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ZENODO
Report . 2024
License: CC BY
Data sources: Datacite
ZENODO
Report . 2024
License: CC BY
Data sources: Datacite
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BIG DATA ANALYSIS TO IMPROVE EMERGENCY RESPONSES: COLLECT AND ANALYZE DATA RELATED TO ACCIDENTS AND INJURIES TO IDENTIFY COMMON PATTERNS AND DEVELOP BETTER RESPONSE STRATEGIES: A REVIEW

Authors: Aasem Helael Ali Alharbe, Fahad Mufarrij Majed Alsubaie, Shaker Salah Ali Al Mobtei , Hussain Hadi Mohammed Al Murayh, Mohammed Ali Huraysh Alrabie, Abdullah Mohammed Mana Alyami, Humaidan Ayiedh Naif Alsubaie;

BIG DATA ANALYSIS TO IMPROVE EMERGENCY RESPONSES: COLLECT AND ANALYZE DATA RELATED TO ACCIDENTS AND INJURIES TO IDENTIFY COMMON PATTERNS AND DEVELOP BETTER RESPONSE STRATEGIES: A REVIEW

Abstract

Big data analysis is transforming emergency response systems by enabling the collection and analysis of vast datasets related to accidents and injuries. By leveraging data from various sources, including emergency medical services, geospatial data, weather information, and social media, emergency management agencies can identify common patterns and risk factors. Advanced analytics, such as predictive modeling, geospatial analysis, and real-time data processing, allow for improved resource allocation, faster response times, and proactive risk mitigation. This article explores the role of big data in enhancing emergency response strategies, the methods used to analyze data, and the potential challenges in implementing these solutions. Keywords: Big data analysis, Emergency response, Accident patterns, Predictive analytics, Resource optimization, Real-time data

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average