Analysis of Water Quality Monitoring Data Based on LSTM

Abstract

Water quality is a very important topic for lives. Nowadays, the intelligent science and technology is developing rapidly, and Internet of Things (IoT) plays a more prominent role in many fields. In this paper, we use IoT and intelligent technology to solve the problem of water quality analysis. With IoT linked with water quality monitoring, w1e first collect the data related to domestic water quality and prepare them for analysis. Then by selecting PH, DO, COD, NH3-H standards as the basis, and using LSTM algorithm to carry out digression and simulation, we build a training model for water quality prediction. The predicted values possibly mark the sudden upcoming of pollutions, which reminds the inspectors of attentions and preventions. As a result, it can ensure the safety of domestic water.