A general-purpose method for Pareto optimal placement of flow rate and concentration sensors in networked systems – With application to wastewater treatment plants

Abstract

The advent of aordable computing, low-cost sensor hardware, and highspeed and reliable communications have spurred ubiquitous installation of sensors in complex engineered systems. However, ensuring reliable data quality remains a challenge. Exploitation of redundancy among sensor signals can help improving the precision of measured variables, detecting the presence of gross errors, and identifying faulty sensors. The cost of sensor ownership, maintenance eorts in particular, can still be cost-prohibitive however. Maximizing the ability to assess and control data quality while minimizing the cost of ownership thus requires a careful sensor placement. To solve this challenge, we develop a generally applicable method to solve the multi-objective sensor placement problem in systems governed by linear and bilinear balance

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

“…WBE can be used to monitor new variants (Wade et al 2020;Bar-Or et al 2021;Yu et al 2021) and to provide data in areas where clinical testing is difficult (Weidhaas et al 2021). Globally WBE may allow for surveillance of the estimated 2.1 billion people living in 105,600 wastewater treatment plant (WWTP) districts worldwide (Weidhaas et al 2021).…”

“…Possible sampling locations include the sewer exit from an individual building or location (targeted surveillance); within a major sewer pipeline (targeted surveillance); at the inlet to a WWTP or in the wider environment (community level surveillance). Practical issues may inhibit sampling such as access and safety of personnel; sample variability and representation; and likelihood of blockages in the system (Wade et al 2020). Wastewater samples from treatment plants provide a snapshot of disease prevalence at a city or town level but sampling with greater granularity, for example, from sewer manholes or buildings, can give a more detailed picture of disease prevalence, allowing an even more comprehensive public health response (Betancourt et al 2021;Fuschi et al 2021;Gibas et al 2021;Harris-Lovett et al 2021).…”

“…Wade et al 2020); Cotinine, 5-HIAA, neurotransmitter metabolite 5-HIAA(Chen et al 2014); and pepper mild mottle virus (PMMoV)(Wu et al 2020b;D'Aoust et al 2021). PMMoV is the most abundant RNA virus in human faeces and is stable in wastewater with little seasonal variation(Kitajima et al 2018).…”

An innovative approach for predicting pandemic hotspots in complex wastewater networks using graph theory coupled with fuzzy logic

“…The leakage was then detected using linked pipe flow between each section. The placement of sensors in wastewater treatment plants was suggested by Villez et al ( 2020 ) in order to evaluate and manage data quality while reducing ownership costs. By integrating distributed data profiling techniques on a reduced graph network by minimising the least influential nodes, Srivastava and Singh ( 2022 ) introduced a new fraud detection technique to expose synthetic identities.…”

Optimal selection of monitoring sites in cities for SARS-CoV-2 surveillance in sewage networks

“…Vonach et al (2018) proposed best sampling locations with the objective of calibrating a hydrodynamic model. Finally, Villez et al (2016) and Villez et al (2020) proposed methodologies for sensor placement in WWTPs based on graph theory and mass balances for maximizing the ability to assess and control data quality while minimizing the cost of ownership. Given this background, this paper proposes two algorithms for SARS-CoV-2 monitoring site selection in sewage networks.…”