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Healthy restaurant (healthy choice)

Background and Motivation: 

In recent years the effects of industrial growth have resulted in drastic changes in consuming behavior, standard of living, and lifestyles. In particular there has been a significant rise in the number of people who eat out regularly. This often means that they cannot control the characteristics of the food they take, such as its taste, calories per portion, and other nutritional details. As a result they may become prone to obesity. Today people are confronted with more difficult decisions about how to select food items suitable to their nutritional needs. 

Project Summary: 

Healthy menu application is a new counseling system for food consumption. Application not only assist for choosing right food by entering parameters such as gender, age, height, weight, exercise activity and favorite food but also provides food recommendation to each individual nutritional profile.
Application consist of two parts – mobile application and web part with nutritional database of 8000 products. Using mobile application client has opportunity to keep food and exercise diary , and to receive recommendation for food consuming. Also mobile application can scan qr-codes for extraction nutrition parameters. Web part is enterprise application which provides API for food and activity searching. Also web part has web interface which provides opportunity to work with database.

List of team members and their organizations: 

Developer: Karasavov A.

Supervisor: Krinkin K.

Project Timeline and Expected Deliverables: 
  • January -February 2014 – learn mobile development
  • February 2014 – Initial plan. Requirements specification.
  • March 2014 – Api model and programming model.
  • April 2014 – Implement simple prototype of mobile and web part.
  • May 2014 – Talk at FRUCT15(
  • September 2014 – December 2014 – add nutrition database, implement web part API, implement food and exercise diary
  • January 2015 – April 2015 – research classification algorithms, create math model, implement recommendation algorithm, test algorithm
  • Feb 2015 – paper for FRUCT 17
Final deadline: 
Tuesday, June 30, 2015 - 12:15