Behavioural Response Analysis Using Vision Engineering (BRAVENet)

Abstract

A new engineering methodology is proposed to improve the automation process in monitoring the water quality in a small scale aquaculture system. Behavioural Response Analysis using Vision Engineering Network or BRAVENet is proposed, as a support system to a traditional sensor-based system, to monitor critical water quality parameters such as temperature, pH, salinity and dissolved oxygen. BRAVENet is based on the reactions or behavioural responses of tiger prawns to different water conditions. The performance of both the sensor-based system and BRAVENet are analysed and discussed. It is shown that the BRAVENet can identify unsafe levels of water parameters and is a good monitoring and prediction tool for water conditions especially those instances when industry grade sensors fail or become erroneous. Promising results show that BRAVENet can be used as a support system, if not as a replacement, in continuously monitoring the status of the critical water quality parameters of aquaculture systems.