Detection of river flow slow-down through sensing system and quasi-real time imaging

Flow slow-down in rivers and artificial canals is a basic aspect to be monitored and kept strictly under control. Flow slow-downs can become a major concern in the event of extreme phenomena. The paper illustrates an advanced image processing method that uses particle tracking velocimetry in conjunction with a monadic approach to better characterize water flow in the presence of waste or debris that block normal water flow within a river. An high-speed camera installed beneath a bridge takes periodic images of the water flow. The measured water level and the images taken by the camera are sent to a central system in real-time. Results demonstrate the capability of the proposed method to accurately detect the presence of debris from the measured water flow