MUMBAI, India, Oct. 11 -- Intellectual Property India has published a patent application (202441027806 A) filed by Dr. Eswaramoorthy V; Soundariya R S; and Anandan P, Sathyamangalam, Tamil Nadu, on April 4, 2024, for 'enhancing agricultural sustainability with ai-driven avian pest management.'
Inventor(s) include Dr. Eswaramoorthy V; Soundariya R S; and Anandan P.
The application for the patent was published on Oct. 10, under issue no. 41/2025.
According to the abstract released by the Intellectual Property India: "The agricultural sector plays a pivotal role in sustaining economies and ensuring food security. HOWCVBI', avian pests pose a significant threat to agricultural productivity. This invention is an innovative approach to enhance agricultural sustainability through the integration of advanced artificial intelligence (Al) techniques, specifically the YOLO (You Only Look Once) algorithm, and [he Jolson Nano edge computing platform. The primary objective of this invention is to develop and implement an Al-driven avian pest management system that can accurately detect and Illunilor avian pcsls in real-time, enabling timely and targeted interventions. The YOLO algorithm, renowned for its real-lime object detection capabilities, is employed to identify avian posts and their behaviors from high-resolution images and videos captured in agricultural fields. The methodology involves collecting and annotating a diverse datacel of avian pest instances, training and optimizing the YOLO model, and deploying it on the Jetson Nano platform for edge computing. The optimized model can recognize various avian pest species and their activities, such as perching, feeding, and flying. The Jelson Nano, with its hardware acceleration capabilities, facilitates real-lime inference. enabling swifi and accurate pest detection. Upon detection of avian pests. the system generates alerts and notifications to inform farmers of potential threats. Additionally. a decision support system provides tailored recommendations based on the detected pest species, their behavior, and prevailing environmental conditions. This empowers farmers to implement precise and effective pest management strategies, minimizing the use of chemical interventions and reducing ecological impact. The invention emphasizes community engagement through training sessions and stakeholder collaboration, fostering knowledge exchange and ensuring the successful adoption of the Al-driven avian pest management system. Continuous monitoring, data analysis, and model refinement guarantee the system's efficacy, adaptability, and scalability. The invention aligns with the goal of achieving sustainable agricultural practices by I mitigating the impact of avian pes'(s on crop yields and promoting environmentally conscious pest management. Through 'he synergy of the YOLO algorithm and Jetson Nano, this innovative A|- driven approach has the potential to revolutionize avian pes! management in the Western Zones of Tamil Nadu, serving as a model for sustainable agriculture across similar regions."
Disclaimer: Curated by HT Syndication.
