Making water smart

Wherever we measure we gather data, wherever we have data we have information, and wherever we have information we have potential knowledge. However, we cannot assume that this knowledge is useful just by ensuring that we measure. The continual growth of data volume, velocity and variety has necessi...

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Bibliographic Details
Published in:Water science and technology 2020-12, Vol.82 (12), p.v-vii
Main Authors: Wade, Matthew J, Steyer, Jean-Philippe, Garcia, M Victoria Ruano
Format: Article
Language:English
Subjects:
Artificial intelligence
Automation
Computer applications
Control
Data
Data analysis
Decision Making
Deep learning
Emission standards
Emissions
Energy consumption
Environmental Engineering
Environmental Sciences
Greenhouse gases
Human performance
Industrial applications
Industry
Information systems
Internet of Things
Linear programming
Machine learning
Neural networks
Nitrates
Principal components analysis
Software
Traction
Water
Water shortages
Water supply
Water treatment
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Summary:Wherever we measure we gather data, wherever we have data we have information, and wherever we have information we have potential knowledge. However, we cannot assume that this knowledge is useful just by ensuring that we measure. The continual growth of data volume, velocity and variety has necessitated the development of tools that can assure its veracity to meet the criteria defined by its ultimate use. Where these tools provide computational functionality that are outside the abilities of a human operator, are non-routine and handle data large or complex in characteristics, we can define them as ‘smart’. This and analogous terminology, such as ‘intelligent’ or ‘cyber physical’, has become ubiquitous within the data science community and has been embraced by manufacturing and processing industries as the 4th Industrial Revolution (Industry 4.0). The water industry is no exception to this and perspectives for Smart Water were neatly presented in two recent IWA whitepapers on Digital Water (IWA 2019; van Thienen & Savic 2020), as part of their ongoing Digital Water Programme. This very much looks at the present and the future of smart technology and intelligent management and use of data across the water sector. For over thirty years, pockets of academics and practitioners have attempted to ‘smarten’ water processes, building on modelling and control foundations, most notably within the Industrial Control and Automation (ICA) community. While some traction has been made (Olsson 2006), general acceptance and integration of methods by industry has been sporadic and limited due to an array of reasons. Nevertheless, we believe that the ideas and approaches for smartening water systems are being embraced wholesale and data analysis and utilisation is being elevated from the mundane to the critical, sitting alongside process and control engineering in the armoury of skills required by practitioners in the water industry to meet present and future challenges facing the sector with preparedness and resilience.
ISSN:0273-1223
1996-9732
DOI:10.2166/wst.2020.581