Applications of Big Data in Disaster Management: A Review

Applications of Big Data in Disaster Management: A Review

Sushrut M.
DOI: 10.4018/IJSPPC.2021100101
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Abstract

Disasters can be both manmade or natural, but the consequences have been atrocious and require swift action to manage the devastating impact. The digital footprint is being left behind at a huge rate in the modern world. The overwhelming digital interactions across the technology-oriented world has necessitated the need of an efficient way to organise and utilise them for a better tomorrow. With ease of access to the internet and high percentage of e-literacy rates, involvement of the citizens of the world in the digital arena is increasing at an impeccable exponential rate. This data is generated at the rate of a quintillion bytes per day and has a total probability to increase furthermore. This paper was synthesized in an effort to consolidate the existing technology in handling the crisis with innovation. In this context, the paper has talked about the utility of big data and the related technological concepts, which help to monitor or detect the hazard, mitigate the efforts in tackling it, and systemize the post-disaster recovery process statistically.
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3. Cloud Computing Of Big Data

The evolution of Big data has come a long way through by addressing various obstacles and novel requirements related to storage of information. Back in the initial days, cassettes and floppy disks were used as secondary storage systems. Later, disk drives became popular and miniature drives replaced the large sized CDs. With the advancement of technology, it is now able to store the data in cloud platforms and eliminate a serious constraint of storage devices.

Cloud services provide On-Demand computing features which benefits the consumers to pay as per the use. (Priyanshu Srivastava, Rizwan Khan, 2018) The Anytime Anywhere computing abilities makes the cloud platforms more attractive and feasible. The reliability factor is also a vital parameter in guaranteeing the trust to the users. All these features combine together to provide a seamless hasslefree platform for dynamic and scalable data analysis.

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