Foodie – A Nutritional Recommendation Web Application
The aim of this project is to create an application that will provide a healthier lifestyle for its users. Given an array of food items by the user, Foodie will aim to identify nutritional aspects missing or dominating in the meal such as protein or sugar. By analyzing the nutritional values of a meal and how it contrasts to that of recommended daily intake amounts, foods can be recommended to the user containing these nutritional elements that will enhance the diet of the user.
Currently, there is an explosion in the popularity in healthy eating and nutrition. Foodie is a web application developed using MEAN stack which is a full stack development framework of AngularJS, MongoDB, Node.js and Express. It functions as a nutritional service where users can log their diet, food or meals they’ve consumed and the application will provide nutritional results and recommendations for that user based on the analysis and collation of the data that has been produced. Users can log a meal by selecting from a large array of food items from various categories of foods. Each food item has their nutritional values attached to them in the database. All selections are added and stored in an array until the foods are submitted. When the process of logging a meal is completed, the meal is submitted and the analysis has been performed on the meal, results will be displayed graphically and structured in order of the results of individual nutritional values. For example, if too much of a specific nutritional value is present in a meal such as protein, the application will identify items high in protein that the user logged and recommend a food to be removed and vice versa for nutritional values that are lacking in the diet. Recommender Algorithms are used to determine the correct foods to be displayed to the user in the results.