameworks such as Flask. Moreover, we acquired additional know-how on how to handle and process large datasets.
Last but not least, we gained many insights into the whole Hackathon experience and are now ready and highly motivated to join other developers and tackle new challenges in our next Hackathon.
What's next for CoronaScare
Since we are rather unexperienced programmers, our main focus for the project was on having a more or less "finished" and working "product" rather than putting a lot of effort into details and precision. The user interface could be made more appealing, the data processing has many possibilities for improvement (use name entity recognition/machine learning, better approaches to compare scare level of different countries/cantons, speed up processes) and other features would be desirable such as the possibility to select a time span etc.
Built With
bootstrap
datawrapper
flask
python
Try it out
github.com | CoronaScare | Corona Scare Level visualization based on Twitter and news data | ['Nicolas Filliol', 'Joel Asper'] | [] | ['bootstrap', 'datawrapper', 'flask', 'python'] | 47 |
10,526 | https://devpost.com/software/epiphany | Inspiration
We want to help people use technologies to increase their happy time, yet most social media is designed to increase general time spent, usually resorting to psychological tricks. Current ways to treat social media addiction are primitive and don't follow addiction treating research. We want to focus on hard science to do it well.
What it does
We take a data-oriented personalised approach to learn the user's habits and then take adequate steps to promote reduction of their unhappy time - not by blocking, but via motivation to do something else.
First we learn when the user is spending "happy time" and "unnecessary time" on social media. In the latter case, we take slow, but gradual steps to reduce their obsession - first by promoting what better they could do based on analysis with the Huawei APIs, then by self-reflection.
How we built it
We wrote an android application which monitors social media use habits, as well as additional data to help us classify "happy" vs "unnecessary" time. In addition we learn the user's general activity habits and hobbies and use this to make proposals when they spend unecessary time on social media.
Challenges we ran into
Android, perhaps for a reason, has not made it easy for apps to monitor activity within other apps. We spent a lot of our time debugging to get our data collection working.
Accomplishments that we're proud of
Apart from managing to debug this and still get a demo out, we're happy that we managed to also use Huawei's APIs to detect and analyse the user's usage habits for better personalisation.
What we learned
Don't underestimate the complexity of native android.
What's next for Epiphany
Launch the MVP and fingers crossed!
Built With
android
bigdata
huawei
kotlin
science
Try it out
github.com
github.com | Epiphany | A social media addiction treatment that actually works. It is smart - leveraging psychology research for self-awareness and a gradual personalised approach. | ['Zvezdin Besarabov', 'Yong Hoon Shin', 'Elisa Garulli', 'Jakub Mularski'] | [] | ['android', 'bigdata', 'huawei', 'kotlin', 'science'] | 48 |
10,526 | https://devpost.com/software/maggi | Maggi Dashboard
Job Submission (Step-1): Code Submission
Job Submission (Step-2): Providing execution parameters
Job Submission (Step-3): Choosing compute profile
Job Submission (Done): Job successfully submitted
Architecture
Inspiration
Due to the pandemic, a lot of people have lost access to their high-powered workstations in the office and are forced to work on comparatively weaker hardware i.e. unless you were willing to transport the whole desk to your place or by investing in expensive cloud solutions, not exactly the easiest pills to swallow for most people.
Having to wait 10 times the usual time for your code to compile definitely takes the magic out of the whole process. The challenge set by Logitech to re-imagine the future of digital work only further cemented our decision to work towards solving this problem.
And with the world barrelling towards decentralized systems, it only seemed natural for us to progress down the same road. And that’s how we came up with Maggi, an open-source decentralized computing platform, aimed at bringing high-performance computing to you.
What it does
Maggie is a community-driven decentralized platform for computing. Put simply, every user will have the ability to contribute as well as make use of the platform for their own creative purposes.
In the case of our MVP,
•Users will be able to submit their code as a text file using a storage method of their choice (torrents or S3
buckets) as a job request.
• Suitable nodes on the network will then complete the request and send the output to the user.
• We also have a token reward system in place to incentivize users to contribute to the network.
How we built it
Pitching Video
Challenges we ran into
As of now, we still haven’t managed to entirely decentralize it as we still require a master node to delegate job requests to suitable nodes. However, since the master node isn’t exactly involved in the computing process, we don’t consider this a dealbreaker.
Accomplishments that we're proud of
We are definitely super proud of ourselves for coming up with an MVP in this short span of time. We certainly believe that this project has a lot of potential and definitely intend to work on this moving ahead.
What's next for Maggi
We intend to have it be fully flexible to adapt to other domains as well in the future.
We also hope to implement a solution to make maggie completely decentralized, eliminating the need for a central master node.
