Harnessing trustable crowdsourcing power for flood disaster evaluation

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.