MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202641053915 A) filed by Nandha Engineering College on April 28, 2026, for Iot-Based Intelligent Animal Detection And Repellent System For Energy Efficient Crop Protection.
Inventors include V. Arun Kumar; G. Dineshkumar; T. Jawagar Sanjay; and B. Kavin.
The application for the patent was published on June 26, 2026, under issue no. 26/2026.
Abstract: ABTRACT OF THE INVENTION The present work proposes an Internet of Things (loT)-based intelligent animal detection and repellent system designed to provide efficient, automated, and eco-friendly crop protection in agricultural fields. The system addresses the critical issue of crop damage caused by animal intrusion, which leads to significant economic losses for farmers. It integrates advanced technologies such as computer vision, deep learning, and wireless communication to enable real- time monitoring and response. A camera captures continuous video from the field, which is processed through frame conversion, segmentation, and feature extraction techniques. A trained Convolutional Neural Network (CNN) model is then used to accurately classify animals such as elephants, wild boars, and buffalo, while minimizing false detections caused by environmental foctors. Upon successful identification, the system sends a signal to a microcontroller (Arduino Nano), which activates a non-lethal sound-based repellent mechanism, such as a buzzer, to deter animals safely. Simultaneously, a GSM communication module transmits real-time alerts to the former, ensuring timely awareness and response. The system also includes a user interface through an LCD display for onsite monitoring and supports remote communication for enhanced accessibility. Additionally, the design emphasizes energy efficiency, reliability, and scalability, making it suitable for deployment in both small and large agricultural fields. Overall, the proposed system provides a cost-effective, intelligent, and sustainable solution for modern smart agriculture by reducing crop loss, minimizing human intervention, and ensuring wildlifefriendly protection methods.s. W
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