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Improving Disaster Resilience and Mitigation - IT Means and Tools pp 135–151Cite as

Disaster Early Warning and Relief: A Human-Centered Approach

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Abstract

Effective need collection is a major part of post-disaster assessment and recovery. A system for matching needs with available offers is an essential component for the recovery of communities in the aftermath of natural disasters. In the classic approach, the needs of disaster-stricken communities are collected by rescue personnel sampling a geographic grid and using emergency communication facilities. Subsequently, needs are matched to offers available at some central server and relief interventions are planned to deliver them. In this chapter, after an introduction to this approach, we explore the new notion of peer-to-peer community empowerment for some key activities of disaster management, including early warning systems, needs collection, and need-to-offer matching. Then, we present the design of a framework that leverages on the capacity for the communities to self-organize during crisis management, proposing advanced algorithms and techniques for need-offer matching. Our framework supports pre- and post-disaster use of social networks information and connectivity via an evolvable vocabulary, and supports metrics for resilience assessments and improvement.

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Acknowledgments

The authors wish to thank Prof. Mustafa Erdik, Dr. Doğan Kalafat and Dr. Mehmet Yılmazer from KOERI for the valuable information they kindly provided. This work was co-funded by the European Commission under the Information and Communication Technologies theme of the 7th Framework Programme, Integrated Project ARISTOTELE (contract no. FP7-257886).

Author information

Authors and Affiliations

  1. Computer Science Department, Università degli Studi di Milano, via Bramante, 65, I-26013, Crema (CR), Italy

    Ernesto Damiani, Mustafa Asim Kazancigil & Fulvio Frati

  2. CNRS Joint Research Unit in Sciences and Technologies for Risk Management, University of Technology of Troyes, Troyes, France

    Babiga Birregah

  3. Faculty of Computer Science and Automation, Technische Universität Ilmenau, Ilmenau, Germany

    Rainer Knauf

  4. School of Information Environment, Tokyo Denki University, Tokyo, Japan

    Setsuo Tsuruta

Authors
  1. Ernesto Damiani
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  2. Mustafa Asim Kazancigil
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  3. Fulvio Frati
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  4. Babiga Birregah
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  5. Rainer Knauf
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  6. Setsuo Tsuruta
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Corresponding author

Correspondence to Ernesto Damiani .

Editor information

Editors and Affiliations

  1. Institute of Computer Science and ‘Gheorghe Asachi’ Technical University of Iasi, Iasi, Romania

    Horia-Nicolai Teodorescu

  2. Faculty of Industrial Engineering and Management, Samuel Neaman Institute for Advanced Studies,Technion – Israel Institute of Technology, Haifa, Israel

    Alan Kirschenbaum

  3. Institute of Mathematics and Computer Science of the Academy of Sciences of Moldova, Chisinau, Moldova

    Svetlana Cojocaru

  4. Department of Global Health and Populati, Harvard University, Cambridge, Massachusetts, USA

    Claude Bruderlein

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© 2014 Springer Science+Business Media Dordrecht

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Damiani, E., Kazancigil, M.A., Frati, F., Birregah, B., Knauf, R., Tsuruta, S. (2014). Disaster Early Warning and Relief: A Human-Centered Approach. In: Teodorescu, HN., Kirschenbaum, A., Cojocaru, S., Bruderlein, C. (eds) Improving Disaster Resilience and Mitigation - IT Means and Tools. NATO Science for Peace and Security Series C: Environmental Security. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9136-6_9

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  • DOI: https://doi.org/10.1007/978-94-017-9136-6_9

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-017-9135-9

  • Online ISBN: 978-94-017-9136-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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