MUMBAI, India, Feb. 27 -- Intellectual Property India has published a patent application (202641017622 A) filed by Swarna Bharathi Institute Of Science And Technology, Khammam, Telangana, on Feb. 17, for 'ensemble deep learning system for multi-region agricultural performance prediction.'
Inventor(s) include Mr. Bandla Yugandhara Chary; Somaraju Sai Lasya Charchitha; Ponugoti Ruthika; Gudimalla Sree Nanditha; and Malyala Srinija.
The application for the patent was published on Feb. 27, under issue no. 09/2026.
According to the abstract released by the Intellectual Property India: "The present invention discloses an advanced ensemble deep learning system for accurate multi-region agricultural performance prediction. The proposed system integrates heterogeneous deep learning architectures, including convolutional neural networks (CNN), recurrent neural networks (RNN), and attention-based models, to capture spatial, temporal, and climatic variability across diverse geographical regions. The framework processes multi-source data comprising satellite imagery, soil characteristics, historical crop yield records, weather parameters, irrigation patterns, and market indicators. A dynamic weighted ensemble mechanism aggregates predictions from individual models based on regional data distributions and seasonal variability, thereby improving robustness and generalization. The system incorporates adaptive feature selection and normalization to handle non-linear dependencies and missing data. Cloud-based deployment enables scalable computation and real-time inference for large agricultural datasets. The invention enhances yield forecasting accuracy, risk assessment, and resource optimization, supporting precision agriculture, policy planning, and sustainable farming practices across heterogeneous agro-climatic zones."
Disclaimer: Curated by HT Syndication.
