MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202641091274 A) filed by Lenin Kalyanasundaram Venugopal; and Ganesh Babu Oorkavalan on July 27, 2026, for Iot-Enabled Machine Learning System For Paddy Leaf Disease Prediction And Yield Optimization.
Inventors include Lenin Kalyanasundaram Venugopal; and Ganesh Babu Oorkavalan.
The application for the patent was published on July 31, 2026, under issue no. 31/2026.
Abstract: An Internet of Things enabled machine learning system for paddy leaf disease prediction and yield optimization is disclosed. The system comprises an imaging subsystem, including fixed canopy nodes, guided mobile capture, or aerial survey, acquiring paddy foliage images, and Internet of Things field nodes measuring in- canopy microclimate including air temperature, humidity, and leaf wetness. A processing arrangement of edge and server intelligence applies trained machine learning models to detect and identify paddy leaf diseases from imagery, distinguish them from nutrient deficiency and pest damage, and assess severity and spatial distribution; and, fusing the image-derived crop state with the sensed microclimate over time, predicts disease onset and progression early rather than detecting late. It generates prioritized recommendations localized to affected regions, specifying targeted intervention, dose, and timing in preference to blanket spraying, together with irrigation and nutrition guidance and yield forecasts. Solar-powered nodes, offline edge operation, local-language pictorial delivery, expert escalation, area-wide epidemic early warning, and continual learning protect and optimize smallholder paddy yield.
Disclaimer: Curated by HT Syndication.
