Applications of IoT and Artificial Intelligence in Water Quality Monitoring and Prediction: A Review

A Review of Hybrid Soft Computing and Data Pre-Processing Techniques to Forecast Freshwater Quality’s Parameters: Current Trends and Future Directions

“…A review of ANN techniques for environmental issues prediction [17] AI, ANFIS, ANN, river, water quality. AI for surface water quality monitoring and assessment: a systematic literature analysis [18] Pollutant, sediment load, ML tool, ANN, discharge prediction…”

“…Water quality prospective in Twenty First Century: Status of water quality in major river basins, contemporary strategies and impediments: A review Additionally, several other review papers have introduced the applications of the soft computer to forecast WQ [5,15,[17][18][19][20][21], whose keywords and crucial aspects are summarised in Table 1.…”

“…Ighalo et al [17] reviewed papers on neural networks, WQ parameters, location of study, and model accuracy. Mustafa et al [18] gave an overview of the internet of things (IoT) in WQ monitoring. Furthermore, their study briefly explained an ANN model with its advantages, limitations, and its recent application.…”

“…In addition, because no consistent principles control proper ANN model development and construction, it is not easy to prioritise a suitable model. [18,41,42] ANFIS It can be used when the system input data is confusing and imprecise. It can manage non-linear data series and allow the modelling process to have the least possible uncertainty level.…”

“…The increasing trend in applying hybrid ML methods can be seen in recent years, as revealed in Figure 1. Additionally, several other review papers have introduced the applications of the soft computer to forecast WQ [5,15,[17][18][19][20][21], whose keywords and crucial aspects are summarised in Table 1.…”