MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641075888 A) filed by Hindusthan Institute Of Technology on June 19, 2026, for Iot Based Detecting Wild Animal Activity To Generate Caution Using Matlab.
Inventors include Dr. C. Natarajan; K. Kowsalya; Dr. B. Paulchamy; Dr. A. Purushothaman; S. Suganya; Singareddy Nithinreddy; Sudi Naga Surya; Syed Islamuddin; and Vutla Narasimha.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: This Invention presents an innovative and cost-effective safety system aimed at safeguarding tribal communities residing in remote mountainous regions from threats posed by wild animals and forest fires. This project presents a solar- powered embedded system designed for detectingwild animal activity and issuing cautionary alerts. The system integrates various components including a GPS module, motion detection sensors, a GSM module for communication, and an LCD display for local alerting. Powered sustainably through a solar panel and battery backup, the setup is managed by a microcontroller (Arduino Uno), ensuring autonomous operation in remote locations. Data from the sensors is processed in real-time, and upon detection of an animal, the system sends alerts with location data to predefined contacts. To enhance the accuracy and efficiency of animal detection, the system leverages a large dataset of wild animal images collected from camera traps and motion sensors during the preprocessing phase. These images are analyzed using a Hyper parameteroptimized Convolutional Neural Network (CNN), which has demonstrated excellent performance in identifying various animal species. The CNN model is capable of dynamically adapting to different input types, offering quick training, efficient data sharing, and compact model deployment. MA TLAB is used for initial image input and preprocessing, after which the processed data is sent to the microcontroller, allowing detected animal information to be displayed and alerts to be sent automatically . .• The proposed system not only enhances the early detection of threats but also supports faster response times and better resource allocation for forest officials. By combining renewable energy through solar panels, deep learning for animal recognition, and GSM technology for alert communication.
Disclaimer: Curated by HT Syndication.
