A review on machine learning, artificial intelligence, and smart technology in water treatment and monitoring

M Lowe, R Qin, X Mao - Water, 2022‏ - mdpi.com
Artificial-intelligence methods and machine-learning models have demonstrated their ability
to optimize, model, and automate critical water-and wastewater-treatment applications …

Predicting water quality with artificial intelligence: a review of methods and applications

D Irwan, M Ali, AN Ahmed, G Jacky, A Nurhakim… - … Methods in Engineering, 2023‏ - Springer
The water is the main pivotal sources of irrigation in agricultural activities and affects human
daily activities such as drinking. The water quality has a significant impact on various …

Performance of machine learning methods in predicting water quality index based on irregular data set: application on Illizi region (Algerian southeast)

S Kouadri, A Elbeltagi, ARMT Islam, S Kateb - Applied Water Science, 2021‏ - Springer
Groundwater quality appraisal is one of the most crucial tasks to ensure safe drinking water
sources. Concurrently, a water quality index (WQI) requires some water quality parameters …

[HTML][HTML] Machine learning models for water quality prediction: a comprehensive analysis and uncertainty assessment in Mirpurkhas, Sindh, Pakistan

F Abbas, Z Cai, M Shoaib, J Iqbal, M Ismail, AF Alrefaei… - Water, 2024‏ - mdpi.com
Groundwater represents a pivotal asset in conserving natural water reservoirs for potable
consumption, irrigation, and diverse industrial uses. Nevertheless, human activities …

[HTML][HTML] AI-driven modelling approaches for predicting oxygen levels in aquatic environments

RB Singh, AI Olbert, A Samantra, MG Uddin - Journal of Water Process …, 2024‏ - Elsevier
Reliable water quality models are crucial for better water management and pollution control.
Biochemical oxygen demand (BOD) and dissolved oxygen (DO) are the widely recognized …

Applications of IoT and artificial intelligence in water quality monitoring and prediction: A review

HM Mustafa, A Mustapha, G Hayder… - 2021 6th international …, 2021‏ - ieeexplore.ieee.org
Currently, internet of things (IoT) devices like environmental sensors are used to capture real-
time data that can be viewed and interpreted via a visual format supported by a server …

Comparison of machine learning algorithms to predict dissolved oxygen in an urban stream

MM Bolick, CJ Post, MZ Naser… - Environmental Science and …, 2023‏ - Springer
Water quality monitoring for urban watersheds is critical to identify the negative urbanization
impacts. This study sought to identify a successful predictive machine learning model with …

Using hysteresis to predict the charge recombination properties of perovskite solar cells

J Wu, Y Li, Y Li, W **e, J Shi, D Li, S Cheng… - Journal of Materials …, 2021‏ - pubs.rsc.org
The mixed halide perovskites have become famous worldwide due to their rapid
development of power conversion efficiency (PCE) and unique photoelectric properties …

Prediction of total organic carbon and E. coli in rivers within the Milwaukee River basin using machine learning methods

N Nafsin, J Li - Environmental Science: Advances, 2023‏ - pubs.rsc.org
Urban water undergoes physical and chemical changes due to various contaminants from
point sources and non-point sources, including organic matter pollution and fecal bacterial …

The potential of big data and machine learning for ground water quality assessment and prediction

A Rajeev, R Shah, P Shah, M Shah… - Archives of Computational …, 2024‏ - Springer
Water, a priceless gift from nature, acts as Earth's matrix, medium, and life-sustaining
substance. While the planet is predominantly covered by water, only 3% is available as …