Research graph
References from Smart sensors for water testing and quality assessment. Local targets link to admitted publications; unresolved targets remain external evidence.
Mobile edge computing: A survey
10.1109/jiot.2017.2750180 · 2017 · External reference
Machine learning methods for better water quality prediction
2019 · External reference
An architecture of IoT service delegation and resource allocation based on collaboration between fog and cloud computing
10.1155/2016/6123234 · 2016 · External reference
“River water quality index prediction and uncertainty analysis: A comparative study of machine learning models
10.1016/j.jece.2020.104599 · 2021 · External reference
Enhancement of groundwater resources quality prediction by machine learning models on the basis of an improved DRASTIC method
10.1038/s41598-024-78812-6 · 2024 · External reference
10.1109/icomitee.2019.8920900
10.1109/icomitee.2019.8920900 · External reference
“Multi-step tap-water quality forecasting in South Korea with transformer-based machine learning model
10.1080/1573062x.2024.2399644 · 2024 · External reference
10.1109/icdcs.2019.00023
10.1109/icdcs.2019.00023 · External reference
Enhancing wastewater treatment efficiency through machine learning-driven effluent quality prediction: A plant-level analysis
10.1016/j.jwpe.2023.104758 · 2024 · External reference
Unresolved reference
External reference
Analysis of ground water quality parameters: A review www.isca.me
2014 · External reference
10.1109/lcn.2004.38
10.1109/lcn.2004.38 · External reference
Prediction of irrigation water quality parameters using machine learning models in a semi-arid environment
10.1016/j.jssas.2020.08.001 · 2020 · External reference
“Wireless sensor network based solution for real-time water quality monitoring
10.21608/ejs.2018.148253 · 2018 · External reference
Predicting the Tigris river water quality within Baghdad, Iraq by using water quality index and regression analysis
10.1016/j.eti.2018.06.013 · 2018 · External reference
Development and evaluation of irrigation water quality guide using II.W.Q.G.V.1 software: A case study of Al-Gharraf Canal, Southern Iraq
10.1016/j.eti.2018.12.001 · 2019 · External reference
10.1088/1755-1315/191/1/012015
10.1088/1755-1315/191/1/012015 · External reference
10.1109/norchip.2014.7004716
10.1109/norchip.2014.7004716 · External reference
“Machine learning in natural and engineered water systems
10.1016/j.watres.2021.117666 · 2021 · External reference
Groundwater prediction using machine-learning tools
10.3390/a13110300 · 2020 · External reference
Internet of things for water quality monitoring and assessment: A comprehensive review
2021 · External reference
Machine learning methods for predicting tap-water quality time series in South Korea
10.3390/w14223766 · 2022 · External reference
Water treatment and artificial intelligence techniques: A systematic literature review
10.1007/s11356-021-16471-0 · 2021 · External reference
IoT-based smart water quality monitoring: Recent techniques, trends and challenges for domestic applications
10.3390/w13131729 · 2021 · External reference
Water quality assessment using water quality index and geographical information system methods in the coastal waters of Andaman Sea, India
10.1016/j.marpolbul.2015.08.032 · 2015 · External reference
A review and research agenda
2023 · External reference
Edge computing: A survey
10.1016/j.future.2019.02.050 · 2019 · External reference
10.1109/itmc.2018.8691271
10.1109/itmc.2018.8691271 · External reference
10.1016/j.ecoinf.2023.101991
10.1016/j.ecoinf.2023.101991 · External reference
Prediction of water quality index (WQI) using support vector machine (SVM) and least square-support vector machine (LS-SVM)
10.1080/15715124.2019.1628030 · 2021 · External reference
Application of edge computing and GIS in ecological water requirement prediction and optimal allocation of water resources in irrigation area
10.1371/journal.pone.0254547 · 2021 · External reference
A critical review of copper nanoclusters for monitoring of water quality
10.1016/j.snr.2021.100026 · 2021 · External reference
Effects of aquaponic system on fish locomotion by image-based YOLO v4 machine learning algorithm
