MUMBAI, India, Aug. 31 -- Intellectual Property India has published a patent application (202621083513 A) filed by Dr. Swati Pandey; Mayank Bharadwaj; Mohit Chandrawanshi; Manyata Agnihotri; Nancy Patel; Pooja Ramchandani; Janvi Patil; Harshita Gangrade; Khayal Tumreki; and Gautam Kumar Mahto on July 07, 2026, for Autonomous Agricultural Drone For Water Stress Detection Using Artificial Intelligence.
Inventors include Dr. Swati Pandey; Mayank Bharadwaj; Mohit Chandrawanshi; Manyata Agnihotri; Nancy Patel; Pooja Ramchandani; Janvi Patil; Harshita Gangrade; Khayal Tumreki; and Gautam Kumar Mahto.
The application for the patent was published on August 28, 2026, under issue no. 35/2026.
Abstract: ABSTRACT An autonomous agricultural drone system for water stress detection using artificial intelligence is provided. The system comprises an unmanned aerial vehicle configured for autonomous flight over agricultural fields, a multispectral imaging sensor system for capturing images at multiple spectral bands, a thermal imaging sensor for capturing thermal images of crops, a global positioning system receiver for location determination, an onboard data processing unit configured with artificial intelligence algorithms comprising a convolutional neural network for real-time analysis of captured images to detect water stress, a wireless communication module, and a cloud-based analytics platform for generating irrigation recommendations. The convolutional neural network is trained on annotated agricultural images depicting various levels of water stress. The system enables real-time detection of water stress, generation of water stress maps indicating the spatial distribution of water stress across the field, and provision of actionable irrigation recommendations. The system distinguishes water stress from other types of crop stress using a multi-modal approach combining multispectral and thermal imaging data. The autonomous flight capability enables efficient large-scale monitoring with minimal human intervention, while the edge computing framework provides low-latency detection. The cloud-based analytics platform provides advanced data processing, continuous improvement of algorithms, and user-friendly presentation of results. The invention contributes to precision agriculture and sustainable water management by enabling efficient and accurate detection of water stress in crops.
Disclaimer: Curated by HT Syndication.
