AQUASENSE: aquaculture water quality monitoring framework using autonomous sensors

Aquaculture is an important economic and food source in many countries. Due to environmental restrictions and the effects of aquatic diseases, aquaculture requires a lot of labor and expensive materials, and it relies on the expertise of aquaculture experts. The quality of water is essential for aquaculture development. Therefore, in this paper, a novel aquaculture water quality monitoring using autonomous sensors (AquaSense) has been proposed which uses autonomous sensors for efficient monitoring of water in the aquaculture environment. In the AquaSense framework, temperature, pH, dissolved oxygen, and salinity measurements are recorded and collected using a variety of autonomous sensors. Based on the information gathered, users can assess the condition of their farm through the Internet. The MATLAB R2012b platform is employed to verify the effectiveness of the suggested water quality (WQ) monitoring technique and analyze the data. Several criteria including accuracy, precision, recall, specificity, and f1-score have been used to assess the effectiveness of the suggested strategy. AquaSense achieves the high accuracy ranges of 96.98%, and existing techniques ISAS, AquaStat, and IoT-WQI FIS achieve 91.24%, 93.39%, and 88.92%, respectively.