Sahay: an Integrated, Kerala-focused Disaster Management, Early-warning and Rescue Coordination Platform
Year: 2026
Type: preprint
Abstract: Natural disasters such as floods, landslides, and extreme rainfall require timely prediction, reliable information, effective communication, and coordinated emergency response. Recent research has explored Artificial Intelligence (AI), Machine Learning (ML), Geographic Information Systems (GIS), Internet of Things (IoT), crowdsourcing, and early-warning technologies for different aspects of disaster management. However, many existing approaches remain fragmented, focusing mainly on prediction, monitoring, mapping, or information collection rather than connecting these functions with practical emergency response. This review examines existing disastermanagement research and software technologies, with particular emphasis on Kerala-specific studies related to landslides, rainfall, floods, and real-time monitoring. Based on the identified research gaps, SAHAY is proposed as an integrated Keralafocused disaster-management and decisionsupport platform that combines real-time weather and location data, AI/ML-based risk assessment, GIS visualization, personalized alerts, citizen incident reporting, SOS, evacuation and shelter assistance, and rescue-team coordination. The proposed platform aims to bridge the gap between disaster prediction and emergency response through a unified, multi-role system.
Authors: Prasad, Aparna, Devis, Jinson
Institution: Amal Jyothi College of Engineering
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7224320319