Soft Computing Techniques Based Diet Recommendation System

Abstract

Many factors influence an individual’s health, such as physical exercise, sleep, nutrition, heredity and pollution. Being nutrition one of the major modifiable factors in our lives, small changes can have a big impact. Due to diversity in food components and large number of dietary sources, it is challenging to perform real-time selection of diet patterns that must fulfill one’s nutrition needs. In this project we have implemented a recommender system that helps the user track their calorie goals based on their Body Mass Index and also provide food recommendations based on the user’s history and preferences. The user will enter their BMI details and their dietary preferences and allergies and will be recommended a certain daily calorie goal. Using the concepts of Fuzzy Logic and Collaborative Filtering for building a recommender system, we help the users by providing food suggestions based on their personal preferences. The Android based application also features a Step Counter or Pedometer for the users to track their steps as part of an activity or exercise.