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Statistical monitoring of a wastewater treatment plant: A case study
2018
Journal of Environmental Management
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This paper presents a flexible and efficient fault detection approach based on unsupervised deep learning to monitor the operating conditions of WWTPs. ...
The efficient operation of wastewater treatment plants (WWTPs) is key to ensuring a sustainable and friendly green environment. ...
We are grateful to the three referees, the Associate Editor, and the Editor-in-Chief for their comments. ...
doi:10.1016/j.jenvman.2018.06.087
pmid:29986328
fatcat:innw4guq3be6ncyr4e5gzjtdke
Monitoring influent conditions of wastewater treatment plants by nonlinear data-based techniques
2019
IEEE Access
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To operate wastewater treatment plants (WWTPs) with optimized efficiency, influent conditions (ICs) as initial states of inflow fed to WWTPs were monitored to identify potential anomalies that would trigger ...
This research proposed kernel machine learning models, the kernel principal components analysis based one-class support vector machine (KPCA-OCSVM) with various kernels, to learn anomaly-free training ...
Wastewater treatment plants (WWTPs) are environmental systems where physical, chemical, and biological unit processes are convoluted [1] . ...
doi:10.1109/access.2019.2933616
fatcat:if4wy3tlevcavbfm72psiu4654
Data-Driven Drift Detection in Real Process Tanks: Bridging the Gap between Academia and Practice
2022
Water
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Sensor drift in Wastewater Treatment Plants (WWTPs) reduces the efficiency of the plants and needs to be handled. Several studies have investigated anomaly detection and fault detection in WWTPs. ...
The challenges related to data quality raise the question of whether the data-driven approach for drift detection is the best solution, as this requires a high-quality data set. ...
Acknowledgments: The authors wish to thank Lars Lading from EnviDan A/S for his assistance with accessing data and supervision. ...
doi:10.3390/w14060926
fatcat:e7bfmjypsrefxj2y6l5mtddruy
Monitoring Influent Measurements at Water Resource Recovery Facility Using Data-Driven Soft Sensor Approach
2019
IEEE Sensors Journal
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Moreover, the radial visualization plot is innovatively employed for fault analysis and diagnosis in combination with PCA and delineated interpretable visualization of anomalies and detector performances ...
In this paper, we introduced a flexible and reliable monitoring soft sensor approach to detect and identify abnormal influent measurements of WRRFs to enhance their efficiency and safety. ...
This plant is an advanced facility with a daily treatment capacity of 9500 m 3 . ...
doi:10.1109/jsen.2018.2875954
fatcat:3x6v2uqqkbg5boohw7lqerl2ie
A behavioral-based forensic investigation approach for analyzing attacks on water plants using GANs
2021
Forensic Science International: Digital Investigation
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Motivated by this, this paper proposes an unsupervised data-driven approach to support cyber forensics in such unique setups. ...
Empirical evaluations using data collected in a testbed representing a small-scale water treatment plant uncovered 32 out of the 36 cyber incidents; exceeding the performance of state-of-the-art. ...
Acknowledgements The authors would like to express their sincere gratitude to the anonymous reviewers and PC members for their constructive feedback. ...
doi:10.1016/j.fsidi.2021.301198
fatcat:ynuoaenwpvayhlbwm6fb3llomu
Computational Surveillance of Microbial Water Quality With Online Flow Cytometry
2020
Frontiers in Water
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However, the vast majority of current cytometric fingerprinting tools use offline statistical computations which cannot detect anomalies immediately. ...
presence of microbial anomalies. ...
We also thank François Murdter from the wastewater treatment plant of Lausanne, CH (STEP de Vidy) for providing water samples of the treatment process. ...
doi:10.3389/frwa.2020.586969
fatcat:s7ptudmtizfnhmljs7mfdw2cwm
Identifying and Estimating the Location of Sources of Industrial Pollution in the Sewage Network
2021
Sensors
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of wastewater treatment plants. ...
Both of the models are trained using simulated electrical conductivity and pH measurements of wastewater in sewers of a european city sub-catchment area. ...
We would also like to thank Steffen Krause and Christoph Wöllgens from the H2020 SYSTEM project for providing the input simulation data of the wastewater network used in the Results section. ...
doi:10.3390/s21103426
pmid:34069087
fatcat:vwrlhmayjbaurkkchx3qtohf2q
Using Real-Time Data and Unsupervised Machine Learning Techniques to Study Large-Scale Spatio–Temporal Characteristics of Wastewater Discharges and their Influence on Surface Water Quality in the Yangtze River Basin
2019
Water
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In this study, real-time monitoring data for chemical oxygen demand (COD), ammonia nitrogen (NH3-N), pH, and dissolved oxygen in the wastewater discharged from 2213 factories and in the surface water at ...
