To most of us, the most essential thing is have a nutritional and budget friendly diet. Our aim was to provide customer an intelligent recommendation system that gives him the flexibility of leading the healthy lifestyle without having to invest his time and money. Our approach is backed up by highly scientific dataset obtained from U.S Department of Agriculture and product libraries of Wegmans Food Market Inc.

What it does

The application intelligently calculate user's nutrient requirement based on their characteristics such as age, sex, height, weight, physical activities, and inspiration to stay healthy. These data forms the basis of presenting their calorie composition which is further analyzed to recommend their dietary plans. The recommendations can vary depending on their choice of dietary plans.

How we built it

The front end of the application is build using android and the back-end using nodejs. The application is hybrid in nature with considerable part of it being developed using web - view toolkit and angular js.

Challenges we ran into

While we were accessing dataset (USDA and Wegmans), there often were instances of where rate limit got exceeded. There were some challenges in interaction between different stages of the project. In backend engineering we faced most crucial challenge of data collection for different food products and using this data to match with Wegmans database using different combination of APIs to provide user a list of products that fits his requirements for diet and budget.

Accomplishments that we're proud of

Making most of USDA food dataset and Wegmans APIs to provide user a list of products that can be bought from Wegmans market which would be very closely in coherence with customer’s fitness goals and at the same time within his budget. In the end, synchronizing every phase and making a successful system is one of our biggest achievements.

What we learned

We learned to effectively leverage open source APIs of commercial markets for mutual benefit of both customer and seller. We learned the importance of a team-effort which can result into a creation of great projects in less time.

What's next for MyFabDiet

The project can be extended to include multiple food market stores and give the most optimized recommendations to the users. We can use the Velocity component of the products to do some useful analysis on the products and consumer habits which would be very useful for comany's profit and growth.

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