Image Processing Based Water Quality Monitoring System for Biofloc Fish Farming

In this paper water quality parameters are measured utilizing low-cost sensors and a unique sensing system based on Image processing to detect several numbers of parameters without the usage of expensive sensors. Low-cost sensors are utilized to monitor temperature, humidity and pH while image processing techniques are applied to quantify dissolved oxygen and ammonia levels in the water. Both the outputs of the sensors and sensing system are transferred to the cloud for real-time monitoring. Moreover, a warning email is sent to the user when any of the parameters exceeds the threshold value. The proposed system makes it possible to minimize the costs and usage of multiple sensors which will be extremely advantageous for monitoring the water quality of fish rearing within confined spaces.