## Inspiration

*It's lunchtime. You quickly grab a bite to eat and sit by yourself while you munch it down alone. While food clearly has the power to bring people together, the pandemic has separated us from friends and family with whom we love to eat together with*

Muk means Eat in in Korean 🍽️ Eating is such an essential and frequent part of our daily lives, but eating alone has become the "norm" nowadays. With the addition of the lockdown and working from home, it is even harder to be social over food. Even worse, some young people are too busy to eat at home at all.

This brings significant health drawbacks, including chances to lead to obesity, higher risk factors for prediabetes, risk of having metabolic syndrome, high blood pressure, and higher cholesterol. This is because loneliness and lack of social support lead to physical wear and anxiety 🤒

We rely on relationships for emotional support and stress management ✨🧑‍🤝‍🧑 This is why we became inspired to make eating social again. With LetsMuk, we bring available the interactions of catching up with friends or meeting someone new, so that you won't spend your next meal alone anymore.

This project targets the health challenge because of the profound problems related to loneliness and mental health. With young people working from home, it brings back the social-ness of lunching with coworkers. Among seniors, it levitates them from isolation during a lonely meal. For friends over a distance, it provides them a chance to re-connect and catch up. 💬🥂 Here are multiple health studies that highlight the health problems around eating alone that inspired us

* [eating-alone-metabolic-syndrome](https://time.com/4995466/eating-alone-metabolic-syndrome/)
* [eating-alone-good-or-bad-for-your-health](https://globalnews.ca/news/6123020/eating-alone-good-or-bad-for-your-health/#:%7E:text=The%20physical%20implicati%5B%E2%80%A6%5D0and%20elevated%20blood%20pressure)
* [eating-alone-is-the-norm](https://ryersonian.ca/eating-alone-is-the-norm-but-ryerson-grads-app-works/)

## How we built it

We chose Flutter as our mobile framework to support iOS and Android and leveraged its tight integrations with Google Firebase. We used Firebase's real-time database as our user store and built a Ruby on Rails API with PostgreSQL to serve as a broker and source of truth. Our API takes care of two workflows: storing and querying schedules, and communication with Agora's video chat API to query the active channels and the users within them.

Here is the video demo of when one joins a room [YouTube Demo on entering a room](https://youtu.be/3EYfO5VVVHU)

## Challenges we ran into

This is the first time any of us has worked with Flutter, and none of us had in-depth mobile development experience. We went through initial hurdles simply setting up the mobile environment as well as getting the Flutter app running. Dart is a new language to us, so we took the time to learn it from scratch and met challenges with calling async functions, building the UI scaffold, and connecting our backend APIs to it. We also ran into issues calling the Agora API for our video-chat, as our users' uid did not cohere with the API's int size restriction.

## Accomplishments that we're proud of

It works!!

* Building out a polished UI
* Seeing your friends who are eating right now
* Ease of starting a meal and joining a room
* "Mukking" together with our team!

## What we learned

* Mobile development with Flutter and Dart
* User authentication with Firebase
* Video call application with Agora
* API development with Ruby on Rails
* Firebase and Postgres databases (NoSQL and SQL)

## What's next for LetsMuk

* Schedule integration - put in when you eat every day
* Notifications - reminders to your friends and followers when you're eating.
* LetsMuk for teams/enterprise - eat with coworkers or students
* Better social integration - FB, twitter, "followers"
## Inspiration

Using “nutrition” as a keyword in the Otsuka valuenex visualization tool, we found that there is a cluster of companies creating personalized nutrition and fitness plans. But when we used the “and” function to try to find intersections with mental wellness, we found that none of those companies that offer a personalized plan really focused on either stress or mental health. This inspired us to create a service where we use a data-driven, personalized, nutritional approach to reduce stress.

## What it does

We offer healthy recipe recommendations that are likely to reduce stress. We do this by looking at how the nutrients in the users’ past diets contributed to changes in stress. We combine this with their personal information to generate a model of which nutrients are likely to improve their mental wellness and recommend recipes that contain those nutrients. Most people do want to eat healthier, but they don’t because it is inconvenient and perceived to be less delicious. Our service makes it easy and convenient to eat delicious healthy food by making the recipe selection and ingredient collection processes simpler.