Built With
amazon-dynamodb
amazon-web-services
angular.js
jython
s3
springboot
sqs
Try it out
github.com
github.com
github.com | Maggi | Paving the way to a decentralized ecosystem. | ['Vishnuvardhan Prem', 'Sangeetha Pradeep'] | [] | ['amazon-dynamodb', 'amazon-web-services', 'angular.js', 'jython', 's3', 'springboot', 'sqs'] | 49 |
10,526 | https://devpost.com/software/mirror-office | Inspiration
The massive change to working at home has made collaboration for work hard.
Even though there are a plethora of video chat apps, they are used in crowded meetings where regular social interactions are impossible.
Spontaneous chats and casual conversation have died out: calling someone without prior notice or reason is rare.
By losing the sense of a shared workspace, not seeing other people work, one also loses motivation.
This has created a major hit in productivity, as well as a degradation in mental health among a wide range of people.
We propose a professional telepresence platform to connect users in a virtual office environment.
What it does
We simulate a virtual office, where each connected person has a position in the virtual office.
You can hear people in your proximity and talk to them, and move around to people at their desks or at the coffee machine.
Simply connect with your phone or browser when you start working and see other people connected in the area.
Our provided demo works on a 2D top-down map of a sample office.
Users can log in and move around on the map and talk to other logged in users.
Voice volume depends on the proximity
and orientation of other users
.
This enables to walk up to anybody who is currently logged in and start casual conversations.
Say a few words to your co-worker on the way to the coffee machine!
How we built it
We used React and Meteor to build this project.
What's next for Mirror Office
Changing the implementation to a 3D office environment would be the first step. Implementing support for VR and AR visualization would be the next:
If the virtual office layout is the same as the layout of the physical office, remote workers could use VR to be present in the virtual office, while onsite workers could use AR to see/interact with people in the virtual office.
People could also use different customizable avatars for the 3D space.
Built With
javascript
react
Try it out
github.com | Mirror Office | Professional Telepresence Platform for Social Communication | ['Artur Grochal', 'Jonathan Lehner', 'Utkarsh Bajpai'] | [] | ['javascript', 'react'] | 50 |
10,526 | https://devpost.com/software/gethealthy | homepage
dashboard
bunty
survey
Inspiration
In Switzerland, 1 adult on 4 doesn't do enough weekly sport, according to the Federal Office of Statistics[1]. Sadly, it has also been shown that there is a clear correlation between one's education/socio-economic level, with the amount of sport one does. People that are already marginalized or from a lower socio-economic level are shown to do less sport. [1]
1. What it does
It connects people who wish to motivate less sporty people, with couch-potatoes. With the money incentive, everyone can earn money by doing sport.
As shown in the demo images:
user is welcomed by the homepage with sign-in promotion if not completed already.
dashboard lists all the possible exercises with user activity data.
bounty page, as the name suggests, shows
2. How we built it
The GetHealthy web app is powered by the
Flask
framework and is implemented with posnet, opencv and tensorflow.js for motion detection.
.
├── README.md
├── benchmark.py
├── flaskr // main Flask project
│ ├── __init__.py
│ ├── __pycache__
│ ├── db.py
│ ├── posenet. // posnet for motion detection
│ ├── static // static files
│ ├── templates // web pages
├── get_test_images.py
├── main.py
├── setup.py
└── venv // virtual env
3. Challenges we ran into
3.1. How to provide smooth-less UX
One of the major problems we ran into is how to render the exercise videos without any hindering. Because to ensure a great user experience, the exercise video must be presented in real time with motion detection enabled. Due to the natural computing power constraint of the web application, after the investigation of possible solutions, we chose to go with posenet, a pure Python implementation of Google's tensorflow.js because it is relatively light-weighted, easy to implement, and are more compatible with Flask framework.
3.2. How to optimize the performance
This part is closely tied to eliminating redundant codebase and minimizing memory usage. It is obvious that available memory should be large enough to support the smooth video rendering. And this is also one of the reasons that we choose Flask so that we can utilize the templates content and static files without getting any duplicates. Also, the cache folder does not hold history files for too long before they are removed from the system. Obviously, there are still some techniques like directly embedding a pure C++ port within to process the data, an JS engine for transfer, and having a better CPU for demo(or support wider hardware frameworks) to optimize the app performance, but our exception has been reached due to the limited time.
4. Accomplishments that we're proud of
4.1. Responsive design for better UX
Some of our team members are not really familiar with web UI and Flask framework before the hackathon but we are proud to say that we made a decent demo in such short period of time, and we are excited to try new tools and tech stack. Apart from the basic functionalities, we added responsive UI so the user can have a better time experiencing the product and it's a rewarding experience to see our product from UX designers' view.
4.2. Real-time motion detection with Posenet
We embedded
Posenet
, a pure Python implementation (multi-pose only) of the Google's
TensorFlow.js
. After it is enabled, we can show the webcam runs inference on an input folder of images and outputs those images with the key points and skeleton overlay.
