Design and development of low cost smart turbidity sensor for water quality monitoring in fish farms

Turbidity monitoring is necessary in many cases and several sensors have been developed for this purpose. However, in some cases to quantify the turbidity it is not enough and its characterization is necessary. In fish farms, the increase of sedimentary or phytoplanktonic turbidity requires different actions to prevent further damages. For this reason, a sensor able to differentiate between turbidity sources is necessary. In this paper, a turbidity sensor able to distinguish different types of turbidity is designed, developed and calibrated. The sensor is based on the Beer-Lambert law and it uses four LEDs as light sources with different wavelengths. The sensing elements are located at 180° of the light sources and consist of a photodiode and a photoresistor, sensitive to infrared and visible wavelengths respectively. For the calibration process different turbidity sources were employed, Isochrysis galbana, Tetraselmis chuii and sediment. The results show that it is possible to determine the turbidity using the infrared light and to characterize the origin of that turbidity with the red light. An algorithm was created in order to create a method to process the data from each sample to obtain the turbidity, the origin of this turbidity and the concentration of the turbidity source. With this algorithm, we can create a smart turbidity sensor for water quality monitoring. Our main application is focused on monitoring the water input in fish farm facilities; however, this smart sensor will be useful in many other areas.