Intellectual Property India Publishes Patent Application for Soc-Based Multimodal Wildfire Intelligence System With Predictive Risk Assessment, Hybrid Energy Harvesting And Lora Communication

MUMBAI, India, Nov. 6 -- Intellectual Property India has published a patent application (202641130487 A) filed by M. Kumarasamy College Of Engineering; K. Ramakrishnan College Of Engineering; and K. Ramakrishnan College Of Technology on November 02, 2026, for Soc-Based Multimodal Wildfire Intelligence System With Predictive Risk Assessment, Hybrid Energy Harvesting And Lora Communication.

Inventors include Dr. Vimalnath S; Priyadharshini K; Janesh G; Ranjithkumar S; Rithis S; Priyadharshini B; Hariny P; Mrs. Mahima R; and Ganesh S.

The application for the patent was published on November 06, 2026, under issue no. 45/2026.

Abstract: ABSTRACT SOC-BASED MULTIMODAL WILDFIRE INTELLIGENCE SYSTEM WITH PREDICTIVE RISK ASSESSMENT, HYBRID ENERGY HARVESTING AND LORA COMMUNICATION The present invention provides a System-on-Chip (SoC) based multimodal wildfire intelligence system for early detection, predictive risk assessment and real-time communication of wildfire related conditions. The system includes a plurality of sensing modules configured to collect multimodal data including concentrations of gasses indicative of fire, environmental parameters and other parameters related to potential wildfire conditions. In one embodiment, the sensing arrangement comprises an NDIR based multi-gas sensing module for monitoring gasses including carbon monoxide (CO), carbon dioxide (CO2) and methane (CH4) along with environmental sensing elements for monitoring temperature, humidity and smoke.The sensed multimodal data is acquired and processed by an integrated processing architecture based on a System on Chip (SoC) comprising an interface for signal conditioning and data acquisition, and an embedded predictive risk assessment engine. The processing architecture conducts local real-time analysis of the acquired sensor parameters to identify variations, patterns and combinations indicative of potential wildfire initiation. The system computes a predictive wildfire risk value based on the processed multimodal information and classifies the monitored environment into one or more pre-defined risk levels. The system further includes a hybrid energy harvesting arrangement that is arranged to harvest electrical energy from a plurality of available energy sources, including a tree-trunk thermoelectric energy harvesting source.

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