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- W2942433350 abstract "The recent development of big data analytics (BDA) and the Internet of Things (IoT) technologies create a huge opportunity for both disaster management systems and disaster-related authorities (emergency responders, police, public health, and fire departments) to acquire state-of-the-art assistance and improved insights for accurate and timely decision-making. The motivation behind this research is to pave the way for effective utilization of the available opportunities that the BDA and IoT collaboratively offer to predict, understand and monitor disaster situations. Most of the conventional disaster management systems lack the support for multiple new data sources and real-time big data processing tools that can assist decision makers with quick and accurate results. This paper highlights the importance of BDA and IoT for disaster management and investigates recent studies directed towards the same. We classify a thematic taxonomy with several related attributes and inspect the prevalent solutions to propose a conceptual reference model for the deployment of BDA- and IoT-based disaster management environments. The reference model with its proposed integrated parameters can provide guidelines to harvest, transmit, manage, and analyze disaster data from various data sources to deliver updated and valuable information for disaster management. We also enumerate some important use cases from a disaster management perspective. Finally, we highlight the main research challenges that need to be addressed in such an important field of research." @default.
- W2942433350 created "2019-05-03" @default.
- W2942433350 creator A5005835956 @default.
- W2942433350 creator A5023820143 @default.
- W2942433350 creator A5024067855 @default.
- W2942433350 creator A5024707647 @default.
- W2942433350 date "2019-01-01" @default.
- W2942433350 modified "2023-10-16" @default.
- W2942433350 title "The Rising Role of Big Data Analytics and IoT in Disaster Management: Recent Advances, Taxonomy and Prospects" @default.
- W2942433350 cites W1014033202 @default.
- W2942433350 cites W133502895 @default.
- W2942433350 cites W1487925325 @default.
- W2942433350 cites W1771314880 @default.
- W2942433350 cites W1772616240 @default.
- W2942433350 cites W1793690408 @default.
- W2942433350 cites W1900961547 @default.
- W2942433350 cites W1934362406 @default.
- W2942433350 cites W1963620879 @default.
- W2942433350 cites W1977933711 @default.
- W2942433350 cites W1990171006 @default.
- W2942433350 cites W1999609115 @default.
- W2942433350 cites W2010310876 @default.
- W2942433350 cites W2010955799 @default.
- W2942433350 cites W2026942921 @default.
- W2942433350 cites W2032082575 @default.
- W2942433350 cites W2058889809 @default.
- W2942433350 cites W2081430667 @default.
- W2942433350 cites W2094895786 @default.
- W2942433350 cites W2098387782 @default.
- W2942433350 cites W2111619626 @default.
- W2942433350 cites W2118023920 @default.
- W2942433350 cites W2131307433 @default.
- W2942433350 cites W2131954179 @default.
- W2942433350 cites W2136922540 @default.
- W2942433350 cites W2157954477 @default.
- W2942433350 cites W2164900158 @default.
- W2942433350 cites W2175381712 @default.
- W2942433350 cites W2238499080 @default.
- W2942433350 cites W2266212058 @default.
- W2942433350 cites W2283027854 @default.
- W2942433350 cites W2293066912 @default.
- W2942433350 cites W2314029052 @default.
- W2942433350 cites W2314864947 @default.
- W2942433350 cites W2342601507 @default.
- W2942433350 cites W2344683494 @default.
- W2942433350 cites W2513908469 @default.
- W2942433350 cites W2532521045 @default.
- W2942433350 cites W2536566510 @default.
- W2942433350 cites W2540570975 @default.
- W2942433350 cites W2549412929 @default.
- W2942433350 cites W2552428250 @default.
- W2942433350 cites W2554382158 @default.
- W2942433350 cites W2560279756 @default.
- W2942433350 cites W2562226287 @default.
- W2942433350 cites W2562710973 @default.
- W2942433350 cites W2571149404 @default.
- W2942433350 cites W2571300184 @default.
- W2942433350 cites W2593197694 @default.
- W2942433350 cites W2613310014 @default.
- W2942433350 cites W2614882898 @default.
- W2942433350 cites W2622903484 @default.
- W2942433350 cites W2726150830 @default.
- W2942433350 cites W2735541318 @default.
- W2942433350 cites W2745024523 @default.
- W2942433350 cites W2748051370 @default.
- W2942433350 cites W2753835807 @default.
- W2942433350 cites W2754546121 @default.
- W2942433350 cites W2764035779 @default.
- W2942433350 cites W2766908073 @default.
- W2942433350 cites W2772049907 @default.
- W2942433350 cites W2783747732 @default.
- W2942433350 cites W2787390775 @default.
- W2942433350 cites W2789750555 @default.
- W2942433350 cites W2791084881 @default.
- W2942433350 cites W2791088620 @default.
- W2942433350 cites W2792598060 @default.
- W2942433350 cites W2792865798 @default.
- W2942433350 cites W2803201508 @default.
- W2942433350 cites W2803317413 @default.
- W2942433350 cites W2804319089 @default.
- W2942433350 cites W2804439326 @default.
- W2942433350 cites W2806017553 @default.
- W2942433350 cites W2808412861 @default.
- W2942433350 cites W2810962470 @default.
- W2942433350 cites W2883922993 @default.
- W2942433350 cites W2888037900 @default.
- W2942433350 cites W2888056532 @default.
- W2942433350 cites W2890327594 @default.
- W2942433350 cites W2902418758 @default.
- W2942433350 cites W2907139784 @default.
- W2942433350 cites W2964248614 @default.
- W2942433350 cites W3125866593 @default.
- W2942433350 cites W3151685851 @default.
- W2942433350 doi "https://doi.org/10.1109/access.2019.2913340" @default.
- W2942433350 hasPublicationYear "2019" @default.
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