Constantly faced with a multitude of options whenever going out to eat, our team was determined that there had to be a better way to decide what food to eat based on a variety of inputs. After playing around with a few ideas, we settled in our current idea which optimizes food based on both health and money, 2 factors important important to nearly everyone.
How it works
The user first enters the name of a restaurant close to the user's current location. After that the user enters the maximum amount of money he or she wishes to spend. Then the user selects the amount of calories desired, high, medium, or low. Once all of the inputs have been specified our algorithm runs which sorts all of the food items from the specified place based on the calories desired and the money specified. Our algorithm assigns each food item with a "Nutritional Score" that takes into account many nutritional facts and the user inputs. The suggested food items sorted by the Nutritional Score are displayed in a chart as well as a table.
Challenges I ran into
One challenge we had was incorporating a first time hacker into our team. However, by taking the time to show him what we had learned from previous hackathon projects, we both learned a great deal. Another challenge we faced was just fixing a lot of the bugs that started popping up. A lot of these bugs took a while to debug, but we were able to fix all of them by seeking help.
Accomplishments that I'm proud of
We're proud of finishing our app and having everyone contribute and learn while working on our hack. The user interface and our algorithm for sorting the food items in particular are parts of the hack that we spent a great deal of time on and are happy with the way they came out.
What I learned
We learned a lot about web development since at most prior hackathons we had been creating mobile applications rather than web apps. We also were using Github a lot more effectively at this hackathon and thus were able to have everyone contribute more to the app.
What's next for Food4Less
We hope to next incorporate a social aspect to our app allowing users to share what they're eating. We're satisfied with our UI and algorithm, but we think we could also incorporate a few other charts to display additional data.