10.1016/j.compag.2022.106785 · 2022 · External reference
A review of genesis and evolution of water quality index (WWQI and some future directions
10.1007/s12403-011-0040-0 · 2011 · External reference
“A survey on mobile edge computing: The communication perspective
10.1109/comst.2017.2745201 · 2017 · External reference
Prediction of purified water quality in industrial hydrocarbon wastewater treatment using an artificial neural network and response surface methodology
10.1016/j.jwpe.2023.104757 · 2024 · External reference
Evaluation and prediction of irrigation water quality of an agricultural district, SE nigeria: an integrated heuristic GIS-based and machine learning approach
10.1007/s11356-022-25119-6 · 2024 · External reference
Machine-learning based multi-objective optimization of helically coiled tube flocculators for water treatment
10.1016/j.cherd.2023.08.028 · 2023 · External reference
Machine learning framework for predicting water quality classification
10.2166/wpt.2024.259 · 2024 · External reference
10.1007/978-981-15-6707-0_30
10.1007/978-981-15-6707-0_30 · External reference
Water contaminants detection using sensor placement approach in smart water networks
2020 · External reference
“Intelligent edge-cloud framework for water quality monitoring in water distribution system
10.3390/w16020196 · 2024 · External reference
A multi-class classification system for continuous water quality monitoring
10.1016/j.heliyon.2019.e01822 · 2019 · External reference
Detection and prediction of HMS from drinking water by analysing the adsorbents from residuals using Machine learning
10.1155/2022/3265366 · 2022 · External reference
Assessment of carbon neutrality in waste water treatment systems through machine learning algorithm
10.2166/wrd.2023.154 · 2023 · External reference
Smart water conservation through a machine learning and blockchain-enabled decentralized edge computing network
10.1016/j.asoc.2021.107274 · 2021 · External reference
Assessment of groundwater quality of Pratapgarh district in India for suitability of drinking purpose using water quality index (WWQI and GGIStechnique
10.1007/s40899-017-0144-1 · 2018 · External reference
IoT-based smart aquaculture system with automatic aerating and water quality monitoring
2022 · External reference
A review of water quality index models and their use for assessing surface water quality
10.1016/j.ecolind.2020.107218 · 2021 · External reference
The role of big data analytics in industrial Internet of Things
10.1016/j.future.2019.04.020 · 2019 · External reference
“Applications of machine learning in water quality management: A state-of-the-art review
10.1016/j.jhydrol.2022.128332 · 2022 · External reference
“A survey on mobile edge networks: Convergence of computing, caching and communications
10.1109/access.2017.2685434 · 2017 · External reference
Evaluation of water quality based on a machine learning algorithm and water quality index for the Ebinur Lake Watershed, China
2017 · External reference
Unresolved reference
External reference
“Quality assessment and prediction of municipal drinking water using water quality index and artificial neural network: A case study of Wuhan, central China, from 2013 to 2019
10.1016/j.scitotenv.2022.157096 · 2022 · External reference
A predictive model of recreational water quality based on adaptive synthetic sampling algorithms and machine learning
10.1016/j.watres.2020.115788 · 2020 · External reference
Real-time detection of potable-reclaimed water pipe cross-connection events by conventional water quality sensors using machine learning methods
10.1016/j.jenvman.2019.02.110 · 2019 · External reference
Estimating the water quality index based on interpretable machine learning models
10.2166/wst.2024.068 · 2024 · External reference
“A survey on the edge computing for the Internet of Things
10.1109/access.2017.2778504 · 2017 · External reference
Prediction of water quality based on artificial neural network with grey theory
2019 · External reference
Retrieval of water quality parameters from hyperspectral images using a hybrid feedback machine factorization machine model
