A Vision-Based Solution for Water Level Monitoring in Flash Floods Scenario

Flash floods represent a serious problem, especially in urban areas, due to the consequences of sediment transport and other phenomena affecting security and life quality of citizens. The availability of low-cost solutions for the real-time monitoring of such phenomena, with particular regards to the water level in urban areas, is of main interest for the realization of early warning systems aimed to predict and handle hazardous events. In this paper a water level monitoring system, based on a low-cost vision system and a dedicated signal processing implemented on an embedded hardware platform, is presented. Main advantage of the proposed approach resides in the adopted sensing methodology, which besides being low-cost, allows for a robust estimation of the water level, without the need for active (powered) ground devices. A proof-of-concept aimed prototype has been realized and its performances have been assessed by means of a dedicated experimental survey. Obtained results highlight high sensitivity and specificity in the water level recognition, with an accuracy close to 100% over the whole explored detection range.