Edge–Cloud Intelligence in Disaster Management: A Review of Architectures, Challenges, and Opportunities
TL;DR
The proposed model demonstrates how distributed computing techniques with energy-aware techniques can result in scalable and sustainable disaster response systems.
Abstract
Natural disasters are happening more often and with more force, which puts a lot of stress on disaster management systems. They require fast, reliable and sustainable technologies. In conventional centralized systems, there are problems with latency, network congestion and a requirement for continuous connectivity. These can slow down the early detection and rapid response. In this study, the Smart Disaster Alert Response System (SDARS), a new approach that integrates cloud computing, edge computing, and green computing to enhance resilience, cut down latency and ensure sustainability. SDARS relies on IoT sensors that constantly monitor the environment, and edge nodes that do initial data processing to provide real-time alerts with low latency. The cloud allows for big data analysis to be conducted to gain predictive knowledge and optimise resource allocation. Energy-efficient (green computing) techniques are also used to conserve energy and extend the lifespan of devices in low-energy environments. The experimental evaluation of SDARS reveals that it can raise alarms in less than a second, consumes 35% less energy compared to conventional systems and continues to operate despite network partition. In conclusion, the proposed model demonstrates how distributed computing techniques with energy-aware techniques can result in scalable and sustainable disaster response systems.