Abstract
Presently, the Internet of Things (IoT) and big data analytics technology offer enormous opportunities to disaster risk management services. Recent disaster risk management patterns involve disaster risk reduction to avoid future disaster risks, minimize current disastrous risks, resilience building, and disaster loss reduction. The main challenges in disaster management are communication within a disaster zone which is being disrupted. In this paper, the Internet of Things assisted disaster risk management framework (IOTDRMF) has been proposed for technical resources to communicate the emergency time and better visibility into reliable and prompt decision-making through observing, evaluating, and forecasting natural disasters. This IOTDRMF utilizes big data analytics to analyze disaster risk management build a kind of spatial data communication network infrastructure, making it a priority to establish rules, protocols, and knowledge sharing. The experimental results show the IOTDRMF, and big data analytics compensate for a weak communication network infrastructure and better decision-making to handle disaster risk management.
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Heqing Huang, BalaAnand Muthu contributed to conception and design of study. Sivaparthipan C.B was involved in acquisition of data. Heqing Huang contributed to analysis and/or interpretation of data. Li Zhou was involved in drafting the manuscript.
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Communicated by Vicente Garcia Diaz.
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Zhou, L., Huang, H., Muthu, B. et al. Design of Internet of Things and big data analytics-based disaster risk management. Soft Comput 25, 12415–12427 (2021). https://doi.org/10.1007/s00500-021-05953-5
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DOI: https://doi.org/10.1007/s00500-021-05953-5