MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202641086294 A) filed by G. Srujana Bharathi; Chaitanya Bharathi Guduru; Raja Sharath Chandra Guduru; Dr. Annapurna Gummadi; and Ravindra Changala on July 14, 2026, for Iot-Enabled Machine Learning System For Paddy Leaf Disease Prediction And Yield Optimization.
Inventors include G. Srujana Bharathi; Chaitanya Bharathi Guduru; Raja Sharath Chandra Guduru; Dr. Annapurna Gummadi; and Ravindra Changala.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: ABSTRACT OF THE INVENTION: The invention provides an IoT-Enabled Machine Learning System for early prediction of paddy leaf diseases and optimization of crop yield. Deployed IoT sensors and cameras collect real-time field data (images, soil moisture, temperature, humidity). Advanced ML models (CNNs for disease detection and ensemble regressors for yield forecasting) analyze this data to identify diseases like Bacterial Leaf Blight, Brown Spot, and Rice Blast with over 95% accuracy. The system generates timely alerts and personalized recommendations for farmers on pesticide application, irrigation, and nutrient management. Hybrid edge-cloud processing ensures low latency even in remote areas. Field trials demonstrate substantial reduction in crop losses and 20-35% yield improvement while promoting sustainable practices through minimized chemical usage. The user-friendly interface supports smallholder farmers with multilingual notifications. This technology advances precision agriculture, contributing to food security and farmer livelihoods in paddy-growing regions.
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