Sweating the assets – The role of instrumentation, control and automation in urban water systems

Yuan, Zhiguo; Olsson, Gustaf; Cardell-Oliver, Rachel; Schagen, Kim van; Marchi, Angela; Deletić, Ana; Urich, Christian; Rauch, Wolfgang; Liu, Yanchen; Jiang, Guangming

doi:10.1016/j.watres.2019.02.034

Cited by 87 publications

(57 citation statements)

References 166 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The outcome of any model or data analysis is only as good as the data that are entered into the process. For example, digitalisation may be based on online sensor water quality data (Blumensaat et al, 2019;Vanrolleghem and Lee, 2003;Yuan et al, 2019). Inaccurate data due to sensor fouling, drift, or lack or maintenance or calibration can lead to erroneous results and consequently fallacious decisions (Rieger et al, 2010).…”

Section: The Importance Of Data and Qualitymentioning

confidence: 99%

When the fourth water and digital revolution encountered COVID-19

Poch

Garrido-Baserba

Corominas

et al. 2020

Science of The Total Environment

View full text Add to dashboard Cite

show abstract

Section: The Importance Of Data and Qualitymentioning

confidence: 99%

When the fourth water and digital revolution encountered COVID-19

Poch

Garrido-Baserba

Corominas

et al. 2020

Science of The Total Environment

View full text Add to dashboard Cite

show abstract

“…These are the most critical challenges requiring urgent research attention as the efficient end-user data analysis approach can benefit the customers' billing and costs. Such work will provide insight into future big water data management research and commercial applications [107][108][109].…”

Section: Smart Water (End-user) Data Disaggregation and Analysismentioning

confidence: 99%

Rethinking the Framework of Smart Water System: A Review

Yang

Sitzenfrei

2020

Water

View full text Add to dashboard Cite

Throughout the past years, governments, industries, and researchers have shown increasing interest in incorporating smart techniques, including sensor monitoring, real-time data transmitting, and real-time controlling into water systems. However, the design and construction of such a smart water system are still not quite standardized for massive applications due to the lack of consensus on the framework. The major challenge impeding wide application of the smart water network is the unavailability of a systematic framework to guide real-world design and deployment. To address this challenge, this review study aims to facilitate more extensive adoption of the smart water system, to increase effectiveness and efficiency in real-world water system contexts. A total of 32 literature pieces including 1 international forum, 17 peer-reviewed papers, 10 reports, and 4 presentations that are directly related to frameworks of smart water system have been reviewed. A new and comprehensive smart water framework, including definition and architecture, was proposed in this review paper. Two conceptual metrics (smartness and cyber wellness) were defined to evaluate the performance of smart water systems. Additionally, three pieces of future research suggestions were discussed, calling for broader collaboration in the community of researchers, engineers, and industrial and governmental sectors to promote smart water system applications.

show abstract

“…Sensor-based control was reviewed by Yuan et al (2019) focusing on interoperability among commonly perceived independent subcategories of water and wastewater pipe systems and treatment systems. Kõrgmaa et al (2019) reported on the use of sensor-based automation to improve sludge volume index in several water reclamation plants and process consistency.…”

Section: Instrumentationmentioning

confidence: 99%