MUMBAI, India, Aug. 24 -- Intellectual Property India has published a patent application (202641097182 A) filed by K. T. Sree Lakshana; S. Rathi Varsha; B. Tharshini; Vivekanandha College Of Engineering For Women; S. Saranya; and K. Radha on August 12, 2026, for A System And Method For Precision Farming Decision Support Using Computer Vision, Iot, And Explainable Deep Learning.
Inventors include K. T. Sree Lakshana; S. Rathi Varsha; B. Tharshini; Vivekanandha College Of Engineering For Women; S. Saranya; and K. Radha.
The application for the patent was published on August 21, 2026, under issue no. 34/2026.
Abstract: The invention relates to precision agriculture, and more particularly to an AI-driven decision support system that combines crop image acquisition, IoT-based environmental sensing, edge preprocessing, deep learning analysis, explainable AI, cloud analytics, and farmer-facing interfaces. Crop images from RGB, multispectral, hyperspectral, mobile, or UAV sources are analysed using models such as CNN, EfficientNet, ResNet, MobileNet, ViT, and YOLO to detect disease, pests, nutrient deficiency, weed growth, and crop stress, while sensor data including soil moisture, temperature, pH, conductivity, humidity, rainfall, light intensity, wind speed, and nutrient levels are integrated with weather and historical records. The system generates interpretable prediction maps and actionable recommendations for irrigation, fertilizer optimization, pest and disease control, harvesting, and automated resource management, thereby improving transparency, productivity, resource efficiency, and sustainable farming practices. Fig. 1 best characterises the invention.
Disclaimer: Curated by HT Syndication.
