Food is capable of uniting all of us together, no matter which demographic we belong to or which cultures we identify with. Our team recognized that there was a problem with how challenging it can be for groups to choose a restaurant that accommodated everyone's preferences. Furthermore, food apps like Yelp and Zomato can often cause 'analysis paralysis' as there are too many options to choose from. Because of this, we wanted to build a platform to facilitate the process of coming together for food, and make the process as simple and convenient as possible.

What it does

Bonfire is an intelligent food app that takes into account the food preferences of multiple users and provides a fast, reliable, and convenient recommendation based on the aggregate inputs of the group. To remove any friction while decision-making, Bonfire is even able to make a reservation on behalf of the group using Google's Dialogflow.

How we built it

We used Android Studio to build the mobile application and connected it to a Python back-end. We used Zomato's API for locating restaurants and data collection, and Google Sheets API and Google Apps scripts to decide the optimal restaurant recommendation given the user's preferences. We then used Adobe XD to create detailed wireframes to visualize the app's UI/UX.

Challenges we ran into

We found that Integrating all the API's into our app was quite challenging as some required Partner access privileges and restricted the amount of information we could request. In addition, choosing a framework to connect the back-end was a difficult.

Accomplishments that we're proud of

As our team is comprised of students studying bioinformatics, statistics, and kinesiology, we are extremely proud to have been able to bring an idea to fruition, and we are excited to continue working on this project as we think it has promising applications.

What we learned

We learned that trying to build a full-stack application in 24 hours is no easy task. We managed to build a functional prototype and a wireframe to visualize what the UI/UX experience should be like.

What's next for Bonfire: the Intelligent Food App

For the future of Bonfire, we are aiming to include options for dietary restrictions and incorporating Google Duplex into our app for a more natural-sounding linguistic profile. Furthermore, we want to further polish the UI to enhance the user experience. To improve the quality of the recommendations, we plan to implement machine learning for the decision-making process, which will also take into account the user's past food preferences and restaurant reviews.

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