Systems and methods for estimating effective pest severity index

Patent metadata

Field	Value
Publication number	US-2017188521-A1
Application number	US-201615066891-A
Country	US
Kind code	A1
Filing date	Mar 10, 2016
Priority date	Jan 4, 2016
Publication date	Jul 6, 2017
Grant date	—

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.

First claim

What is claimed is:

1 . A computer implemented method for estimating effective pest severity index, the method comprising:
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 associated with the geo-location under consideration; generating a pest forecasting model and a natural enemies forecasting model for each pest associated with the geo-location under consideration, the pest forecasting model and the natural enemies forecasting model being based on the received first set of inputs and the second set of inputs; and estimating the effective pest severity index based on the generated pest forecasting model and the natural enemies forecasting model.

2 . The computer implemented method of claim 1 further comprising:
creating a historical data lookup table based on the received first set of inputs and the second set of inputs and the estimated effective pest severity index;
appending the historical data lookup table with actual effective pest severity index detected for the corresponding first set of inputs and the second set of inputs for a given period of time; and
updating the pest forecasting model and the natural enemies forecasting model based on the actual effective pest severity index.

3 . The computer implemented method of claim 2 , wherein the received first set of inputs and the second set of inputs comprise at least one of participatory sensing inputs and crowdsourcing inputs.

4 . The computer implemented method of claim 2 , wherein updating the pest forecasting model and the natural enemies forecasting model is further based on management practices deployed in the geo-location under consideration.

5 . The computer implemented method of claim 1 further comprising optimizing pesticide application based on the estimated effective pest severity index.

6 . A system for estimating effective pest severity index, the system comprising:
one or more internal data storage devices comprising instructions; and one or more processors operatively coupled to the one or more internal data storage devices, the one or more processors being configured by the instructions to:
receive a first set of inputs pertaining to weather associated with a geo-location under consideration;
receive a second set of inputs pertaining to agronomic information;
generate a pest forecasting model and a natural enemies forecasting model for each pest associated with the geo-location under consideration, the pest forecasting model and the natural enemies forecasting model being based on the received first set of inputs and the second set of inputs; and
estimate the effective pest severity index based on the generated pest forecasting model and the natural enemies forecasting model.

7 . The system of claim 6 , wherein the one or more processors are further configured to:
create a historical data lookup table based on the received first set of inputs and the second set of inputs and the estimated effective pest severity index; append the historical data lookup table with actual effective pest severity index detected for the corresponding first set of inputs and the second set of inputs for a given period of time; and update the pest forecasting model and the natural enemies forecasting model based on the actual effective pest severity index.

8 . The system of claim 7 , wherein the received first set of inputs and the second set of inputs comprise at least one of participatory sensing inputs and crowd sourcing inputs.

9 . The system of claim 7 , wherein the one or more processors are further configured to update the pest forecasting model and the natural enemies forecasting model based on management practices deployed in the geo-location under consideration.

10 . The system of claim 6 , wherein the one or more processors are further configured to optimize pesticide application based on the estimated effective pest severity index.

11 . A computer program product comprising a non-transitory computer readable medium having a computer readable program embodied therein, wherein the computer readable program, when executed on a computing device, causes the computing device to:
receive a first set of inputs pertaining to weather associated with a geo-location under consideration; receive a second set of inputs pertaining to agronomic information; generate a pest forecasting model and a natural enemies forecasting model for each pest associated with the geo-location under consideration, the pest forecasting model and the natural enemies forecasting model being based on the received first set of inputs and the second set of inputs; and estimate the effective pest severity index based on the generated pest forecasting model and the natural enemies forecasting model.

Assignees

• Tata Consultancy Services Ltd

Inventors

• Jagyasi Bhushan Gurmukhdas
• Mohite Jayantrao
• Pappula Srinivasu

Classifications

• G06Q10/04 Primary

  Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202) · CPC title

• A01M99/00

  Subject matter not provided for in other groups of this subclass · CPC title

• G06Q50/02 Primary

  Agriculture; Fishing; Forestry; Mining · CPC title

• A01C14/00

  Methods or apparatus for planting not provided for in other groups of this subclass · CPC title

• A01G22/00 Primary

  Cultivation of specific crops or plants not otherwise provided for · CPC title