Water and Wastewater Building CPS: Creation of Cyber-Physical Wastewater Collection System Centered on Urine Diversion

Abstract

Decentralized treatment of wastewater has been identified as an area of growth for cyber-enabled sensing and control. One such system that would benefit from embedded cyber components is urine diversion. This research sought to create a cyber-physical system for wastewater collection and treatment. Two subsystems were integrated into the CPS: sensing and actuation. Real-time sensing using low-cost pH and conductivity sensors was used to monitor urine chemistry. Actuation was used to deliver urine to the system and to control urine chemistry. Once integrated, the system used the sensing data to determine when to actuate urine chemistry control pumps. By using urine diversion as a test case, two demonstrations were able to show the applicability of the system created. The first demonstration was able to characterize the flow characteristics of the physical system. The second demonstration was able to mimic and inhibit urea hydrolysis under realistic conditions. Ultimately, the use of this novel CPS approach was able to confirm the benefits of sensing and actuation in wastewater collection and treatment within buildings.

Pragmatic analysis of wastewater treatment methods from a statistical perspective

“…This is because the later models utilize chemical reactions in order to speed-up the treatment process. In terms of deployment costs, TMOOA (Han et al 2020), IMCDR (Elsahwi et al 2019), EP (Deng et al 2020), MOPC (Han et al 2020), PD (Deng et al 2020), AOPO (Deng et al 2020), SC (Deng et al 2020), and EM (Saetta et al 2019) outperform other models, thus, are widely used for low-cost wastewater treatment. Based on this comparison, researchers can select the best model for their application, but it is difficult to identify a model with optimum quality, sludge level, complexity, delay, and cost, thus, a novel model rank (MR) is estimated for these models using Equation (1),…”

“…Electrochemical methods (EMs) (Saetta et al 2019) are also useful for cyanide removal from wastewater with higher efficiency than chemical or sedimentation processes. While, data-driven iterative adaptive critic (DDIAC) strategy (Wang et al 2021), stacking ensemble learning (SEL) (Liu et al 2020b), chemical treatment of anaerobic reactor (CTAR) (Zeb et al 2020), and discharged plasma-based reactor (DPBR) design (Xiang et al 2019) are proposed by authors, these models are highly application-specific, and do not scale well due to their inherent internal compositions.…”

Perspective: Phosphorus monitoring must be rooted in sustainability frameworks spanning material scale to human scale

“…(2022) developed soft sensor CPS for predicting P concentration in wastewater bioreactors based on real time surrogate sensors (see supplemental Table S1). Other examples of soft sensor CPS have been demonstrated in urine monitoring and control ( Saetta et al., 2019 ) and in-pipe robotic systems for water quality ( Kazeminasab and Banks 2022 ).…”

An Internet-of-Things Enabled Smart System for Wastewater Monitoring

“…The sensing systems proposed by Rekha et al and Saetta et al in [24] and [21], respectively, use alarms triggered by a distance-based anomaly detection algorithm, with predefined fixed thresholds as the basic method for classification of a time-series of measurements as an anomaly. Such methods may perform properly for drinking water distribution networks and the monitoring of physical parameters of excreted urine, since no fluctuations in those physical parameters are expected in those applications at any time or point in the network in a normal context, viz., no data seasonality.…”