Prototype Design and Development of IoT and Machine Learning Based Flood Monitoring, Alerting and Forecasting System

Abstract

Floods are among the most common natural disasters worldwide, affecting every aspect of society. In recent years, research has focused on developing models to predict floods. Few models have proposed an integration of alert aid mechanisms for risk mitigation, policy recommendations, and reducing fatalities and property damage caused by floods. However, predicting and mitigating floods is complex, requiring thorough research on the contributing factors. This research work has designed and developed an Internet of Things based flood status evaluation prototype with alert mechanism along with using a prediction model to predict floods using machine learning so that the authorities could take necessary steps to avoid the damage due to flood and do necessary managements. The machine learning algorithm streamlines the data collection and data process. The implementation results show that the objectives are well accomplished, and the proposed model effectively completes data collection and prediction tasks.