To personally tailor each user's recipe suggestions to their stress history, we have users save food items to their food log and fill out a daily questionnaire with common stress indicators. We then use the USDA food database to view the specific nutrients each food item has and use this data to calculate the relationship between the user's stress and the specific nutrients they consumed. Finally, we use this model to suggest future recipes that contain nutrients likely to reduce stress for that user.

In order to proactively reduce user's stress, we offer a simple interface to plan meals in advance for your entire week, an auto-generated ingredients list based on selected recipes for the week, and a seamless way to order and pay for the ingredients using the Checkbook API service. To make it easier for users, the food log will automatically populate each day with the ingredients from the recipes the user selected to eat for that day.

## How we built it

We used Bubble to build a no-code front end by dragging and dropping the design elements we needed. We used Bubble's USDA plugin to let users search for and enter foods that they consumed. The USDA food database is also used to determine the nutrients present in each of the foods the user reports consuming. We also used Bubble's Toolbox plugin to write Javascript code that allows us to run the Checkbook API. We use the Spoonacular API to get the recipe suggestions based on the user's personalized preference quiz answers where they give the types of cuisines they like and their dietary restrictions. We use a linear regression model to suggest future recipes for users based on the nutrients that are likely to reduce their stress.

## Challenges we ran into

One challenge for us was using Bubble. Only one team member had previous design experience, but everyone on the team wanted to contribute to building the front-end, so we faced a huge learning curve for all members of the team to learn about good design principles and how to space elements out on Bubble. Grouping elements together was sometimes weird on Bubble and caused issues with parts of our header not lining up the way we wanted it to. Elements would sometimes disappear under other elements and it would become hard to get them out. Formatting was weird because our laptops had different aspect ratios, so what looked good on one person's laptop looked bad on another person's laptop. We were debugging Bubble until the end of the hackathon.

## Accomplishments that we're proud of

Our team had little to no front-end design experience coming into this hackathon. We are proud of how much we all learned about front-end design through Bubble. We feel that moving forward, we can create better front-end designs for our future projects.

We are also proud of finding and figuring out how to use the Spoonacular API to get recipe recommendations. This API had very thorough documentation, so it was relatively easy to pick it up and figure out how to implement it.

## What we learned

The first thing we learned was how to use the Otsuka valuenex visualization tool for ideation. We found this tool to be extremely helpful with our brainstorming process and when coming up with our idea.

We learned how to use Bubble to create a front-end without needing to write code. Despite the struggles we initially faced, we grew to find Bubble more intuitive and fun to use with more practice and managed to create a pretty nice front-end for our service. We hosted our server on Bubble.

We also learned how to use the Checkbook API to seamlessly send and receive payments.

Finally, we learned how to use the Spoonacular API to generate recipe recommendations based on a set of parameters that includes preferred types of cuisines, dietary restrictions, and nutrients present in each dish.

## What's next for mood food

We feel very passionate about exploring this project in more depth by applying more complex machine learning models to determine better recipe recommendations for users. We would also like to have the opportunity to deploy this service to collect real data to analyze.

## Thanks

Thank you very much to Koji Yamada from Otsuka for meeting up with our team to discuss our idea and offer us feedback. We are very grateful to you for offering our team support in this form.

Thank you to the amazing TreeHacks organizers for putting together this awesome event. Everyone on our team learned a lot and had fun.
## Inspiration

We felt that 3D viewing and manipulation software had been giving us quite the headache. It all came down to how un-intuitive the navigation was. As such, we built Myosis, an for an unconventional way to view 3D objects.

## What it does

Uses arm gesture recognition technology, gyroscopic motion, acceleration and orientation to view and navigate STL files.

## How we built it

Blood, sweat, and tears... Lots and lots of tears (and Soylent

## Challenges we ran into

We had quite a big problem setting up the Myo armband, especially when it had difficulties in gyroscopic readings. Learning 3D rendering techniques from scratch was also quite challenge. Creating a smooth and simple UI from processed values was difficult as well.

## Accomplishments that we're proud of

We're proud that we've built such a responsive web app, despite communication difficulties we faced between the Myo and browser.

## What we learned

As we were all pretty well versed in hardware, we faced quite a big learning curve, given all the new modules we had to implement. It was tough but worth it.

## What's next for 3D Myosis

Better zoom, pan, and gesture based controls. We also hope to implement 3d notes/drawing tools, as well as the ability to mold/edit a 3d file with two armbands. If given more time, we would definitely peruse implementation with AR controls with the hand.