Monitoring water quality parameters in aquaculture using edge computing

In this paper, we study an integration of temperature and pH sensors into the system to collect and monitor water quality parameters in aquaculture using a combination of edge computing (EC), Artificial Intelligence (AI) and Internet-of-Things (IoT). We develop and deploy a model using edge computing and a Long-Short Term Memory (LSTM) algorithm to forecast the aquaculture water quality at the network's edge.