The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 11, 2020

Filed:

Mar. 10, 2016
Applicant:

Tata Consultancy Services Limited, Mumbai, IN;

Inventors:

Bhushan Gurmukhdas Jagyasi, Thane, IN;

Jayantrao Mohite, Thane, IN;

Srinivasu Pappula, Hyderabad, IN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A01G 22/00 (2018.01); G06Q 50/02 (2012.01); G06Q 10/04 (2012.01); G06Q 10/06 (2012.01); A01C 14/00 (2006.01); A01M 17/00 (2006.01); A01M 99/00 (2006.01); G01W 1/00 (2006.01);
U.S. Cl.
CPC ...
A01G 22/00 (2018.02); A01C 14/00 (2013.01); A01M 17/00 (2013.01); A01M 99/00 (2013.01); G01W 1/00 (2013.01); G06Q 10/04 (2013.01); G06Q 10/067 (2013.01); G06Q 50/02 (2013.01);
Abstract

Presence of natural enemies has a considerable impact on pest severity in a given geo-location. However, manually estimating pest severity or population of natural enemies is cumbersome, inaccurate and not scalable. Systems and methods of the present disclosure enable estimating effective pest severity index by receiving a first set of inputs pertaining to weather associated with a geo-location under consideration; receiving a second set of inputs pertaining to agronomic information; generating a pest forecasting model and a natural enemies forecasting model based on the received first set and the second set of inputs for each pest; and estimating the effective pest severity index based on the generated models. The timing and quantity of pesticide application can be optimized based on the estimated pest severity index. The generated models can be further enhanced continually based on one or more of historical data, participatory sensing inputs, crowdsourcing inputs and management practices.


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