Intellectual Property India Publishes Patent Application for Intelligent Iot-Enabled Multi-Hazard Disaster Monitoring, Prediction And Adaptive Response Network

MUMBAI, India, Sept. 7 -- Intellectual Property India has published a patent application (202641104149 A) filed by Mrs. Pilaka Anusha; Ms. V. Indu; Ms. Binodini Kar; Mrs. D. Jhansi Lakshmi; Mrs. Saujanya Gudese; Mrs. Samrajyam Mekala; and Dr. Jami Venkata Suman on August 29, 2026, for Intelligent Iot-Enabled Multi-Hazard Disaster Monitoring, Prediction And Adaptive Response Network.

Inventors include Mrs. Pilaka Anusha; Ms. V. Indu; Ms. Binodini Kar; Mrs. D. Jhansi Lakshmi; Mrs. Saujanya Gudese; Mrs. Samrajyam Mekala; and Dr. Jami Venkata Suman.

The application for the patent was published on September 04, 2026, under issue no. 36/2026.

Abstract: The present invention discloses an intelligent IoT-enabled multi-hazard disaster monitoring, prediction and adaptive response network comprising geographically distributed intelligent sensing nodes, edge intelligence units, a distributed event-correlation engine, a dynamic risk-state engine, a disaster propagation prediction engine, a resilient communication manager, and an adaptive response engine. Heterogeneous sensor measurements are locally processed into normalized event descriptors and spatially, temporally, and cross-modally correlated to validate hazardous events and reduce false alarms. Dynamic risk states control sensing frequency, sensor activation, processing, and communication operations. The disaster propagation prediction engine generates time-indexed predicted risk zones, which cause sensing nodes located along an estimated hazard progression path to adaptively increase sensing resolution. The communication manager establishes alternative node- to-node relay paths upon communication degradation. Predicted risk zones are combined with vulnerability and exposure information to generate geographically differentiated warnings and response instructions. The network thereby provides resilient, adaptive, and predictive monitoring of multiple disaster conditions even during partial communication infrastructure failure. Accompanied Drawing [FIGS. 1-2]

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