Intellectual Property India Publishes Patent Application for A Federated Generative Artificial Intelligence System For Climate Adaptive Agricultural Decision Support And Sustainable Crop Yield Prediction

MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202641083108 A) filed by Mr. Laxminarayana Thirupathi; Dr. Sivakumar M; Dr. A. Vani; Dr. Biswa Ranjan Senapati; Dr. Mamta Thakur; Mrs. Priyadarshini; Ms. Anju Arya; Ms. S. Yamunadevi; Mrs. G. Priyadharshini; and Dr. Someshwar S on July 06, 2026, for A Federated Generative Artificial Intelligence System For Climate Adaptive Agricultural Decision Support And Sustainable Crop Yield Prediction.

Inventors include Mr. Laxminarayana Thirupathi; Dr. Sivakumar M; Dr. A. Vani; Dr. Biswa Ranjan Senapati; Dr. Mamta Thakur; Mrs. Priyadarshini; Ms. Anju Arya; Ms. S. Yamunadevi; Mrs. G. Priyadharshini; and Dr. Someshwar S.

The application for the patent was published on July 10, 2026, under issue no. 28/2026.

Abstract: [056] The present invention relates to a federated generative artificial intelligence system for climate adaptive agricultural decision support and sustainable crop yield prediction. The system comprises a plurality of agricultural edge nodes configured to receive field- level agricultural data from sensors and local data sources, train local crop intelligence models, and generate privacy-preserving model updates without transmitting raw farm data. A federated coordination server aggregates the protected updates to generate a global climate adaptive model. The system further includes a climate perturbation generator for simulating climate stress scenarios, a yield prediction module for predicting crop yield with uncertainty estimation, a sustainability scoring module for ranking crop management actions based on resource efficiency and yield stability, and a generative agricultural intelligence engine for generating field-specific recommendations. The invention improves privacy preservation, reduces bandwidth usage, supports low-connectivity agricultural environments, detects climate drift, and provides sustainable crop management decisions under changing climatic conditions. Accompanied Drawing [FIGS. 1-2]

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