Deploying Artificial Intelligence for Optimized Flood Forecasting and Mitigation

The urgent need to develop strategies for predicting and managing flooding disasters has become increasingly important due to the rising frequency and severity of such events largely attributed to the effects of climate change. Artificial intelligence presents an approach to effectively tackle this pressing issue. This study thoroughly examines how artificial intelligence techniques are being used in flood forecasting and control. It explores the utilization of data sources like satellite imagery and Internet of Things (IoT) sensors to enhance the accuracy of AI based predictions. However like any advancement utilizing artificial intelligence in this field comes with its own unique set of challenges. The aim of this research is to investigate concerns that require attention in the realm of AI powered flood management. These challenges encompass aspects such as ensuring data integrity across geographical regions, efficiently handling the computational requirements of deep learning models and addressing issues related to fair distribution of AI powered flood control technologies. By examining methodologies employed in this domain along with their associated challenges, this paper seeks to provide an understanding of how artificial intelligence profoundly influences the future direction of flood prediction and control.