Post flood management system based on smart IoT devices using AI approach

In recent years the losses due to urban floods are exponentially increasing. The major reasons for the floods are the poor drainage system and urbanization. There is a need for addressing the issues related to post floods, so in this work, we focus on creating a system for real-time post-flood management using Artificial intelligence (AI)-integrated Smart IoT devices. We selected Mumbai as the study city based on five years of rainfall and flood frequency. We split Mumbai into separate clusters based on population density, where we treated Santacruz and Colaba as two clusters. The AI model data is collected for the training and testing of the Artificial Neural Network (ANN) model for the Indian Metrological Department (IMD), Mumbai. We chose ANN here because the data to be evaluated is ambiguous and discreet; for this type of data, the choice must be made correctly. 80 percent of the data obtained is used for ANN model training and 20 percent for research. We discovered that this suggested model is better than the current outgoing flood control techniques. Decision-making and data processing have been automated so that casualties can be reduced and the stakeholders can conduct rescue operations better than the old methods of urban flood management