A Sensor-Based Smart Urban Flood Warning and Management System

Song, Sunyang; Deng, Xue; Gao, Chao

doi:10.1109/ispds58840.2023.10235462

2023 4th International Conference on Information Science, Parallel and Distributed Systems (ISPDS) 2023

DOI: 10.1109/ispds58840.2023.10235462

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A Sensor-Based Smart Urban Flood Warning and Management System

Sunyang Song,

Xue Deng,

Chao Gao

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2024

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Cited by 2 publications

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LSTM Model-Based Rapid Prediction Method of Urban Inundation with Rainfall Time Series

Pan,

Hou,

Gao

et al. 2024

Water Resour Manage

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LSTM Model-Based Rapid Prediction Method of Urban Inundation with Rainfall Time Series

Pan,

Hou,

Gao

et al. 2024

Water Resour Manage

View full text Add to dashboard Cite

Flood-Resilient Smart Cities: A Data-Driven Risk Assessment Approach Based on Geographical Risks and Emergency Response Infrastructure

Peixoto,

Costa,

Portugal

et al. 2024

Smart Cities

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Flooding in urban areas is expected to become even more common due to climatic changes, putting pressure on cities to implement effective response measures. Practical mechanisms for assessing flood risk have become highly desired, but existing solutions have been devoted to evaluating only specific cities and consider only limited risk perspectives, constraining their general applicability. This article presents an innovative approach for assessing the flood risk of delimited urban areas by exploiting geospatial information from publicly available databases, providing a method that is applicable to any city in the world and requiring minimum configurations. A set of mathematical equations is defined for numerically assessing risk levels based on elevation, slope, and proximity to rivers, while the existence of emergency-related urban infrastructure is considered as a risk reduction factor. Then, computed risk levels are used to classify areas, allowing easy visualisation of flood risk for a city. This smart city approach not only serves as a valuable tool for assessing the expected flood risk based on different parameters but also facilitates the implementation of cutting-edge strategies to effectively mitigate critical situations, ultimately enhancing urban resilience to flood-related disaster.

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A Sensor-Based Smart Urban Flood Warning and Management System

Cited by 2 publications

References 22 publications

LSTM Model-Based Rapid Prediction Method of Urban Inundation with Rainfall Time Series

LSTM Model-Based Rapid Prediction Method of Urban Inundation with Rainfall Time Series

Flood-Resilient Smart Cities: A Data-Driven Risk Assessment Approach Based on Geographical Risks and Emergency Response Infrastructure

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