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Statistical monitoring of a wastewater treatment plant: A case study

Fouzi Harrou, Abdelkader Dairi, Ying Sun, Mohamed Senouci
2018 Journal of Environmental Management  
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

Tuoyuan Cheng, Abdelkader Dairi, Fouzi Harrou, Ying Sun, Tor Ove Leiknes
2019 IEEE Access  
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

Bolette D. Hansen, Thomas B. Hansen, Thomas B. Moeslund, David G. Jensen
2022 Water  
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

Tuoyuan Cheng, Fouzi Harrou, Ying Sun, TorOve Leiknes
2019 IEEE Sensors Journal  
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

Nataliia Neshenko, Elias Bou-Harb, Borko Furht
2021 Forensic Science International: Digital Investigation  
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

Marie C. Sadler, Jérémy Senouillet, Simon Kuenzi, Luigino Grasso, Douglas C. Watson
2020 Frontiers in Water  
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

Magdalena Paulina Buras, Fernando Solano Donado
2021 Sensors  
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

Zhenzhen Di, Miao Chang, Peikun Guo, Yang Li, Yin Chang
2019 Water  
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

Luis Arismendy, Carlos Cárdenas, Diego Gómez, Aymer Maturana, Ricardo Mejía, Christian G. Quintero M.
2020 Sustainability  
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

Evy Hendriarianti, National Institute of Technology Malang, Aryuanto Soetedjo, National Institute of Technology Malang
2021 International Journal of Intelligent Engineering and Systems  
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]

Mohammad Sadegh Sadeghi Garmaroodi, Faezeh Farivar, Mohammad Sayad Haghighi, Mahdi Aliyari Shoorehdeli, Alireza Jolfaei
2020 arXiv   pre-print
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

Pei-Ying Hong, David Mantilla-Calderon, Changzhi Wang
2020 Applied and Environmental Microbiology  
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]

Chandana Gopalakrishnappa, Karna Gowda, Kaumudi Prabhakara, Seppe Kuehn
2021 arXiv   pre-print
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

A. Fernandez Gambin, E. Angelats, J. Soriano Gonzalez, M. Miozzo, P. Dini
2021 IEEE Access  
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

David Velásquez, Alejandro Sánchez, Sebastian Sarmiento, Mauricio Toro, Mikel Maiza, Basilio Sierra
2020 Applied Sciences  
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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