Jul 2026· International Scientific Journal of Engineering and Management· Vol 05, pp. 1-7· 0 citations
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
The findings highlight the need for harmonized governance, interoperable digital infrastructure, multidisciplinary collaboration, and implementation-focused research to facilitate the safe and effective integration of autonomous technologies into future disaster management systems, with important implications for policymakers, emergency management agencies, humanitarian organizations, and researchers.
R. Ohaka, A. D. Akinyemi, Ugochukwu Udonna Okonkwo· Journal of Computers and App...· 0 citations
A Multi-Agent Disaster Management Simulator that automates the disaster response process using intelligent software agents, machine learning, graph-based routing, and generative artificial intelligence.
Hemanth S, Manoj M, Harisha S, Dr Manjunath B· International Journal of Adv...· 0 citations
An IoT-enabled disaster management system that integrates distributed sensors, wireless communication networks, cloud computing platforms, and machine learning techniques to improve disaster preparedness, detection, response, and recovery is presented.
Kasiraju Rajvardhan Kasiraju Rajvardhan, Islavath Meenakshi Islavath Meenakshi, A. M. A Mamatha· International Journal of Cre...· 0 citations
The increasing frequency, complexity, and economic costs of disasters worldwide have intensified global demand for robust early warning systems and rapid emergency response mechanisms. Advances in space-based technologies—including satellite imagery, synthetic aperture radar (SAR), remote sensing, and geographic information systems (GIS)—have fundamentally transformed disaster monitoring, situational awareness, and response coordination. In developing countries such as Nigeria, where natural and human-induced disasters including riverine flooding, desertification, oil spills, drought, and coastal erosion occur with alarming regularity, space-derived data offers critical opportunities to strengthen preparedness and response systems. This paper examines the role of space-based data in enhancing early emergency response in Nigeria. It evaluates the institutional structures responsible for disaster management and space technology, including the National Emergency Management Agency (NEMA) and the National Space Research and Development Agency (NASRDA), while analysing their integration within international frameworks such as the Sendai Framework for Disaster Risk Reduction (2015–2030) and the United Nations Platform for Space-based Information for Disaster Management and Emergency Response (UN-SPIDER). Drawing on empirical disaster events, geospatial monitoring practices, and recent peer-reviewed literature, the study demonstrates how satellite technologies—particularly NigeriaSat-1, NigeriaSat-2, Sentinel-1, Sentinel-2, and cloud-based platforms such as Google Earth Engine—enhance situational awareness, hazard monitoring, and emergency coordination. Key challenges including limited technical capacity, inadequate geospatial infrastructure, high cost of high-resolution imagery, and weak institutional integration are critically examined. The paper concludes by proposing strategic policy measures for integrating satellite-derived information into Nigeria's national disaster management framework, with implications for broader sub-Saharan African contexts.
Dr. Emenike John Umesi· International journal of res...· 0 citations
Odisha, a state on India’s eastern coast, is one of the most disaster-prone states in the country. It is affected by cyclones, floods, and droughts. Following the Super Cyclone of 1999, the approach to disaster preparedness has slowly changed from relief to disaster management. In this altered context, civil society organizations – non-governmental organizations, community-based organizations, self-help groups, volunteers and community radio stations – have become essential partners. This paper examines the changing role of civil society in disaster management and resilience across Odisha, drawing on 107 peer-reviewed publications from 2001 to 2025. It highlights that civil society organisations play a robust role in all the phases of disaster, that is, during preparedness through training, spreading early warning signals, and preparing local contingency plans, during response through last mile distribution of relief materials, support evacuation and two-way communication, during recovery through restoration of means livelihood, psychosocial support, resilient building back and during mitigation through advocacy for risk-informed development and ecosystem-based adaptation. Civil society involvement has gradually taken on a formal character through institutional mechanisms such as the Odisha State Disaster Management Authority (OSDMA), the District Disaster Management Authorities (DDMAs), and the Village Disaster Management Committees (VDMCs). While CSOs and NGOs have made significant contributions, there are still many issues they face, such as resource constraints, coordination gaps, capacity limitations, and the sustainability of engagement between disasters. The paper concluded that institutionalizing community-based approaches, expanding participatory communication platforms, establishing sustainable funding mechanisms, and deepening policy engagement are essential for strengthening civil society. The experiences of Odisha can provide salient lessons for the world's disaster-prone regions. These experiences demonstrate that successful disaster governance requires a true partnership among the government, civil society, and the people.
S. Sethi· International Journal For Mu...· 0 citations
Disasters triggered by hydro-meteorological, geophysical, and climatic hazards are increasing in frequency and severity, straining the capacity of conventional disaster risk management (DRM) systems that rely on manual data collection and delayed decision-making [1], [5]. Recent advances in Artificial Intelligence (AI), the Internet of Things (IoT), and Geographic Information Systems (GIS) have opened new possibilities for building smart, data-driven, and anticipatory disaster management systems [3], [14]. This paper presents a systematic review of the literature published mainly between 2020 and 2026 that examines how AI, IoT, and GIS are being integrated to support hazard prediction, real-time monitoring, spatial risk assessment, early warning, and post-disaster response. Fifty-seven peer-reviewed and indexed sources were synthesised following a structured review protocol. The review identifies five major integration themes: (i) sensor-driven early warning networks, (ii) geospatial machine-learning hazard susceptibility mapping, (iii) UAV and remote-sensing based damage assessment, (iv) social-media and big-data situational awareness, and (v) digital-twin-enabled smart-city resilience platforms. The paper further develops a conceptual AI-IoT-GIS integration architecture, presents mathematical formulations commonly used for spatial risk indexing, sensor network reliability, and machine-learning performance evaluation, and illustrates these formulations with worked numerical examples, tables, and charts. The review concludes that while integration of these three technologies significantly improves prediction accuracy and response times, challenges remain around data interoperability, energy-constrained sensor networks, algorithmic bias, and the digital divide affecting adoption in low-resource regions [2], [15].
Chirag Patel· Journal of Commerce, Economi...· 0 citations
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