Dam Hazard Prediction Using an AIoT Based System - Nabila Aissani; Abderraouf Messai; Salheddine Sadouni (Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 2026)
Dams are a very important infrastructure because they are one of the main water and electricity supplies for most countries; However, it is susceptible to demolition due to several factors such as aging and floods. This not only causes damage to water supplies and economical loss, but also human lives. And with the current climate change and global warming, heavy rainfalls and storms leading to floods are rapid and abrupt; existing studies tend to focus on one aspect rather than a total security system. Which drives us to look for the answer to the most important question; How can we deploy a system that is capable predicting coming floods and estimating the impact giving us enough time for a reaction? Hence, in this paper, we propose an Artificial intelligence of things based system to predict potential floods in dams by overtopping and potential breaching, their time, and estimated threatened distance. This system includes mainly 1) several types of sensors like temperature, humidity, and water level 2) AI models like one class support vector machine, isolation forest, hybrid models, and regression models. The results were promising for improving dam security.