Nutrify

Nutrify your wasted food and help protect the environment

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Inspiration

Every year thousands of pounds of food is wasted by families simply because they don't use it/can't cook anything good with it. Food waste is a one of the main factors of global warming and needs to be addressed. The US in total produces about 80 billion pounds of food waste each year. As a result, all the food that is rotting in food piles releases CO2 and Methane into the atmosphere which are the leading causes of global warming. In fact, food waste primarily consist of meat, grains, and fruits, and meats produce a incredible amount of methane which is 21 time more harmful to the atmosphere than CO2. Plus, millions of dollars are wasted because of food waste. Our solution to this problem was to create a app that allows users to scan items, see personalized recipes, and helps them see the impacts they made.

What it does

Nutrify allows users to scan all their food items. This is done from a ml model that can detect food images. After that, the user can go back tot he home page and click generate recipes, this will show the top listed recipes that includes all the food items the user has. This allows the user to make a savory dish and use the food items they were going to throw away. The user then can go back to the ingredients page and select which food items they used and which they didn't. Finally, the user goes to the user page and they can see their analytics . This includes how much food they saved and CO2 emissions. Based on the CO2 emissions saved the user can go to the augmented reality feature and see how many trees save that much CO2 and compare to see how big of a impact they made and how the corresponding the users carbon score/ingredients consumed.

How we built it

We built this app using swift and created a iOS app. We used Google Clouds to save the user credentials and food Items of the user, First, we used some machine learning (Google Vision API) to scan the food items and output the names of the items. Then we built 2 API's and integrated them together. One scraped the web by querying the food item names, then getting the top result. The second API, scarped that URL/web page and outputted the ingredient, servings, instructions, and title. The rest of our app was built using swift logic and integrating the AIP request calls to make a fully functioning app. We also used Apple's Realty Composer to create AR scenes and integrating it with the user analytics

Challenges we ran into

Their were many hard things that we encountered during this project. First, creating the API and making them work together was very difficult since they called and requested different attributes. However, through much testing we were able to get the results we wanted. Another challenge that we ran into was calling the requests from the iOS app itself since we wanted to display it on out phone. Through many third party library (Alamo Fire) we were able to connect it with he app. Throughout the app, another main challenge was really flowing all the elements though and providing the correct information on each page of the app. But though many errors and testing we were able to get it done!

Accomplishments that we're proud of

This was our first time integrating external API's with swift code. It was really challenging but it was a good learning experience and we were able to make it work. Another thing was implementing the AR with the app since we needed all the user data and show the correct sprites in augmented reality. This was really challenging but the end result was really cool.

What I learned

We learned a lot in the hackathon! This was our first time creating a complex iOS application and linking it to external API's. Python web scarping was something new for use and it worked out well as we learned how scarping actually works. One of the main things we learned was connecting our app with the external API's we made, which was really challenging as we weren't sure how to actually receive the data. But we learned by analyzing the data structure's and extracting the information. In all we were able to connect all these different features and create a fully functionally iOS app.

What's next for Nutrify

We hope that Nutriy will be released on the app store for thousands of people to use. We would like to add more features, and create more rewarding experiences for the user like sending plants to them for saving x amount of food, etc. These steps would create a much more regarding experience to the user and also save the experience.

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