10.1016/j.watres.2021.117618 · 2021 · External reference
Privacy-preserved data sharing towards multiple parties in industrial IoTs
10.1109/jsac.2020.2980802 · 2020 · External reference
Water quality prediction of MBR based on machine learning: A novel dataset contribution analysis method
10.1016/j.jwpe.2022.103296 · 2022 · External reference
10.1007/978-981-15-6707-0_30
10.1007/978-981-15-6707-0_30 · ExternalCitation · doi-reference
Water treatment and artificial intelligence techniques: A systematic literature review
10.1007/s11356-021-16471-0 · ExternalCitation · doi-reference
Evaluation and prediction of irrigation water quality of an agricultural district, SE nigeria: an integrated heuristic GIS-based and machine learning approach
10.1007/s11356-022-25119-6 · ExternalCitation · doi-reference
A review of genesis and evolution of water quality index (WWQI and some future directions
10.1007/s12403-011-0040-0 · ExternalCitation · doi-reference
Assessment of groundwater quality of Pratapgarh district in India for suitability of drinking purpose using water quality index (WWQI and GGIStechnique
10.1007/s40899-017-0144-1 · ExternalCitation · doi-reference
Smart water conservation through a machine learning and blockchain-enabled decentralized edge computing network
10.1016/j.asoc.2021.107274 · ExternalCitation · doi-reference
Machine-learning based multi-objective optimization of helically coiled tube flocculators for water treatment
10.1016/j.cherd.2023.08.028 · ExternalCitation · doi-reference
Effects of aquaponic system on fish locomotion by image-based YOLO v4 machine learning algorithm
10.1016/j.compag.2022.106785 · ExternalCitation · doi-reference
10.1016/j.ecoinf.2023.101991
10.1016/j.ecoinf.2023.101991 · ExternalCitation · doi-reference
A review of water quality index models and their use for assessing surface water quality
10.1016/j.ecolind.2020.107218 · ExternalCitation · doi-reference
Predicting the Tigris river water quality within Baghdad, Iraq by using water quality index and regression analysis
10.1016/j.eti.2018.06.013 · ExternalCitation · doi-reference
Development and evaluation of irrigation water quality guide using II.W.Q.G.V.1 software: A case study of Al-Gharraf Canal, Southern Iraq
10.1016/j.eti.2018.12.001 · ExternalCitation · doi-reference
Edge computing: A survey
10.1016/j.future.2019.02.050 · ExternalCitation · doi-reference
The role of big data analytics in industrial Internet of Things
10.1016/j.future.2019.04.020 · ExternalCitation · doi-reference
A multi-class classification system for continuous water quality monitoring
10.1016/j.heliyon.2019.e01822 · ExternalCitation · doi-reference
“River water quality index prediction and uncertainty analysis: A comparative study of machine learning models
10.1016/j.jece.2020.104599 · ExternalCitation · doi-reference
Real-time detection of potable-reclaimed water pipe cross-connection events by conventional water quality sensors using machine learning methods
10.1016/j.jenvman.2019.02.110 · ExternalCitation · doi-reference
“Applications of machine learning in water quality management: A state-of-the-art review
10.1016/j.jhydrol.2022.128332 · ExternalCitation · doi-reference
Prediction of irrigation water quality parameters using machine learning models in a semi-arid environment
10.1016/j.jssas.2020.08.001 · ExternalCitation · doi-reference
Water quality prediction of MBR based on machine learning: A novel dataset contribution analysis method
10.1016/j.jwpe.2022.103296 · ExternalCitation · doi-reference
Prediction of purified water quality in industrial hydrocarbon wastewater treatment using an artificial neural network and response surface methodology
10.1016/j.jwpe.2023.104757 · ExternalCitation · doi-reference
Enhancing wastewater treatment efficiency through machine learning-driven effluent quality prediction: A plant-level analysis
10.1016/j.jwpe.2023.104758 · ExternalCitation · doi-reference
Water quality assessment using water quality index and geographical information system methods in the coastal waters of Andaman Sea, India
10.1016/j.marpolbul.2015.08.032 · ExternalCitation · doi-reference
