Research graph
References from Artificial intelligence and big data application for drinking water quality monitoring. Local targets link to admitted publications; unresolved targets remain external evidence.
Drinking water resources suitability assessment based on pollution index of groundwater using improved explainable artificial intelligence
10.3390/su152115655 · 2023 · External reference
Low-cost internet-of-things water-quality monitoring system for rural areas
10.3390/s23083919 · 2023 · External reference
Urban river water quality monitoring based on self-optimizing machine learning method using multi-source remote sensing data
10.1016/j.ecolind.2022.109750 · 2023 · External reference
Applications of artificial intelligence (AI) in drinking water treatment processes: Possibilities
10.1016/j.chemosphere.2024.141958 · 2024 · External reference
A novel approach for water quality classification based on the integration of deep learning and feature extraction techniques
10.1016/j.chemolab.2021.104329 · 2021 · External reference
Chemical assessment of drinking water quality and associated human health risk of heavy metals in Gutai Mountains, Romania
10.3390/toxics12030168 · 2024 · External reference
Real-time anomaly detection for water quality sensor monitoring based on multivariate deep learning technique
10.3390/s23208613 · 2023 · External reference
Development of a proof-of-concept microfluidic portable pathogen analysis system for water quality monitoring
10.1016/j.scitotenv.2021.152556 · 2022 · External reference
Modelling and prediction of water quality by using artificial intelligence
10.3390/su13084259 · 2021 · External reference
Recent advancements in electrochemical biosensors for monitoring the water quality
10.3390/bios12070551 · 2022 · External reference
A hybrid machine learning and embedded IoT-based water quality monitoring system
10.1016/j.iot.2023.100774 · 2023 · External reference
Development of LoRaWAN-based IoT system for water quality monitoring in rural areas
10.1016/j.eswa.2023.122862 · 2024 · External reference
IoT-based solutions to monitor water level, leakage, and motor control for smart water tanks
10.3390/w14030309 · 2022 · External reference
The latest innovative avenues for the utilization of artificial Intelligence and big data analytics in water resource management
10.1016/j.rineng.2023.101566 · 2023 · External reference
Using machine learning models for predicting the water quality index in the La Buong River, Vietnam
10.3390/w14101552 · 2022 · External reference
10.3390/electronics11131927
10.3390/electronics11131927 · External reference
Predicting optical water quality indicators from remote sensing using machine learning algorithms in tropical highlands of Ethiopia
10.3390/hydrology10050110 · 2023 · External reference
Water quality classification using machine learning algorithms
10.1016/j.jwpe.2022.102920 · 2022 · External reference
Determination of key parameters in water quality monitoring of the most sediment-laden Yellow River based on water quality index
10.1016/j.psep.2022.05.067 · 2022 · External reference
Perspectives of heavy metal pollution indices for soil, sediment, and water pollution evaluation: An insight
10.1016/j.totert.2023.100039 · 2023 · External reference
Artificial intelligence for surface water quality evaluation, monitoring and assessment
10.3390/w15223919 · 2023 · External reference
Real-time monitoring and prediction of water quality parameters and algae concentrations using microbial potentiometric sensor signals and machine learning tools
10.1016/j.scitotenv.2020.142876 · 2021 · External reference
Water quality prediction using machine learning models based on grid search method
10.1007/s11042-023-16737-4 · 2024 · External reference
IoT-enabled effective real-time water quality monitoring method for aquaculture
10.1016/j.mex.2024.102906 · 2024 · External reference
Smart water quality monitoring with iot wireless sensor networks
10.3390/s24092871 · 2024 · External reference
Data-driven models for predicting microbial water quality in the drinking water source using E. coli monitoring and hydrometeorological data
10.1016/j.scitotenv.2021.149798 · 2022 · External reference
Remote sensing retrieval of inland water quality parameters using Sentinel-2 and multiple machine learning algorithms
10.1007/s11356-022-23431-9 · 2023 · External reference
Application of digital PCR for public health-related water quality monitoring
10.1016/j.scitotenv.2022.155663 · 2022 · External reference
Robust machine learning algorithms for predicting coastal water quality index
10.1016/j.jenvman.2022.115923 · 2022 · External reference
Performance analysis of the water quality index model for predicting water state using machine learning techniques
10.1016/j.psep.2022.11.073 · 2023 · External reference
An IoT real-time potable water quality monitoring and prediction model based on cloud computing architecture
10.3390/s24041180 · 2024 · External reference