4.3. Teamwork
This year HackZurich has been an unforgettable challenge. Not just because the amazing challenges we get to solve, but also because it's happening during this unprecedented time(special thanks to the HackZurich team!). Our members come from three different time zones and two are joining onsite while the other three are joining virtually. We are proud of what our collaboration project can accomplish and how teamwork made all this possible.
5. What we learned
How to work in a diverse team;
How to work under deadline;
How to learn new technologies and implement them to meet the user need;
How to connect technology with business need.
How to better communicate;
6. What's next for getHealthy
We will thrive to make sure we could bring great exercise experience for our users, help those in need, connect people from different communities and bring the world closer together. We are a platform that greatly values the data privacy of our users and will never betray your trust to violate their privacy. We hope to reach a wider audience group and bring in more financial resources for funding.
Sources:
[1]
https://www.bfs.admin.ch/bfs/fr/home/statistiques/sante/determinants/activite-physique.assetdetail.9546739.htm
[2]
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2743027/
[3]
https://github.com/rwightman/posenet-python
[4]
https://opencv.org/
Built With
bootstrap
css3
flask
git
github
html
javascript
jquery
markdown
opencv
posenet
python
sqlite
tensorflow
Try it out
github.com | getHealthy | Pay lazy people to do sport | ['Olivier Cloux', 'Shreyasvi Natraj', 'Danni Li', 'Shachindra Kumar', 'Oscar Pitcho'] | [] | ['bootstrap', 'css3', 'flask', 'git', 'github', 'html', 'javascript', 'jquery', 'markdown', 'opencv', 'posenet', 'python', 'sqlite', 'tensorflow'] | 51 |
10,526 | https://devpost.com/software/don-t-panic-vmyxfr | View by country
View by City
System Overview
Machine Learning Pipeline
Inspiration
Aren't we all tired of hearing day-in and day-out negative news?
We decided to break the cycle and bring back positivity by showing that people are full are good sentiment!
What it does
Our service gathers and analyzes the sentiment from extracted news articles from the Schweizer Mediendatenbank (SMD) and a list of Tweets pre-selected by SRF.
After being interpreted by our NLP algorithm, everything is displayed on a map by country or by city to compare the general sentiment between news and tweets in different region. You can also filter the news by topics
How we built it
Our service is comprised of two mains components running with two independent life cycles. The first part having the task to process, analyze and extract the sentiment of the articles and the tweets using Natural Language Processing (NLP) provided by the Text Analytics Cognitive Services from Microsoft Azure which will then be uploaded into MongoDB. The second part is a WebApp built with a Spring backend and a Vue.js frontend able to querying and aggregate the data to plot the general sentiment of the news and tweets on a Map built with Google Charts.
Challenges we ran into
Find a meaningful and innovative way to represent the sentiment between two types of media (article vs tweet)
Figure out the impact of the newspaper at a specific location
Accomplishments that we are proud of
Bringing a fully working prototype while successfully integrating multitude of technologies in such a short time.
What we learned
Microsoft Azure Text Analytics Cognitive Services
Google GeoLocation Service with Google Charts
What's next for Don't Panic
Include new news outlets in other countries and continents
Improve the visualization of sentiment over time
Visualize the impact of the media on the tweets
Built With
azure
cognitives
google
java
mongodb
python
spring
textanalytics
vue.js
Try it out
gitlab.com
dontpanic-fe.herokuapp.com | Don't Panic! | Aren't you tired of only hearing about negative news? Don't Panic! We have something that will brighten your day! | ['Mauricio Enriquez Calle', 'Danilo Djordjevic', 'Marcos Carbonell', 'Thomas Denoréaz'] | [] | ['azure', 'cognitives', 'google', 'java', 'mongodb', 'python', 'spring', 'textanalytics', 'vue.js'] | 52 |
10,526 | https://devpost.com/software/work-7uhxyi | WŌRK makes remotes teams feel close - with their own virtual office space
Screenshot of the app in action
A spontaneous video call via WŌRK
It's the small interactions that make a workplace feel like a community and we help bringing your virtual company space to your home office. With WŌRK you can stay connected with your friends and colleagues at work no matter where you are.
PROBLEM
The COVID-19 pandemic wreaks havoc among how we as human beings connect, interact and work together. We're not only disconnected from our loved ones, but especially distributed virtual teams suffer from a lack of human contact and connection. So much of a healthy social life and a good work climate depends on small talk, coffee breaks with one another, knowing what the colleagues are working on and seeing that there are other people around oneself working towards the same goal. As such we're not looking for more efficiency, but more humanity when workers cannot meet in person.
