Water Science & Technology Special Issue on

Developments and Applications of IoT-based Sensors
for Wastewater and Drainage Systems

The ongoing rapid development of the internet of things (IoT) concept as part of smart city development triggers new approaches for the monitoring and controlling of urban water and wastewater infrastructure. The prevalence of system-wide management of urban water and wastewater infrastructure will therefore increase in future. Notably, the evolution of low-cost sensors, when combined with innovative and wireless data transfer technologies, enables large-scale implementation of measurement equipment, even in remote or underground structures. These developments open up new opportunities for the management of the urban stormwater and wastewater infrastructure.

This Special Issue gathers contributions and review articles on advancing scientific and technical methodologies, technologies, and best practices in the context of IoT sensors for urban wastewater and drainage systems. We have created a broad collection of papers introducing recent developments, new experiences and novel ideas.

Prof. Dr. Robert Sitzenfrei, University of Innsbruck, Austria

Prof. Dr. Ivar Annus, Tallinn University of Technology, Estonia

Prof. Dr. Jeroen Langeveld, Technical University Delft, Netherlands

Dr. Jörg Rieckermann, Swiss Federal Institute of Aquatic Science and Technology, Switzerland

Prof. Dr. Wolfgang Rauch, University of Innsbruck, Austria

Editorial: Developments and applications of IoT-based sensors for wastewater and drainage systems

Robert Sitzenfrei; Ivar Annus; Jeroen Langeveld; Jörg Rieckermann; Wolfgang Rauch

Water Science & Technology (15 February 2024) 89 (4): iii–v.

DOI: https://doi.org/10.2166/wst.2024.058

A comprehensive, open-source data model for wastewater-based epidemiology

Jean-David Therrien; Mathew Thomson; Eugen-Sorin Sion; Ivan Lee; Thomas Maere; Niels Nicolaï; Douglas G. Manuel; Peter A. Vanrolleghem

Water Science & Technology (2024) 89 (1): 1–19.

DOI: https://doi.org/10.2166/wst.2023.409

Validation of wastewater data using artificial intelligence tools and the evaluation of their performance regarding annotator agreement

Imane Zidaoui; Cédric Wemmert; Matthieu Dufresne; Claude Joannis; Sandra Isel; Jonathan Wertel; José Vazquez

Water Science & Technology (2023) 87 (12): 2957–2970.

DOI: https://doi.org/10.2166/wst.2023.174

Monitoring and control of smart urban drainage systems using NB-IoT cellular sensor networks

Priit Roosipuu, Ivar Annus, Alar Kuusik, Nils Kändler, Muhammad Mahtab Alam

Water Science & Technology (2023) 88 (2): 339–354.

DOI: https://doi.org/10.2166/wst.2023.222

Chances and barriers of building information modelling in wastewater management

Florian Kretschmer, S. Franziskowski, F. Huber, T. Ertl

Water Science & Technology (2023) 87 (7): 1630–1642.

DOI: https://doi.org/10.2166/wst.2023.079

Smart water campus – a testbed for smart water applications

Martin Oberascher; Carolina Kinzel; Ulrich Kastlunger; Martin Schöpf; Karl Grimm; Daniel Plaiasu; Wolfgang Rauch; Robert Sitzenfrei

Water Science & Technology (2022) 86 (11): 2834–2847.

DOI: https://doi.org/10.2166/wst.2022.369

Wastewater-based epidemiology (WBE) for SARS-CoV-2 – A review focussing on the significance of the sewer network using a Dublin city catchment case study

Joanne Mac Mahon, Alejandro Javier Criado Monleon, Laurence W. Gill, John J. O'Sullivan, Wim G. Meijer

Water Science & Technology (2022) 86 (6): 1402–1425.

DOI: https://doi.org/10.2166/wst.2022.278

A predictive model for ammonium removal in polishing ponds operated in sequential bath mode

Carlos Eduardo Pereira de Morais, Silvânia Lucas dos Santos, Adrianus van Haandel

Water Science & Technology (2023) 87 (1): 13–26.

DOI: https://doi.org/10.2166/wst.2022.418