This chapters in this book highlight the breadth of smart water technologies and applications. From the use of classical machine learning and data transformation methods for process improvement, to data management and assimilation in models for better monitoring control, a selection of these chapters describes the acquisition and preparation of data as an initial step in its use as part of a digital framework for smart water applications. Importantly, several chapters examine the use of smart tools and contemporary AI technologies, such as neural networks and Internet of Things, that demonstrate value in non-conventional or remote environments. This collection demonstrates the innovation possible through the entire ‘pipeline’ of the process of applying smart water techniques, from data measurement and collection, through initial analysis to the application of machine learning and AI techniques and finally through to system deployment. Each of these steps plays an important role in the application of data science and AI techniques to water problems.

Collectively, the book showcases the innovation required to leverage modern data science and AI approaches in the water sector and collectively point the way towards a future of new measurement techniques, innovative methodologies, and intuitive human interaction to truly ‘Make Water Smart’.

In Focus – a book series that showcases the latest accomplishments in water research. Each book focuses on a specialist area with papers from top experts in the field. It aims to be a vehicle for in-depth understanding and inspire further conversations in the sector.


A critical review of the data pipeline: how wastewater system operation flows from data to intelligence
Jean-David Therrien, Niels Nicolaï and Peter A. Vanrolleghem

A comprehensive review of deep learning applications in hydrology and water resources
Muhammed Sit, Bekir Z. Demiray, Zhongrun Xiang, Gregory J. Ewing, Yusuf Sermet and Ibrahim Demir

Performance improvement of wastewater treatment processes by application of machine learning
O. Icke, D. M. van Es, M. F. de Koning, J. J. G. Wuister, J. Ng, K. M. Phua, Y. K. K. Koh, W. J. Chan and G. Tao

Data analytics in control and operation of municipal wastewater treatment plants: qualitative analysis of needs and barriers
S. Eerikäinen, H. Haimi, A. Mikola and R. Vahala

Making urban water smart: the SMART-WATER solution
Gerasimos Antzoulatos, Christos Mourtzios, Panagiota Stournara, Ioannis-Omiros Kouloglou, Nikolaos Papadimitriou, Dimitrios Spyrou, Alexandros Mentes, Efstathios Nikolaidis, Anastasios Karakostas, Dimitrios Kourtesis, Stefanos Vrochidis and Ioannis Kompatsiaris

Fault detection and diagnosis in water resource recovery facilities using incremental PCA
Pezhman Kazemi, Jaume Giralt, Christophe Bengoa, Armin Masoumian and Jean-Philippe Steyer

Use of real-time sensors for compliance monitoring of nitrate in finished drinking water
Christopher S. Jones, Tianyi Li, Alex Sukalski, Darrin A. Thompson and David M. Cwiertny

Data integration for infrastructure asset management in small to medium-sized water utilities
N. Carriço, B. Ferreira, R. Barreira, A. Antunes, C. Grueau, A. Mendes, D. Covas, L. Monteiro, J. Santos and I. S. Brito

Multi-objective optimization of energy and greenhouse gas emissions in water pumping and treatment
Iliana Cardenes, Afreen Siddiqi, Mohammad Mortazavi Naeini, Jim W. Hall

Development of a biogas distribution model for a wastewater treatment plant: a mixed integer linear programming approach
Harry Laing, Chris O'Malley, Anthony Browne, Tony Rutherford, Tony Baines, Mark J. Willis

Predicting failures in electronic water taps in rural sub-Saharan African communities: an LSTM-based approach
N. M. Offiong, Y. Wu, F. A. Memon

Experiments of an IoT-based wireless sensor network for flood monitoring in Colima, Mexico
O. Mendoza-Cano, R. Aquino-Santos, J. López-de la Cruz, R. M. Edwards, A. Khouakhi, I. Pattison, V. Rangel-Licea, E. Castellanos-Berjan, M. A. Martinez-Preciado, P. Rincón-Avalos, P. Lepper, A. Gutiérrez-Gómez, J. M. Uribe-Ramos, J. Ibarreche and I. Perez

Capturing high-resolution water demand data in commercial buildings
Peter Melville-Shreeve, Sarah Cotterill and David Butler

A feasibility study of uninhabited aircraft systems for rapid and cost-effective plant stress monitoring at green stormwater infrastructure facilities
Kery Prettyman, Meghna Babbar-Sebens, Christopher E. Parrish and Jeremy Matthew Babbar-Sebens

Data assimilation in hydrodynamic models for system-wide soft sensing and sensor validation for urban drainage tunnels
Rocco Palmitessa, Peter Steen Mikkelsen, Adrian W. K. Law and Morten Borup

Taking water efficiency to the next level: digital tools to reduce non-revenue water
J. Cassidy, B. Barbosa, M. Damião, P. Ramalho, A. Ganhão, A. Santos and J. Feliciano

An ethical decision-making framework with serious gaming: a smart water case study on flooding
Gregory Ewing and Ibrahim Demir

Interactive decision support methodology for near real-time response to failure events in a water distribution network
E. Nikoloudi, M. Romano, F. A. Memon and Z. Kapelan

Control theory-based data assimilation for hydraulic models as a decision support tool for hydropower systems: sequential, multi-metric tuning of the controllers
Miloš Milašinović, Dušan Prodanović , Budo Zindović , Boban Stojanović and Nikola Milivojević

Visualisation of the combinatorial effects within evolutionary algorithms: the compass plot
Qi Wang, Miaoting Guan, Wen Huang, Libing Wang, Zhihong Wang, Shuming Liu and Dragan Savić

Flood mitigation in coastal urban catchments using real-time stormwater infrastructure control and reinforcement learning
Benjamin D. Bowes, Arash Tavakoli, Cheng Wang, Arsalan Heydarian, Madhur Behl, Peter A. Beling and Jonathan L. Goodall

Matthew J Wade

Edward C. Keedwell

Jean-Philippe Steyer

M. Victoria Ruano Garcia

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