WŌRK
Real interactions are seldom forced. They happen spontaneously, out of curiousity and without much planning. That is why
WŌRK graphically virtualizes the office space and the workers within it
and gives you the information you would have had on-premise. You see that Susan takes a coffee break, maybe you can join her. Martin is working on the Clifford deal, you could check in on how he's doing. Kim is on the phone, again, but it's good to see that sales are coming along.
WŌRK accompanies each team member and displays what they are doing at the moment. WŌRK offers to
connect with short and spontaneous voice or video calls
, without the need to schedule anything or pick an agenda.
WŌRK protects your privacy
, so that you can approximately know what is going on without feeling like you're spied on 24/7. And last but not least WŌRK gives you
the feeling of being part of a bustling team
, even when everyone is by themselves and far apart.
HOW DOES IT WŌRK?
Creating a virtual office is literally as simple as one click. You create an anonymous room and can then invite your team members, while the office space automatically expands as more members join. We are using
deep learning to automatically infer four different classes of activities
from your webcam feed:
working, telephony, eating and absence
. The different states are then reflected in the graphical virtual office to raise awareness within your team and help to create a natural feeling of community. Most importantly though, you do not have to worry about sharing your video stream continuously as
all your activities are represented by your virtual avatar
AUTOMAGICALLY
.
WŌRK establishes encrypted peer-to-peer connections between all team members to share the virtual office environment. No manual interactions are required, although they are possible. Instead
automatic recognition via audio and video
takes place to assess your current activity, which is then broadcasted to the rest of your team and displayed visually. We are using
on-device machine learning and a purely web-based solution
for activity recognition, so video data never leaves your device and no account or installation is necessary. Even video calls are transferred solely via end-to-end-encrypted peer-to-peer telephony -- preserving both your privacy and sensitive work-related information.
VISION
WŌRK can already help so much to make teams feel closer to one another but we feel that there is a lot more we can tackle. We want to help new team members get to know their colleagues better and feel included, or also support the sharing and managing of knowledge between workers in the office. Ultimately, we crave social bonds and for this reason we want to
build a platform that acts and feels just like the real thing
.
How We built WŌRK
WŌRK is completely web-based and relies on latest cutting-edge technologies and frameworks.
The client is an
Ionic-Angular web app
that connects to the other clients in a peer-to-peer fashion via
web sockets using the WebRTC standard
. While a server exists, implemented with
Azure Functions
, is only acts as a broker to help clients find one another via anonymous rooms ("virtual offices").
Each client can freely join and create rooms and change their identity as they please. Rooms however can only be joined if the invite code is known, which is distributed by the creator. Once clients join a room, they are notified of all current participants and establish
P2P connections
to each one of them. From no on, all interactions happen purely between participants without interaction with a third party.
The clients then start to analyze the behavior of their owner via the
TensorFlow framework for artifical intelligence
to analyze the video stream from the web or front camera. The models are evaluated solely on the client and results and then broadcasted to all active connections, which each then update their virtual office model. This model is represented in a 2D virtual office space implemented in the
HTML5 game framework Phaser
, where each participant is represented by an avatar that mimickes their activities continuously.
Similarly, voice and video calls can be requested and executed in an encrypted P2P fashion via the same connections.
Challenges We ran into
Combining the technologies
.
We focused on three major technologies that we didn't have too much experience with beforehand: activity recognition via machine learning, P2P communication via WebRTC and graphical depictions using a game engine. We split up the technologies between the three of us and spent the first half of the hackathon only working on our respective parts before we were first able to combine the technologies.
Balance between privacy and legitimate interest
.
At first glance our project can seem like a violation of privacy, as workers don't want to be watched 24/7. So we needed to decide on a balance that on one hand does not offer much more information that one would have in an office (like for example knowing that someone is in a call, but not with whom) but on the other side offer enough information that it is useful for the users.
Working as a hybrid team
.
It was the first time for all of us to participate in a hackathon as a hybrid team of on-premise and remote team members. We were connected to one another for probably 80% of the whole hackathon and learned a lot about what works and what doesn't when discussing aspects of the project or working by ourselves.
Accomplishments that We are proud of
We have a 100% working prototype. This first version is publicly hosted and could be demo'ed with everyone that wants to. That means that in the demos we show both in this project description and the accompanied video, no data or functionality is mocked and is instead created with real clients.
What's next for WŌRK
If you read up to this point, you must be really interested in the project. We appreciate you taking the time to look into what we have done. To stay up to date about WORK feel free to follow our social media channels
@TobiasRoeddiger
.
