Disaster Response and Emergency Management System
Abstract
Natural and man-made disasters continue to extract a catastrophic toll on human lives, infrastructure, and economies across the world. Between 2000 and 2022, disaster events claimed over 1.9 million lives and caused economic losses exceeding USD 2.97 trillion, with climate change accelerating the frequency and intensity of hydro-meteorological events such as cyclones, floods, and droughts. In India, a country that ranks among the world's most disaster-prone nations, the lack of an integrated, technology-enabled disaster response coordination system has repeatedly resulted in delayed relief operations, duplicated resource deployment, and inadequate victim tracing. This paper proposes a comprehensive Disaster Response and Emergency Management System (DREMS) — an AI-driven, IoT-integrated, multi-agency coordination platform designed to support all four phases of disaster management: mitigation, preparedness, response, and recovery. The DREMS architecture comprises six functional modules: a multi-hazard early warning subsystem using satellite and ground sensor fusion, an AI-based damage and casualty assessment engine using satellite imagery analysis, a real-time resource allocation and dispatch optimizer, a decentralized mesh-network communication infrastructure for connectivity-denied disaster zones, a victim registration and family reunification portal, and a post-disaster recovery tracking dashboard. The system was evaluated through a simulated large-scale flood disaster scenario modelled on the 2015 Chennai floods, demonstrating a 34% reduction in resource dispatch response time, 91.4% accuracy in satellite-based damage classification, 87.6% victim registration coverage in simulation, and communication continuity in connectivity-denied zones with mesh network node density of 1 node per 0.8 km². The proposed DREMS framework offers a deployable, scalable model for integrated disaster management aligned with India's National Disaster Management Authority guidelines. Keywords — Disaster Management, Emergency Response, Early Warning System, Satellite Imagery, AI Damage Assessment, Mesh Network, Resource Allocation, NDMA, IoT, Flood Response