An AI-Powered, Low-Cost IoT Node Oriented to Flood Early Warning Systems

Abstract

The present study aims to design a low-cost smart AI-powered node to serve as a flood Early Warning System with a complete solution. The node is designed to predict forthcoming flood events by capturing and combining critical data related to such phenomena. Such data are the water levels at rivers or other water discharge basins, rainfall, soil moisture, and material displacement at river slopes. The node will autonomously monitor the above quantities at a high frequency rate and selectively upload them to a server only when verified conditions for a forthcoming flood will exist. These conditions will be evaluated by the local ML model. This will allow each node to reliably predict flood events and issue local and remote alarms. The combination of several nodes at an area of interest will form a robust and reliable Early Warning System.

Keywords

• Early Warning Systems
• floods
• AI
• low cost
• IoT
• nodes