Built With
angular.js
azure
ionic
phaser.js
serverless
tensorflow
webrtc
Try it out
github.com | WŌRK | We're making remote teams feel close. It's the small interactions that make a workplace feel like a community and we help bringing your virtual company space to your home office. | ['Tobias Röddiger', 'Rudolf Biczok', 'Dominik Doerner'] | [] | ['angular.js', 'azure', 'ionic', 'phaser.js', 'serverless', 'tensorflow', 'webrtc'] | 53 |
10,526 | https://devpost.com/software/physiotherapy-aid | Inspiration
During Covid or in general working class specially IT professionals cant get time for exercise, sitting for long hours therefore they might get issues in body. So if we get them a virtual physiotherapist, so that sitting at home they can work out with proper guidance and do exercises will be beneficial.
What it does
Our application uses a tensorflow.js (browser-based) model to make predictions on the state of the current user's pose. It has been trained on a dataset of images created by us (~300 images per pose) to predict whether the position is correct, or incorrect - and what makes it so. I have used GCP Machine Learning Studio, a GCP Machine Learning tool, to train our models in the various physiotherapy poses. GCP Services Speech-to-Text API was also used to enable the application to be accessible by the visually impaired. The user can start their exercises via speech in various languages using GCPTranslator Speech API remotely and this is more convenient and easier to use for our target audience. The application utilizes GCP Services for text-to-speech. This is useful for the visually impaired as they can hear if they are in the right position as the application will tell them to adjust their posture if incorrect. We also use the webcam to track the user's movement which is fed as input to the posenet machine learning model and outputs posture image on the user's body.
How I built it
This is fully supported on Desktop/Android Google Chrome.
What's next for Physiotherapy Aid
Make it available for Gym enthusiasts
Built With
gcp
javascript
machine-learning
tensorflow
Try it out
github.com | Physiotherapy Aid | Your physio assistant. | ['Shivay Lamba'] | [] | ['gcp', 'javascript', 'machine-learning', 'tensorflow'] | 54 |
10,526 | https://devpost.com/software/migli | Loading Screen
Main Screen
The assistant is running
Search Results
ARView with Arrow Guide
Inspiration
Migli is the virtual Assistent for your next shopping trip to your local Migros. You don't find any item in the Store and there is no Staff Member around who you can ask? Just take your Smartphone out of your pocket and start Migli. He will guide you to the products you are serching and speed up your grocery shopping.
What it does
It is possible to sesrch by Speech-to-text or by using the keyboard. Over the Products API will be a search performed for Products by a Keyword, like
IceTea
. The Customer can then select the Product in a List and an AR View will be opened to guide the Customer trough the store, like it is well known in navigation devices in cars.
How we built it
After the Elevator pitch we gathered some Ideas what is possible. We looked the Challenge for something absolutely new to us and we think that we tackled it well. After this first phase we invested some time in researching and reading documentation from Apple and some blogs, then we started coding.
Challenges we ran into
We had some issues with JSON Parsing because of the inserting into structs. Also a big challenge was to show animated gif images to let Migli Speak. AR is very complicated and needs more reading and learning.
Accomplishments that we're proud of
That we can deliver a POC which can be used by Migros to make decisions on what is possible and what is wanted by everyday customers
What we learned
A lot about Swift and SwiftUI. How to build Userinterfaces for native iOS Programming. We made first steps into the world of AR, sadly we had to mock the Store. To locate a customer in Store there must be a Beacon Network. Paired with the In-Store Layout Migli can Guide Customers to the Products they are searching. It needs some time for Migros to install these beacons in a test store so we can try it "out in the wild".
What is further possible, some Ideas
Customer Feedback
Better planning of stores to prevent jams
Optimizing Store layouts
enhance the overall shopping experience
happy customers who will return to the store
Gamification for a sometimes boring task of groceries shopping
Repo Link:
https://github.com/rkreienbuehl/Migli
Built With
swift
swiftui | Migli | - the virtual grocery store assistent | ['Florian Thiévent', 'rkreienbuehl Kreienbühl'] | [] | ['swift', 'swiftui'] | 55 |
10,526 | https://devpost.com/software/garbage_collector | Map of Nigeria with points of interest for LafargeHolcim such as construction sites and cement factories.
Two routes for truck drivers to complete deliveries between construction sites and a cement factory.
The submission form for the public to report pickup locations for construction waste or plastic waste.
Closer look at the map.
Inspiration
Following the famous quote "One man's trash is another man's treasure.", we leverage the power of crowd-sourcing to bridge the gap between economic realities and sustainability goals.
We optimize already existing truck networks to transport waste materials on their empty load trips, leading to a more sustainable tomorrow.
What it does
We’re using crowd-sourcing in order to locate plastic waste (PW) as well as construction and demolition waste (CDW). Anyone can add a local waste spot to our web app by making an entry and providing details like amount, and optionally supply a picture.
We then optimize the routing of trucks delivering construction materials to traverse pick-up spots for the trash on their empty-load trips.
How we built it
We opted for a mapbox-based web app with React (javascript), utilizing Flask (Python) and Firebase as our backend.
