MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202621056443 A) filed by Dr. D. Y. Patil Institute Of Technology, Pimpri, Pune - on May 04, 2026, for Smart Farm Security System.
Inventors include Mrs. Vasudha Phaltankar; Mr. Sharad Adsure; Gayatri Vijay Chim; Priyanka Ravindra Pilley; Chinmay Dilip Chavda; and Dattatray Sanjay Nikam.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: The Smart Farm Security System offers an AI-based solution for real-time animal detection and farm intrusion prevention. Based on deep learning models, the system detects and classifies animals, distinguishing between livestock and wildlife. It includes automated deterrent features such as species-specific sound alerts and real-time notifications to deter crop damage. The system improves farm security, minimizes manual surveillance activities, and encourages sustainable wildlife management. Monitoring livestock is an essential aspect of modern farm management. Traditional methods of tracking livestock are labour-intensive and error-prone. This project proposes a real-time animal detection system utilizing advanced deep learning models, specifically YOLO (You Only Look Once) and TensorFlow Object Detection API. These models enable the automated detection and tracking of livestock in farm environments. A custom object detection model is trained using a dataset of farm animals (cows, wild boars, and deer). This model can accurately identify and classify animals under dynamic conditions with varying lighting and backgrounds. The system uses open- source frameworks like YOLOv4, YOLOv5, YOLOv8 or TensorFlow's Object Detection `API to perform real-time object detection. In addition, the solution combines AI-powered motion tracking and real-time anomaly detection to accurately identify suspicious activity. The species-specific alarms are created to disrupt farm operations as little as possible while still deterring wildlife. The solution is power-efficient, optimizing low-power consumption for deployment in rural and remote communities with low infrastructure levels. Moreover, its cloud-based analysis allows farmers to analyze historical intrusion patterns to optimize preventive measures. This new method guarantees an affordable, scalable, and AI-based farm security system, enhancing agricultural productivity and sustainability.
Disclaimer: Curated by HT Syndication.
