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Title	Sustainable Flood Risk Identification And Assessment Using Artificial Intelligence: A Literature Review And Case Scenario
ID_Doc	53962
Authors	Ahmed I.; Ahmad M.; Chehri A.; Joen G.
Year	2024
Published	Proceedings - 2024 IEEE World Forum on Public Safety Technology, WFPST 2024
DOI	http://dx.doi.org/10.1109/WFPST58552.2024.00041
Abstract	The combination of Internet of Things (IoT) and Artificial Intelligence (AI) has been widely applied in various fields, including transportation, agriculture, tourism, smart cities, environmental monitoring, and security. The growing accessibility of satellite and drone imagery, as well as remote sensing data, such as drones, has enabled the efficient utilization and training of deep learning algorithms. These algorithms can accurately identify, categorize, and partition flood areas in real-time. By integrating artificial intelligence (Al)-powered flood detection algorithms with additional data sources, such as meteorological forecasts and ground-based sensors, it is possible to create robust flood monitoring systems. These systems can offer timely alerts for potential flood events and enable efficient emergency response measures. The paper outlines advanced functionalities and technologies that will be available by integrating the Internet of Things (IoT) and Artificial Intelligence (AI) for flood monitoring. The paper provides a comprehensive overview of AI-IoT visions, services, applications, and the networking infrastructure involved. Additionally, it includes a vast assortment of satellite images. © 2024 IEEE.
Author Keywords	Artificial intelligence; Disaster Management; Drones Imageries; Emergency Management; Flood risk assessment; Safety and Security

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