To balance the profitability of transport (CO2) cost and sustainability (recycling) we came up with an inequality in order to decide if a truck should take a detour to pick up waste from the available pick-up spots.
Challenges we ran into
Solving the dynamic adding of new waste locations and making the routing for the trucks as time- and cost-efficient as possible was our biggest challenge.
Accomplishments that we're proud of
We managed to get a running prototype and deployed our web-app.
What we learned
Communication, Teamwork and how to distribute work in an efficient manner with a team of five people.
What's next for Garbage_Collector
Take over the trash of the world.
Built With
firebase
flask
javascript
mapbox
python
react
Try it out
github.com
github.com
hackzurich2020-frontend.vercel.app | Garbage_Collector | Following the famous quote "One man's trash is another man's treasure.", we leverage the power of crowd-sourcing to bridge the gap between economic realities and sustainability goals. | ['Robin Worreby', 'Felix Saaro', 'Martin Tschechne', 'Marcel Saaro', 'cmtsch'] | [] | ['firebase', 'flask', 'javascript', 'mapbox', 'python', 'react'] | 56 |
10,526 | https://devpost.com/software/m-sustain | Past Purchases
Purchase Articles
Product comparison
Goals
Goal tips
Inspiration
Sustainability is the main theme of
"#2 FOOD FOR THOUGHT"
by IBM & SwissRe and
"#18 STEP-BY-STEP: REDUCING CARBON FOOTPRINT"
by Zurich Insurance. We wanted to find a solution for individuals to help them reduce their CO2 footprint. The
"#1 LET'S CREATE DIGITAL PRODUCT TWINS"
challenge by Migros asked for solutions to help customers make better buying decisions. In order to stop climate change everyone has to adapt their own behaviors, so choosing a more sustainable product means choosing a better product.
We could not find any apps on the market that provide CO2 information of different products to the customer, so we decided to combine the product data from Migros with the CO2 data from the Eaternity.ai API. Our goal is to help the customers make better buying decisions every day.
What we have learned
When four people from different backgrounds start to work together there are lots of tools, languages and frameworks. No one knows everything and you do not know the others yet. Therefore it is important to communicate openly about any struggles or roadblocks, because someone else might have an idea to get out of there, even if they are using a different technology.
Challenges we had to overcome
Many but getting the required data took some huge team effort.
How we have build it
Data never comes in the way you would like to have it. The API was slow, because there were many people trying to get product data from Migros. We therefore downloaded the complete JSON file for all the products that we needed and parsed the files for all relevant data. Unfortunately the product categories were quite broad and there was no data field for alternative products so we had to find out how to match the products more specifically.
What is next for m-sustain?
We hope that Migros will be inspired by the idea to provide CO2 data for all of their products in their shopping app.
Built With
angular.js
docker
github
github-actions
google-cloud
https://eaternity.docs.apiary.io
https://hackzurich-api.migros.ch/products?
nest
nestjs
node.js
python
surge.sh
tailwind
Try it out
m-sustain.ch
github.com | M-sustain | The m-sustain app helps Migros customers to make more sustainable product decisions. It gives more sustainable product suggestions based on your recent purchases. | ['Pascal Bertschi', 'Yannick Müller', 'Susanne Brockmann', 'Fabio Poroli'] | [] | ['angular.js', 'docker', 'github', 'github-actions', 'google-cloud', 'https://eaternity.docs.apiary.io', 'https://hackzurich-api.migros.ch/products?', 'nest', 'nestjs', 'node.js', 'python', 'surge.sh', 'tailwind'] | 57 |
10,526 | https://devpost.com/software/steer-0rifbw | The Team> Dubious Robots
Inspiration
People go off topic during the meetings all the time. Your little story about two kitten in a basket easily wastes tens of working hours per meeting. This needs to end, Karen. We are claiming the time back!
What it does
Our app "Steer" is a game changer. It monitors your meetings, as soon as you start drifting off, you're gonna get a friendly nudge. It will keep track of your agenda and keep ticking off the covered topics.
But wait...there's more!
Steer also provides the complete meeting minutes for you, in an easily digestible format. It does this, so you don't have to!
How we built it
By conducting a thorough UX analysis with various stakeholders (as seen on the video).
We then selected the best technologies for the job, while constantly keeping the focus on the users.
Many sprints and running around were involved.
Challenges we ran into
Integration with some APIs were not actually possible to lift the heavy weight for us.
Accomplishments that we're proud of
We pulled it off, we managed to provide proof of concept that is valuable for the clients.
What we learned
How to do the video editing.
What's next for Steer
Sky is the limit!
Built With
java
javascript
node.js
python
Try it out
github.com | Steer | It continuously steers your online meetings back to the topic | ['hexagon6', 'Ivan Nesic', 'Tony K.', 'Meva Himmetoğlu', 'Tijana Wekker'] | [] | ['java', 'javascript', 'node.js', 'python'] | 58 |
10,526 | https://devpost.com/software/legal-anonymizer-ret-group | We look forward to taking this further with the sponsors of the Legaltech workshop!
