MUMBAI, India, March 13 -- Intellectual Property India has published a patent application (202641005987 A) filed by Easwari Engineering College; Srm Institute Of Science And Technology, Chennai, Tamil Nadu, on Jan. 21, for 'hybrid deep learning and iot integration for real time forest fire detection,segmentation,and spread forecasting.'
Inventor(s) include Dr A. Abirami; Ramsundar M; Sivakumar M; and Swaminathan V M.
The application for the patent was published on March 13, under issue no. 11/2026.
According to the abstract released by the Intellectual Property India: "Hybrid Deep Learning and loT Integration for Real-Time Forest Fire Detection, Segmentation, and Spread Forecasting ABSTRACT OF THE INVENTION . . . This invention focuses on developing a hybrid loT and deep learning-based system for accurate and efficient forest fire detection, segmentation, and spread forecasting. Forest fires pose severe ecological and environmental threats, and early detection is crucial for preventing largescale destruction. Traditional monitoring methods such as manual patrolling and satellite imaging often suffer from delays, limited visibility, and low temporal resolution. To address these challenges, the proposed system integrates ESP32-CAM devices with environmental sensors to collect real-time video and multimodal data from forest regions. Deep learning models including YOLOv8, MA-Net, and ConvLSTM are used to detect fire outbreaks, generate pixelj level fire boundaries, and predict future fire spread, respectively. This automated framework enhances situational awareness, reduces human error, and provides authorities with timely insights to support rapid response, resource allocation, and disaster mitigation."
Disclaimer: Curated by HT Syndication.
