Munch is an intelligent nutrition tracker that analyses your diet, and gives food suggestions based on micro and macronutrient deficiencies. It utilises the USDA’s food composition database of over 8,000 food items and tracks 40 different properties about the foods you eat. Your historical nutrition information is checked against the USDA’s “Dietary Reference Intakes” for both “Acceptable Macronutrient Distribution Range” and “Recommended Daily Intake.” This information is then used in order to determine your best course of action and inform you about how to improve your diet.
The application also integrates image tracking in order to provide a more personal feel. With the current trends in social media, moving beyond just text to images is extremely powerful. A visual heatmap of how many calories were eaten each day allows for the identification of long term trends.
Munch is unique in tracking a vast number of nutrient types, and competitors don't suggest foods that would fit perfectly in your diet.
On the frontend, the client uses modern design paradigms and libraries to give the user a consistent interface. It was developed for the Android operating system in Java. This allows it to run on most mobile phones, and it can run on laptops with Google Chrome. The application interfaces with the API and allows the user to access different ways of viewing their nutritional info. It takes full advantage of the Android platform to edit and share photos taken with the camera.
The client is open source! Check it out on GitHub! https://github.com/chrisfrederickson/munch
This project was developed for the 2015 IEEEmadC: http://ieeemadc.org/ and it won the best design award!