The app recognizes context and does not just delete it but replace it by references to broader demographic categories. This makes the anonymized text compliant with anonymity requirements while still allowing the reader to understand and relate. This again increases user productivity.
The video demo has examples. For example broader geographic references are more useful than just redactions.
The app comes with an intuitive user interface and a case history, allowing the user to review all choices made by the app.
Herein lies also the differentiation to products currently on the market. This app will continue to learn.
The app will be open-sourced, and in return users will review anonymizations and rate or improve them.
Further work: understand context even further. The video shows an example of someone who bought then resold a car with distinctive mileage. This can ultimately also be an identifier, taken in context. The app will understand, improve an ultimately replace with broader references 'A car of more than 5 years with considerable mileage'.
Built With
natural-language-processing
python
Try it out
github.com | Legal Anonymizer RET Group | Legal Anonymizer App Saving Time and Providing Context | ['Tim Mondorf', 'Rahul Raj'] | [] | ['natural-language-processing', 'python'] | 59 |
10,526 | https://devpost.com/software/hack-the-crash-thales-solutions | Inspiration
Amazin challenge
What it does
Predict damage grade
How I built it
Python
Challenges I ran into
Numerous ways to solve this kind of problems
Accomplishments that I'm proud of
Finished in time
What I learned
Time management
What's next for Hack the Crash - Thales Solutions
Sleep
Team Name
Thales Solutions
Built With
excel
powerpoint
python | ThalesSolutions | ThalesSolutions | ['Philippe Schlattner', 'boss records'] | [] | ['excel', 'powerpoint', 'python'] | 60 |
10,526 | https://devpost.com/software/hack-the-crash | TEAM NAME ON CODALAB: MLPHANTS
Inspiration
Hi, we are MLPhants team! Thomas and I, Martina took up the challenge ‘Hack the Crash’ proposed by the QuantumBlack Team. We do not only love machine learning but we also love helping people out! We want to present our idea of solving this problem by embedding categorical variables into probabilistic distributions.
What it does
Our solution solves the problem presented to us by QuantumBlack team so classification of damage grades assigned to various buildings and areas. We used the idea of embedding each such feature as a low-dimensional vector.
How we built it
We created our model considering all examples in the dataset for which features have constant value and by looking at what percent of them falls into each damage level. This gave us representation telling that for example if a building is made of bamboo it has 15% chance to have damage 2 level after earthquake. Each such embedding is a very weak classification but we have many of them, so we could build strong classifiers from many weak ones. To do so we first performed principal component analysis to construct for us 75 new numerical features that explain 99.9% of variance. The rest of the work was done by gradient boosting algorithm that learns the effective classification. This embedding is very fast and consumes little computational power.
Challenges we ran into
Our main challenge was to properly understand the nuisances and links between data in the dataset given to us. Another challenge was selecting best ML techniques (and sometimes the choice is not as obvious as it seems!)
Accomplishments that we're proud of
We achieved very high score of our model (and several model iterations) and we were able to improve it several times in row.
What we learned
We learned a lot about ensembling models, data analysis, the importance of using PCA to understand the distribution of the data.
What's next for Hack The Crash
Obviously, our model by itself is not going be a self-sufficient solution to the given problem, but it surely has a lot of applications. Our model could investigate data points for which the classification was very wrong and spot which buildings seem to be safe, but in fact are not, and check if they share common features. This could help to discover some new weaknesses and improve possible building constructions in the future. This model could also be combined with a mobile app that has access to geo-spatial data and could warn a user of being in or near a building with high risk of damage in an earthquake (the alert would be for example triggered by the seismological data). The app could also show the user what are the safest buildings or areas within walking distance when the user could take cover. Other useful feature for such application would be a notification of current user’s location triggered by seismic shock which could potentially be helpful in case of a rescure operation. Additionally, our model could help insurance companies evaluate the risk of damaging buildings or properties based on their location, on the quality of adjacent buildings.
