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Harnessing trustable crowdsourcing power for flood disaster evaluation

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Abstract

This paper presents a proposed information and communication technology-based system that uses a crowdsourcing model to collect and provide accurate and up-to-date information about flooded areas. The system aims to assist relief organizations to act more efficiently following a flood disaster. The system collects data related to four informational requirements: people and animals, facilities for living, medical facilities, and shelters and roads. The proposed system includes a malicious user detection algorithm to prevent inaccurate information and keep the data current. The paper also introduces an information aggregation algorithm and a user reputation score algorithm to identify high-scoring users. The three proposed algorithms are assessed using simulation, which shows that they can accurately identify malicious users and rank non-malicious users. By providing up-to-date information from flooded areas, the system can help relief organizations respond more effectively to a flood disaster.

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Code availability

https://github.com/sajedeh2112/crowdsourcing-for-flood-disaster-evaluation. Open source, 2023, Developed in Python.

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Authors and Affiliations

  1. Pervasive and Cloud Computing Lab, Faculty of Electrical and Computer Engineering, University of Birjand, Birjand, Iran

    Sajedeh Abbasi & Hamed Vahdat-Nejad

  2. Birjand University of Technology, Birjand, Iran

    Hossein Moradi

Authors
  1. Sajedeh Abbasi
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  2. Hamed Vahdat-Nejad
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  3. Hossein Moradi
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Contributions

SA: Conceptualization, Software, Original draft preparation. HV-N: Supervision—Conceptualization, Methodology—Reviewing and Editing. HM: Supervision—Reviewing and Editing.

Corresponding author

Correspondence to Hamed Vahdat-Nejad.

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Abbasi, S., Vahdat-Nejad, H. & Moradi, H. Harnessing trustable crowdsourcing power for flood disaster evaluation. Nat Hazards (2024). https://doi.org/10.1007/s11069-024-06547-8

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