Because of a lack of data and few methods, the relationships between pollutants discharged in wastewater and those in surface water have not been fully revealed and unsupervised machine learning techniques ...
Acknowledgments: The authors are grateful for the useful and meaningful suggestions from the editors and reviewers of Water.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/w11061268
fatcat:l4crbg77tjcdtg5pwevozq4k6q
Intelligent System for the Predictive Analysis of an Industrial Wastewater Treatment Process
2020
Sustainability
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the wastewater treatment plant (WWTP). ...
Considering the exponential growth of today's industry and the wastewater results of its processes, it needs to have an optimal treatment system for such effluent waters to mitigate the environmental impact ...
Reference [18] implemented data-driven unsupervised anomaly detection approaches based on deep learning methods and clustering algorithms. ...
doi:10.3390/su12166348
fatcat:mb7wps5qn5hpzpu4xz2hqpriui
IoT Based Real-Time Monitoring of Phytoremediation of Wastewater using the Mathematical Model Implemented on the Embedded Systems
2021
International Journal of Intelligent Engineering and Systems
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Phytoremediation is a technique to remove pollutants from the wastewater using the plants. ...
This paper presents the Internet of things (IoT) technology for real-time monitoring of wastewater phytoremediation. ...
An unsupervised machine learning that integrates a deep belief network and a support vector machine was used in [28] for an anomaly-detection of decentralized WWTP. ...
doi:10.22266/ijies2021.0430.25
fatcat:soxxhlpu4bhhhbyy756lpgguc4
Detection of Anomalies and Faults in Industrial IoT Systems by Data Mining: Study of CHRIST Osmotron Water Purification System
[article]
2020
arXiv
pre-print
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In this paper, with the help of a few sensors and data mining approaches, an anomaly detection system is built for CHRIST Osmotron water purifier. ...
Given the data, we propose two anomaly detection approaches to build up our edge fault detection system. ...
Ali Naghi Mansubi, for their supports during this study. ...
arXiv:2009.03645v1
fatcat:3sesg6l32fehhltqpvxa6tn6pa
Mini Review: Metagenomics as a tool to monitor reclaimed water quality
2020
Applied and Environmental Microbiology
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Here, we reviewed metagenomic approaches (i.e., both sequencing platforms and bioinformatic tools) and studies that demonstrated their use for reclaimed water quality monitoring. ...
Conventional monitoring tools rely on cultivation and are not robust in addressing modern water quality concerns. ...
Using this approach, bacterial pathogens such as Bacillus anthracis, Klebsiella pneumoniae, and nontuberculous mycobacteria were detected in the effluent of a wastewater treatment plant (WWTP) that utilized ...
doi:10.1128/aem.00724-20
pmid:32503906
pmcid:PMC7414949
fatcat:hsmuqcqcn5aelfnpxr7rmymbai
An ensemble approach to the structure-function problem in microbial communities
[article]
2021
arXiv
pre-print
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Finally, we discuss what types of data analysis approaches might be lucrative for learning the structure-function mapping in communities from these data. ...
We survey the types of communities for which this approach might be best suited and then review the analytical techniques available for quantifying metabolite dynamics in communities. ...
These processes are key for wastewater treatment [18] and human health [19] . ...
arXiv:2111.06279v1
fatcat:pijztgqp2zgffm54szz7epztza
Sustainable Marine Ecosystems: Deep Learning for Water Quality Assessment and Forecasting
2021
IEEE Access
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Biosensors are not widely used in environment sensing, but have some potential regarding drinking water purification in water treatment plants for the detection of live organisms [39] . ...
Pollution can be localized, including discharge from a shore-based industrial wastewater treatment plant, a ship or other offshore structure (e.g., an oil platform), or coming from many diffuse sources ...
Sustainable Marine Ecosystems: Deep Learning for Water Quality Assessment and Forecasting EDUARD ANGELATS holds a M.Sc. in Telecommunications Engineering from Technical University of Catalonia (UPC) in ...
doi:10.1109/access.2021.3109216
fatcat:e4mubouhprcm3l2kanxjtrir54
A Method for Detecting Coffee Leaf Rust through Wireless Sensor Networks, Remote Sensing, and Deep Learning: Case Study of the Caturra Variety in Colombia
2020
Applied Sciences
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drone capable multispectral cameras), wireless sensor networks (multisensor approach), and Deep Learning (DL) techniques. ...
Failure to detect pathogens at an early stage can result in infestations that cause massive destruction of plantations and significantly damage the commercial value of the products. ...
Sierra, and Dentist Samuel Roldán for their support in the procurement of the coffee plants and the biological matter containing CLR. ...
doi:10.3390/app10020697
fatcat:77kxbhumfre2rgl7fllgz7al4q
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