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Reliable and Smart Decision Support System for Emergency Management Based on Crowdsourcing Information

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Exploring Intelligent Decision Support Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 764))

Abstract

Command and control centres face the challenge of quickly obtaining accurate information about emergencies they should response to. Conversely, crowdsourcing information and mobile technologies offer great potential for better engaging eyewitnesses in emergency and crisis management processes. This paper describes the vision and the realisation of the RESCUER system, a smart and interoperable decision support system for emergency and crisis management based on mobile crowdsourcing information. Eight evaluation exercises with end users were performed during the project duration, in addition to technical verifications of the individual system components. The results of the evaluation exercises were quite positive and helped to continuously improve and extend the system.

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Notes

  1. 1.

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Acknowledgements

The work reported in this paper was carried out in the RESCUER project, a European-Brazilian collaborative project funded by the European Commission (Grant: 614154) and by the Brazilian National Council for Scientific and Technological Development CNPq/MCTI (Grant: 490084/2013-3).

Author information

Authors and Affiliations

  1. Fraunhofer Institute for Experimental Software Engineering, Kaiserslautern, Germany

    Karina Villela & Claudia Nass

  2. Fraunhofer Project Center for Software and Systems Engineering, Federal University of Bahia, Instituto Federal de Educacão, Ciência e Tecnologia da Bahia, Salvador, Brazil

    Renato Novais

  3. Fraunhofer Project Center for Software and Systems Engineering, Federal University of Bahia, Salvador, Brazil

    Paulo Simões Jr.

  4. University of Sao Paulo, Sao Carlos, Brazil

    Agma Traina & Jose Rodrigues Jr.

  5. Polytechnic University of Madrid, Madrid, Spain

    Jose Manuel Menendez & Jorge Kurano

  6. German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany

    Tobias Franke & Andreas Poxrucker

Authors
  1. Karina Villela
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  2. Claudia Nass
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  3. Renato Novais
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  4. Paulo Simões Jr.
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  5. Agma Traina
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  6. Jose Rodrigues Jr.
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  7. Jose Manuel Menendez
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  8. Jorge Kurano
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  9. Tobias Franke
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  10. Andreas Poxrucker
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Corresponding author

Correspondence to Karina Villela .

Editor information

Editors and Affiliations

  1. Departamento de Informática y Sistemas, Facultad de Informática, Universidad de Murcia, Murcia, Spain

    Rafael Valencia-García

  2. Departamento de Informática y Sistemas, Facultad de Informática, Universidad de Murcia, Murcia, Spain

    Mario Andrés Paredes-Valverde

  3. Departamento de Informática y Sistemas, Facultad de Informática, Universidad de Murcia, Murcia, Spain

    María del Pilar Salas-Zárate

  4. Division of Research and Postgraduate Studies, Instituto Tecnológico de Orizaba, Orizaba, Veracruz, Mexico

    Giner Alor-Hernández

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Villela, K. et al. (2018). Reliable and Smart Decision Support System for Emergency Management Based on Crowdsourcing Information. In: Valencia-García, R., Paredes-Valverde, M., Salas-Zárate, M., Alor-Hernández, G. (eds) Exploring Intelligent Decision Support Systems. Studies in Computational Intelligence, vol 764. Springer, Cham. https://doi.org/10.1007/978-3-319-74002-7_9

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  • DOI: https://doi.org/10.1007/978-3-319-74002-7_9

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  • Online ISBN: 978-3-319-74002-7

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