Utilizing next generation emerging technologies for enabling collective computational intelligence in disaster management

Bessis, Nik; Assimakopoulou, Eleana; Aydin, Mehmet Emin; Xhafa, Fatos

Abstract

Much work is underway within the broad next generation emerging technologies community on issues associated with the development of services to foster synergies and collaboration via the integration of distributed and heterogeneous resources, systems and technologies. In this chapter, we discuss how these could help coin and prompt future direction of their fit-to-purpose use in various real-world scenarios including the proposed case of disaster management. Within this context, we start with a brief overview of these technologies highlighting their applicability in various settings. In particular, we review the possible combination of next generation emerging technologies such as ad-hoc and sensor networks, grids, clouds, crowds and peer to peer with intelligence techniques such as multi-agents, evolutionary computation and swarm intelligence for augmenting computational intelligence in a collective manner for the purpose of managing disasters. We then conclude by illustrating a relevant model architecture and by presenting our future implementation strategy. © 2011 Springer-Verlag Berlin Heidelberg.

Citation

Bessis, N., Assimakopoulou, E., Aydin, M. E., & Xhafa, F. (2011). Utilizing next generation emerging technologies for enabling collective computational intelligence in disaster management. Studies in Computational Intelligence, 352, 503-526. https://doi.org/10.1007/978-3-642-20344-2_19

• Journal Article Type: Review
• Publication Date: Aug 4, 2011
• Journal: Studies in Computational Intelligence
• Print ISSN: 1860-949X
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 352
• Pages: 503-526
• Series Title: Studies in Computational Intelligence
• Series Number: 352
• DOI: https://doi.org/10.1007/978-3-642-20344-2_19
• Keywords: collective intelligence, disaster management
• Public URL: https://uwe-repository.worktribe.com/output/966928
• Publisher URL: http://dx.doi.org/10.1007/978-3-642-20344-2_19