A long-range, low-cost technique to measure water level variations over limnimeters on hydraulic weir using machine vision and IoT

Abstract

It is neither practical nor economical to make continuous and direct measurements of the water flow in a stream, so indirect methods must be used to measure the water level and, based on a calibration curve, relate it to the corresponding flow rate. A hydraulic weir with a limnimeter fulfills this purpose, but its disadvantage is that it does not allow the automated registration of the water level and therefore new and more efficient technologies must be used to perform this measurement automatically and thus have a lower waste and optimization of the resource. This experiment develops an algorithm based on computer vision and the inclusion of the concepts of the Internet of Things, in order to measure and record the values of the water level in a hydraulic dam, also includes energy storage system, power supply, remote computer, devices with wireless communication and IoT platform that allow a measurement error of less than ± 2% to be obtained with respect to a visual measurement made by the operator.