Water quality prediction using machine learning models based on grid search method
10.1007/s11042-023-16737-4 · ExternalCitation · doi-reference
Remote sensing retrieval of inland water quality parameters using Sentinel-2 and multiple machine learning algorithms
10.1007/s11356-022-23431-9 · ExternalCitation · doi-reference
A novel approach for water quality classification based on the integration of deep learning and feature extraction techniques
10.1016/j.chemolab.2021.104329 · ExternalCitation · doi-reference
Applications of artificial intelligence (AI) in drinking water treatment processes: Possibilities
10.1016/j.chemosphere.2024.141958 · ExternalCitation · doi-reference
Urban river water quality monitoring based on self-optimizing machine learning method using multi-source remote sensing data
10.1016/j.ecolind.2022.109750 · ExternalCitation · doi-reference
Development of LoRaWAN-based IoT system for water quality monitoring in rural areas
10.1016/j.eswa.2023.122862 · ExternalCitation · doi-reference
A hybrid machine learning and embedded IoT-based water quality monitoring system
10.1016/j.iot.2023.100774 · ExternalCitation · doi-reference
Robust machine learning algorithms for predicting coastal water quality index
10.1016/j.jenvman.2022.115923 · ExternalCitation · doi-reference
Water quality classification using machine learning algorithms
10.1016/j.jwpe.2022.102920 · ExternalCitation · doi-reference
IoT-enabled effective real-time water quality monitoring method for aquaculture
10.1016/j.mex.2024.102906 · ExternalCitation · doi-reference
Determination of key parameters in water quality monitoring of the most sediment-laden Yellow River based on water quality index
10.1016/j.psep.2022.05.067 · ExternalCitation · doi-reference
Performance analysis of the water quality index model for predicting water state using machine learning techniques
10.1016/j.psep.2022.11.073 · ExternalCitation · doi-reference
The latest innovative avenues for the utilization of artificial Intelligence and big data analytics in water resource management
10.1016/j.rineng.2023.101566 · ExternalCitation · doi-reference
Real-time monitoring and prediction of water quality parameters and algae concentrations using microbial potentiometric sensor signals and machine learning tools
10.1016/j.scitotenv.2020.142876 · ExternalCitation · doi-reference
Data-driven models for predicting microbial water quality in the drinking water source using E. coli monitoring and hydrometeorological data
10.1016/j.scitotenv.2021.149798 · ExternalCitation · doi-reference
Development of a proof-of-concept microfluidic portable pathogen analysis system for water quality monitoring
10.1016/j.scitotenv.2021.152556 · ExternalCitation · doi-reference
Application of digital PCR for public health-related water quality monitoring
10.1016/j.scitotenv.2022.155663 · ExternalCitation · doi-reference
Perspectives of heavy metal pollution indices for soil, sediment, and water pollution evaluation: An insight
10.1016/j.totert.2023.100039 · ExternalCitation · doi-reference
Recent advancements in electrochemical biosensors for monitoring the water quality
10.3390/bios12070551 · ExternalCitation · doi-reference
10.3390/electronics11131927
10.3390/electronics11131927 · ExternalCitation · doi-reference
Predicting optical water quality indicators from remote sensing using machine learning algorithms in tropical highlands of Ethiopia
10.3390/hydrology10050110 · ExternalCitation · doi-reference
Low-cost internet-of-things water-quality monitoring system for rural areas
10.3390/s23083919 · ExternalCitation · doi-reference
Real-time anomaly detection for water quality sensor monitoring based on multivariate deep learning technique
10.3390/s23208613 · ExternalCitation · doi-reference
An IoT real-time potable water quality monitoring and prediction model based on cloud computing architecture
10.3390/s24041180 · ExternalCitation · doi-reference
Smart water quality monitoring with iot wireless sensor networks
10.3390/s24092871 · ExternalCitation · doi-reference
Modelling and prediction of water quality by using artificial intelligence
10.3390/su13084259 · ExternalCitation · doi-reference
Drinking water resources suitability assessment based on pollution index of groundwater using improved explainable artificial intelligence
10.3390/su152115655 · ExternalCitation · doi-reference
Chemical assessment of drinking water quality and associated human health risk of heavy metals in Gutai Mountains, Romania
10.3390/toxics12030168 · ExternalCitation · doi-reference
IoT-based solutions to monitor water level, leakage, and motor control for smart water tanks
10.3390/w14030309 · ExternalCitation · doi-reference
Using machine learning models for predicting the water quality index in the La Buong River, Vietnam
10.3390/w14101552 · ExternalCitation · doi-reference
Artificial intelligence for surface water quality evaluation, monitoring and assessment
10.3390/w15223919 · ExternalCitation · doi-reference
