MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641115375 A) filed by Sri Eshwar College Of Engineering on September 24, 2026, for A Multimodal Adaptive Artificial Intelligence System For Early Detection, Classification, And Severity Assessment Of Natural Disasters.
Inventors include Ms R. Megala; Ms. R. Preethi; Mr. R. Arun; and G. Dency Flora.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: The present invention relates to a Multimodal Adaptive Artificial Intelligence System for early detection, classification, and severity assessment of natural disasters using Artificial Intelligence (AI), Computer Vision, Internet of Things (IoT), remote sensing, and multimodal data fusion technologies. The proposed system acquires and integrates heterogeneous data from satellite imagery, drones, surveillance cameras, weather stations, IoT sensors, seismic sensors, rainfall measurements, geographic information, and historical disaster records to identify and assess natural disaster events at an early stage. An adaptive multimodal AI engine processes the integrated visual, sensor, temporal, spatial, and environmental data to detect and classify disaster types such as floods, landslides, cyclones, wildfires, earthquakes, and other hazardous events. The system further estimates disaster severity, affected regions, potential risk levels, and likely progression using deep learning and spatiotemporal analysis.Explainable Artificial Intelligence (XAI) techniques provide confidence scores and interpretable reasoning for predictions, thereby improving transparency and operational trust. Continuous learning and adaptive model updating enable the system to respond to changing environmental conditions and emerging disaster patterns. Real-time monitoring, geospatial visualization, cloud-based analytics, and automated alert mechanisms support rapid situational awareness and resource prioritization. The proposed invention provides an intelligent decision-support platform for disaster management agencies, emergency responders, government authorities, researchers, and communities, with the objective of reducing response time, improving preparedness, minimizing loss of life and property, and strengthening climate-resilient disaster management.
Disclaimer: Curated by HT Syndication.