Built With
ensembling
feature-engineering
feature-selection
jupyter
machine-learning
numpy
pandas
pca
python
scikit-learn
xgboost
Try it out
github.com | HACK THE CRASH - categorical to probabilistic distribution | A machine learning solution to the problem of classifying damage grades of buildings using categorical to probabilistic distributions. | ['Martyna Wiącek', 'Tomasz Odrzygóźdź'] | [] | ['ensembling', 'feature-engineering', 'feature-selection', 'jupyter', 'machine-learning', 'numpy', 'pandas', 'pca', 'python', 'scikit-learn', 'xgboost'] | 61 |
10,526 | https://devpost.com/software/mrshopper | Real world view with 3D grid for profile elements
HoloLens view for profile inside Unity playground
HoloLens view for products inside Unity playground
HoloLens view for recipes inside Unity playground
Real world view with 3D grid for nutrition and ingredient information
Real world view with 3D grid for recipe selection
Inspiration
These are peculiar times. The world is plagued by the coronavirus pandemic and there is a huge uptick in the demand for remote activities. While this sounds uber comfortable, it can also be detrimental to one's social, physical and mental health. One also has to consider the fact that more often than not, walking to the grocery store is often a person's only "fitness" incentive during the day. Take this away and we aren't left with a lot of activities to keep up our physical fitness. Keeping this in mind, we want to present an end to end solution that marries something as banal as grocery shopping with fitness challenges and nurtures users towards healthy and more responsible choices.
When you think of online shopping, what is the first thing that comes to your mind? Let me take a guess. You are probably imagining a person endlessly through products, perusing, questioning life decisions, asking themselves what they are doing with their lives. Wondering how life might have been if I had said "Yes" to that 1 month South America travel escapade my friend had invited me to in February before the travel bans. Err...I digress. You get the gist. Online shopping is comfortable, very very comfortable, but it isn't necessarily a lot of fun. And then you have online grocery shopping, which in my opinion, is one of the most tedious things to do. Scrolling through a plethora of products without any structure or meaning does not appeal to me. Tell me, what sends your stomach into a frenzy? Looking at onions, garlic and chicken or a picture of freshly cooked butter chicken curry?
Good looking food usually comes with a lot of fitness caveats. And then there is your diet plan. You really want to eat that butter chicken but how exactly do you fit it in your plan? What about your allergies? Can you still eat it on a Keto diet? These are some of the problems we aim to tackle with our solution. Great, the food is sorted but what about exercising now? Based on a study by
Barte
and several others, we know that there is a strong relationship between exercising and incentives. But how can one be incentivised to exercise during online grocery shopping? This is where we took the concept of "Adding to Cart" quite literally. If Pokemon Go was any indication, most people don't mind doing physical tasks to gain rewards, financial or not. Similarly, using the power of Mixed Reality devices such as HoloLens, a user can be incentvised to perform fitness tasks within the confines of their home to gain rewards such as discount vouchers and bonus coupons while accomplishing the goal of shopping conveniently and safely.
What it does
Reimagines online shopping by
harnessing mixed reality
Integrates fitness training with shopping and gamifies the experience of monotonous buying
Remote shopping and exercising, keeping you safe from the clutches of Coronavirus!
Enables you to
search and retrieve recipes using images
of the delicious food images you see in the web with Computer Vision algorithms.
Empowers you to
shop based on what you want to eat
instead of forcing you to think what to eat based on what you have shopped.
Aids in
making better food choices
for your health and also the environment
Personalised recommendation
of products based on your dietary preferences and allergies
Connects to your fitness devices
and leverages this data to improve your nutrition choices
Rewards you
for better choices
How I built it
We used Microsoft's HoloLens 2 as our choice of platform to present our solution.
For the datalake, we used data from vendors such as Migros, Eaternity. byte.ai, Eatfit and OpenFoodFacts.
We used Azure to deploy our backend
Challenges I ran into
The major challenges came in the form of leveraging the humongous amounts of information at our disposal through a multitude of APIs and filtering them to use the most relevant data points. This often lead to slowdowns and demanded novel ways of optimising data retrieval techniques. Another major hurdle was to build 3D elements for the HoloLens and render it in a user-friendly manner. Surprisingly, the most obvious challenge of collaborating within ourselves (since one of us was working remotely) didn't turn out to be as difficult as one would imagine. Hurrah to the wonders of modern technology!
Accomplishments that I'm proud of
Implementing most of the features we had planned
Merging APIs from several vendors to produce a unified datalake
Deploying the backend as a container to Azure
Finishing the project and having a product!
What I learned
I learnt how to build interactive applications for HoloLens and how to leverage cutting edge technologies as viable solutions to daily life problems.
What's next for mrshopper
We would like to augment the fitness games with different tasks and optimise the UX and responsiveness of our application.
Built With
azure
bite.ai
c#
docker
dockerfile
eaternity
eatfit
migros
mrtk
openfoodfacts
python
unity
Try it out
github.com
github.com | mrshopper | Our idea is to redefine shopping and fitness in a world plagued by coronavirus, obesity and environmental crisis by leveraging the power of data with disruptive technologies such as ML and HoloLens. | ['Eric Vollenweider', 'Rishu Agrawal'] | [] | ['azure', 'bite.ai', 'c#', 'docker', 'dockerfile', 'eaternity', 'eatfit', 'migros', 'mrtk', 'openfoodfacts', 'python', 'unity'] | 62 |
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