“Quality assessment and prediction of municipal drinking water using water quality index and artificial neural network: A case study of Wuhan, central China, from 2013 to 2019
10.1016/j.scitotenv.2022.157096 · ExternalCitation · doi-reference
A critical review of copper nanoclusters for monitoring of water quality
10.1016/j.snr.2021.100026 · ExternalCitation · doi-reference
A predictive model of recreational water quality based on adaptive synthetic sampling algorithms and machine learning
10.1016/j.watres.2020.115788 · ExternalCitation · doi-reference
Retrieval of water quality parameters from hyperspectral images using a hybrid feedback machine factorization machine model
10.1016/j.watres.2021.117618 · ExternalCitation · doi-reference
“Machine learning in natural and engineered water systems
10.1016/j.watres.2021.117666 · ExternalCitation · doi-reference
Enhancement of groundwater resources quality prediction by machine learning models on the basis of an improved DRASTIC method
10.1038/s41598-024-78812-6 · ExternalCitation · doi-reference
Prediction of water quality index (WQI) using support vector machine (SVM) and least square-support vector machine (LS-SVM)
10.1080/15715124.2019.1628030 · ExternalCitation · doi-reference
“Multi-step tap-water quality forecasting in South Korea with transformer-based machine learning model
10.1080/1573062x.2024.2399644 · ExternalCitation · doi-reference
10.1088/1755-1315/191/1/012015
10.1088/1755-1315/191/1/012015 · ExternalCitation · doi-reference
“A survey on mobile edge networks: Convergence of computing, caching and communications
10.1109/access.2017.2685434 · ExternalCitation · doi-reference
“A survey on the edge computing for the Internet of Things
10.1109/access.2017.2778504 · ExternalCitation · doi-reference
“A survey on mobile edge computing: The communication perspective
10.1109/comst.2017.2745201 · ExternalCitation · doi-reference
10.1109/icdcs.2019.00023
10.1109/icdcs.2019.00023 · ExternalCitation · doi-reference
10.1109/icomitee.2019.8920900
10.1109/icomitee.2019.8920900 · ExternalCitation · doi-reference
10.1109/itmc.2018.8691271
10.1109/itmc.2018.8691271 · ExternalCitation · doi-reference
Mobile edge computing: A survey
10.1109/jiot.2017.2750180 · ExternalCitation · doi-reference
Privacy-preserved data sharing towards multiple parties in industrial IoTs
10.1109/jsac.2020.2980802 · ExternalCitation · doi-reference
10.1109/lcn.2004.38
10.1109/lcn.2004.38 · ExternalCitation · doi-reference
10.1109/norchip.2014.7004716
10.1109/norchip.2014.7004716 · ExternalCitation · doi-reference
An architecture of IoT service delegation and resource allocation based on collaboration between fog and cloud computing
10.1155/2016/6123234 · ExternalCitation · doi-reference
Detection and prediction of HMS from drinking water by analysing the adsorbents from residuals using Machine learning
10.1155/2022/3265366 · ExternalCitation · doi-reference
Application of edge computing and GIS in ecological water requirement prediction and optimal allocation of water resources in irrigation area
10.1371/journal.pone.0254547 · ExternalCitation · doi-reference
“Wireless sensor network based solution for real-time water quality monitoring
10.21608/ejs.2018.148253 · ExternalCitation · doi-reference
Machine learning framework for predicting water quality classification
10.2166/wpt.2024.259 · ExternalCitation · doi-reference
Assessment of carbon neutrality in waste water treatment systems through machine learning algorithm
10.2166/wrd.2023.154 · ExternalCitation · doi-reference
Estimating the water quality index based on interpretable machine learning models
10.2166/wst.2024.068 · ExternalCitation · doi-reference
Groundwater prediction using machine-learning tools
10.3390/a13110300 · ExternalCitation · doi-reference
IoT-based smart water quality monitoring: Recent techniques, trends and challenges for domestic applications
10.3390/w13131729 · ExternalCitation · doi-reference
Machine learning methods for predicting tap-water quality time series in South Korea
10.3390/w14223766 · ExternalCitation · doi-reference
“Intelligent edge-cloud framework for water quality monitoring in water distribution system
10.3390/w16020196 · ExternalCitation · doi-reference
