MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202641124728 A) filed by J. J College Of Engineering And Technology on October 18, 2026, for Artificial Intelligence-Based Multi-Hazard Disaster Prediction And Early Warning System Using Iot Sensors.
Inventors include Abinaya. N; Mrs Mahalakshmi P; Suganya. P; Yobu D; Mrs M Saranya; Sathiya Priya T; Mrs A Apoorvavalli; and Ms Rajeshwari S.
The application for the patent was published on October 30, 2026, under issue no. 44/2026.
Abstract: The present invention relates to an artificial intelligence (AI)-based multi-hazard disaster prediction and early warning system using Internet of Things (IoT) sensors for real-time environmental monitoring, hazard prediction, and timely dissemination of alerts. The system comprises a plurality of distributed IoT sensor nodes configured to measure environmental parameters including temperature, humidity, rainfall intensity, atmospheric pressure, water level, soil moisture, ground vibration, and air quality. A communication module transmits the acquired sensor data to an edge computing unit and/or a cloud-based processing platform, where the data are preprocessed, analysed, and correlated using artificial intelligence and machine learning algorithms. A multi-hazard prediction engine evaluates the processed data to identify abnormal environmental patterns and estimate the probability and severity of hazards such as floods, landslides, earthquakes, forest fires, and extreme weather events. A dynamic risk assessment module generates hazard-specific risk levels based on sensor measurements, historical observations, temporal variations, and predefined geographical thresholds. Upon detecting a potential hazard, an early warning module generates location-specific alerts and disseminates them through mobile applications, SMS, audible alarms, and connected emergency communication devices. The system further supports continuous model updating, sensor fault identification, and prioritisation of alerts according to predicted severity and response time. The invention provides an integrated, scalable, and intelligent approach for improving disaster preparedness, reducing response delays, and supporting risk-informed emergency management.
Disclaimer: Curated by HT Syndication.
