SYSTEM AND METHOD FOR A PERSONAL DIET MANAGEMENT

• US 20140080102A1
• Filed: 05/11/2012
• Published: 03/20/2014
• Est. Priority Date: 05/13/2011
• Status: Abandoned Application

• Current Assignee: Srikanth Krishna
• Original Assignee: Srikanth Krishna
• Inventors: Krishna, Srikanth
• Application Number:
  US14/116,760
• Publication Number:
  US 20140080102A1
• Time in Patent Office: Days
• US Class Current: 434/127
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G09B 19/0092 Nutrition

Abstract

A system and method for enabling a personal diet management service is disclosed. The system enables users to communicate with the system and receive recommendations throughout the day. The system recommends recipes and restaurants serving the recipes based on a plurality of factors comprising of the calorie and nutrient intake of the person for each meal, identified deficiencies based on the recommended daily intake among others. The system also allows user to communicate with restaurants for reserving tables and specifying any further requests.

Claims

1. A method for making real time recommendations related to diet of a user by a decision engine, based on a plurality of factors comprising of at least one of

calorie consumption of said user;

nutritional requirements of said user;

preferences of said user; and

consumption pattern of said user.

2. The method, as claimed in claim 1, wherein said decision engine estimates said calorie consumption on a daily basis.

3. The method, as claimed in claim 1, wherein said decision engine estimates said calorie consumption on basis of a plurality of days.

4. The method, as claimed in claim 1, wherein said decision engine estimates said nutritional requirements on a daily basis.

5. The method, as claimed in claim 1, wherein said decision engine estimates said nutritional requirements on basis of a plurality of days.

6. The method, as claimed in claim 1, wherein said decision engine furthers considers factors comprising of type of meal, physiological information of said user, medical history of said user, location of said user, current weather in location of said user, religious preferences of said user, cost of food, purchasing power of said user, taste preferences of said user, food availability at location of said user, seasonal food preferences of said user, a wide variety of food, locally grown food choices, organically or hormone free food sources and current season.

7. The method, as claimed in claim 1, wherein said method further comprises of said user approving said recommendations.

8. The method, as claimed in claim 1, wherein said recommendations may be in the form of at least one of meals;

recipes, ingredients for preparing said meals, restaurants for availing said recommended meals.

9. The method, as claimed in claim 8, wherein said method further comprises of offering at least one retail location for obtaining said ingredients based on cost factor to said user.

10. The method, as claimed in claim 9, wherein said method further comprises of offering at least one of coupons;

or promotional materials related to said retail location.

11. The method, as claimed in claim 1, wherein said decision engine uses at least one linear programming model for making said recommendations.

12. The method, as claimed in claim 1, wherein said method further comprises of

assigning a score to said recommendations by said decision engine;

and

ranking said recommendations by said decision engine on basis of said assigned scores.

13. A system for making real time recommendations related to diet of a user, said system configured for considering a plurality of factors comprising of at least one of

calorie consumption of said user;

nutritional requirements of said user;

preferences of said user; and

consumption pattern of said user.

14. The system, as claimed in claim 13, wherein said system is further configured for estimating said calorie consumption on a daily basis.

15. The system, as claimed in claim 13, wherein said system is further configured for estimating said calorie consumption on basis of a plurality of days.

16. The system, as claimed in claim 13, wherein said system is further configured for estimating said nutritional requirements on a daily basis.

17. The system, as claimed in claim 13, wherein said system is further configured for estimating said nutritional requirements on basis of a plurality of days.

18. The system, as claimed in claim 13, wherein said system is further configured for furthers considering factors comprising of type of meal, physiological information of said user, medical history of said user, location of said user, current weather in location of said user, religious preferences of said user, cost of food, purchasing power of said user, taste preferences of said user, food availability at location of said user, seasonal food preferences of said user, a wide variety of food, locally grown food choices, organically or hormone free food sources and current season.

19. The system, as claimed in claim 13, wherein said system is further configured for taking approval from said user for said recommendations.

20. The system, as claimed in claim 13, wherein said system is further configured for making said recommendations in the form of at least one of meals;

recipes, ingredients for preparing said meals, restaurants for availing said recommended meals.

21. The system, as claimed in claim 19, wherein said system is further configured for offering at least one retail location for obtaining said ingredients based on cost factor to said user.

22. The system, as claimed in claim 21, wherein said system is further configured for offering at least one of coupons;

or promotional materials related to said retail location.

23. The system, as claimed in claim 13, wherein said system is further configured for using at least one linear programming model for making said recommendations.

24. The system, as claimed in claim 13, wherein said system is further configured for

assigning a score to said recommendations;

and

ranking said recommendations on basis of said assigned scores.