Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Plenary 5: Monitoring and Associated Technologies 1 - Measurement Methods
1:30pm - 3:00pm
Session Chair: Jean-Luc Bertrand-Krajewski
Location:Lecture Hall BMT
BMTEG138 (HS BMT), Biomedical Engineering Building at Stremayrgasse 16, 8010 Graz, ground floor
1:30pm - 1:50pm ID: 117 / Plenary 5: 1 Abstract for Oral Presentation Topics: Monitoring and associated technologies, Emerging Issues and new technologies related to sewers Keywords: hyperspectral imaging, online monitoring, wastewater pollution, non contact
Towards non-contact pollution monitoring in sewers with hyperspectral imaging
Pierre Lechevallier1,2, Christian Felsheim3, Jörg Rieckermann2
1ETH Zürich, Institute of Environmental Engineering, 8093 Zürich, Switzerland; 2Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland; 3Headwall Photonics, Bolton, USA
Monitoring continuously pollution in the urban drainage system is challenging. Traditional approaches such as sampling campaigns or spectrometric probes have limitations. Using a hyperspectral imaging system to measure light reflection spectra of the wastewater surface is a promising approach for non-contact online measurement of pollution. We acquired hyperspectral data-cube from 18 synthetic wastewater samples. After pre-processing and pixel selection, a cross-validation partial-least square regression was used to predict turbidity (R2=0.923). Further research is planned before the SPN10 to improve the measurement, generate and analyse more data, and explore other indicators such as organic pollution.
1:50pm - 2:10pm ID: 127 / Plenary 5: 2 Abstract for Oral Presentation Topics: Monitoring and associated technologies, Emerging Issues and new technologies related to sewers Keywords: Organic micropollutants, on-site monitoring, combined sewer overflows
On-site measurement of organic micropollutants with transportable HRMS platform at combined sewer overflows
Viviane Furrer1,2, Heinz Singer1, Christoph Ort1
1Eawag, Switzerland; 2ETH Zürich
The MS2field, an automated transportable HRMS platform, allows real-time measurement of dissolved organic micropollutants with a temporal resolution of 20 minutes.
The MS2field was adapted to be applied at combined sewer overflows and tested during a four-month field campaign.
Results show high temporal variation in concentration of polar organic micropollutants.
2:10pm - 2:30pm ID: 124 / Plenary 5: 3 Abstract for Oral Presentation Topics: Monitoring and associated technologies, Emerging Issues and new technologies related to sewers Keywords: Deep-learning, FOG, optical monitoring, CCTV
Deployment of a non-invasive optical monitoring system in wastewater pumping stations
Antonio Moreno-Rodenas1, Alex Duinmeijer2, Danko Boonstra1, Christian van Nieuwenhuizen1, Mathieu Lepot3, Francois Clemens1,4
1Deltares, Netherlands, The; 2Municipality of Rotterdam, The Netherlands; 3Un poids une mesure, Lyon, France; 4Norwegian University of Science and Technology, Trondheim, Norway
Accumulation of floating solids (such as plastics, fat, oil and grease) in wastewater pump sumps is a relevant cause of malfunctioning, loss of efficiency and frequent maintenance activities. Recently, we developed a deep-learning based solution to automatically monitor the surface dynamics of floating layers in wastewater pumping stations. We present here the application of this technique to 7 pumping stations (6 in the Netherlands and 1 in France) representative of different urban drainage systems.
2:30pm - 2:50pm ID: 107 / Plenary 5: 4 Abstract for Oral Presentation Topics: Monitoring and associated technologies Keywords: open source, machine learning, sensors, sewer flow measurements
On dirty water and cheap video: Real-time flow measurements derived from camera footage using an Open-Source ecosystem
Robert Meier1, Franz Tscheikner-Gratl1, David B. Steffelbauer1,2, Christos Makropoulos1,3
1Norwegian University of Science and Technology; 2Kompetenzzentrum Wasser Berlin; 3National Technical University of Athens
Sensors used for wastewater flow measurements are robust and expensive pieces of hardware that must be maintained regularly to function in the hazardous environment of sewers. Remote sensing can remedy these issues. We utilize off‐the‐shelf cameras and convolutional neural networks to extract the water level and surface velocity from camera images directly, without the need for artificial markers in the sewage stream. In a laboratory setting, our method estimates the water level with an accuracy of ±2.48% and the surface velocity with an accuracy of ±2.08% —a performance comparable to other state‐of‐the‐art solutions.