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A Next Generation Technology Victim Location and Low Level Assessment Framework for Occupational Disasters Caused by Natural Hazards
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Author(s): Nik Bessis (Edge Hill University, UK), Eleana Asimakopoulou (University of Bedfordshire, UK), Peter Norrington (University of Bedfordshire, UK), Suresh Thomas (University of Bedfordshire, UK)and Ravi Varaganti (University of Bedfordshire, UK)
Copyright: 2012
Pages: 10
Source title:
Machine Learning: Concepts, Methodologies, Tools and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-60960-818-7.ch806
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Abstract
Much work is underway within the broad next generation technologies community on issues associated with the development of services to support interdisciplinary domains. Disaster reduction and emergency management are domains in which utilization of advanced information and communication technologies (ICT) are critical for sustainable development and livelihoods. In this article, the authors aim to use an exemplar occupational disaster scenario in which advanced ICT utilization could present emergency managers with some collective computational intelligence in order to prioritize their decision making. To achieve this, they adapt concepts and practices from various next generation technologies including ad-hoc mobile networks, Web 2.0, wireless sensors, crowd sourcing and situated computing. On the implementation side, the authors developed a data mashup map, which highlights the criticality of victims at a location of interest. With this in mind, the article describes the service architecture in the form of data and process flows, its implementation and some simulation results.
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