Survey on DL Methods for Flood Prediction in Smart Cities

Abstract

The government has focused to maintain the needs of the populace's health and hygienic standards; numerous initiatives are involved, such as flood forecasting, water management, and sewage management. To prevent damage throughout the city, flood prediction must be done early on. “Smart” refers to artificial intelligence or machine learning methods, either directly or indirectly. To comprehend the general pattern and depth of the rainfall and to forecast the occurrence of floods, artificial intelligence techniques like deep learning are applied. To extract key properties for forecasting heavy rains and floods, many deep learning approaches, including CNN and deep belief networks, are applied. As a result, there is less harm done to both city infrastructure and human life. The study done on flood forecasting utilizing AI, ML, and deep learning techniques will be covered in this chapter. This review research will provide a thorough analysis based on the many types of deep learning models, the input datatypes for forecasting, the model effectiveness, real-time application, etc.