Trustable Mobile Crowd Sourcing for Acquiring Information from a Flooded Smart Area

TL;DR

This paper proposes a crowdsourcing scheme utilizing smartphones and IoT technology to quickly gather accurate information from flooded areas for effective rescue operations, including malicious user detection.

Contribution

It introduces a novel crowdsourcing framework for flooded environments that classifies information needs and incorporates malicious user detection to improve data reliability.

Findings

The scheme effectively detects malicious users.

It ensures high quality and accurate information collection.

Simulation results validate the approach's effectiveness.

Abstract

Flood is a natural phenomenon that causes severe environmental damage and destruction in smart cities. After a flood, topographic, geological, and living conditions change. As a result, the previous information regarding the environment is no more valid. Rescue and relief organizations that intend to help the affected people need to obtain new and accurate information about the conditions of the flooded environment. Acquiring this required information in the shortest time is a challenge for realizing smart cities. Due to the advances in the Internet of Things technology and the prevalence of smartphones with several sensors and functionalities, it is possible to obtain the required information by leveraging the Crowdsourcing model. In this paper, the information required from a flooded area is classified into four categories: victim, Facility and Livelihood, medical, and transfer. Next, a crowdsourcing scheme for acquiring information is proposed, including malicious user detection to ensure the accuracy of information received. Finally, simulation results indicate that the proposed scheme correctly detects malicious users and ensures the quality of obtained information.