Application of radio-frequency identification (RFID) sensors for smart- monitoring applications in sewer systems
Foul sewer and storm drainage systems are buried assets that play important roles in the prevention of diseases and the reduction of health risks for our societies. Sewer blockages and inflow/infiltration (I/I) issues in sewer systems are some of the challenges faced by water authorities. Due to their hidden nature, these assets cannot be frequently assessed and maintained in optimal conditions. The lack of maintenance can cause overflows that result in the release of pathogens into the environment. For cities, monitoring sewer-associated issues on a large-scale can be expensive, time-consuming, and labor-intensive with low-throughput methods, such as smoke testing, dye testing, closed-circuit television camera (CCTV), and other acoustic technologies. Alternatively, smart-sensor systems can provide high-throughput, cost-effective, automatic-data-driven features, and robust solutions for monitoring sewer networks. This thesis aims to design, develop, and evaluate novel passive ultra-high frequency radio identification (UHF-RFID)-based sensors for real-time monitoring applications in sewers. Example applications are detecting sewer blockages, I/I flow variations, pinpointing illicit connections, measuring surface velocities, and monitoring water depth in utility holes. First, in Chapter 3, comprehensive development and evaluation of UHF-RFID-based sensors tags were conducted with an ultimate of reliable sewer applications. Initially, three circular or linear polarization antennae with a respective gain of 8 dBiC, 9 dBiC, or 12.5 dBi were used to examine reading ranges and detect limits of 12 types of pre-selected UHF-RFID tags. A significant decrease in the maximum reading distances was observed when the tags were placed in a vertical orientation relative to the center of the antenna as compared with the horizontal orientation. Overall, the 9 dBiC antenna had the best performance in terms of accuracy and stability in the near-field and far-field measurements compared to the 8 dBiC and the 12.5 dBi antennae. The high humidity and water environments like the sewer pipes are detrimental to the performance of UHF-RFID sensors. Therefore, 3D-printed polylactic acid (PLA) and polyvinyl alcohol (PVA) encapsulations were designed to insulate UHF-RFID sensors and allow them to work in sewer pipes. The encapsulations have been specially designed to keep the UHF-RFID sensors floating at the water-to-air interface, making them very tolerant to water interferences in transmitting radio frequency (RF) waves. The new sensors showed optimal reading ranges up to 3.5 m, satisfying the field application requirements. In addition, the encapsulated sensors were tested for their dosing through gully traps or toilet bowls. This study showed that the designed sensors rapidly passed through the S-trap flush toilet drainage system in low and high flush volumes. Moreover, the passage rate of the sensor has been significantly reduced with the increase in the percentage of blocking (10% to 80%) in the drainpipe. Based on sensor passing ratios, the remaining pipe capacity was measured, making it possible to predict the hydraulic capacity of household drains in real-time. In Chapter 4, the UHF-RFID sensors fabricated in Chapter 3 were further evaluated and improved to determine effective reading zones at the water-air interface in sewer utility holes. In this study, Tag 7, Tag 8, and Tag 9 were selected for further study based on their low-cost, small sizes, and satisfactory maximum reading distances of 6.5 m, 6.6 m, and 7.9 m, respectively. 3D encapsulated Tag 7, Tag 8, and Tag 9 have the optimal reading ranges of 0.57–3.5 m that were determined between sensor to antenna distance. The optimal detection ranges are used to guide the design and installation of the reader in various utility holes relative to the water-air interface and minimize the water interference to RF signal communications. Field trials demonstrated that the UHF RFID system is a low-cost, high-throughput, and robust solution for monitoring blockage, illicit-connection, and water flow in sewer networks. Based on the developed sensors in Chapter 3 and Chapter 4, the passive UHF-RFID-based sensors Tag 7 and Tag 9 were further used to gain quantitative information of sewer blockages, flow velocities, and I/I under various flow patterns and scenarios in near real-time in Chapter 5. First, Tag 7 and Tag 9 RFID-based water level gauges were used in the measurement of water depths. The RFID gauge accurately determined water levels at a 0.7 cm resolution with robust reliability. From 3D printed Tag 7 and Tag 9 RFID sensors, the surface velocities (V_sur) were predicted for flows from 7–72 L/s. The findings showed that good linearity (R2 = 0.95) between the mean velocity (V_avg) and the surface velocity (V_sur) is V_avg = 0.607 V_sur . This constant was observed to be close to the value of 0.60 used to calculate the mean velocity in small channels with shallow water flows specified in the literature. In addition, as the size of the blockage (0–50%) increased, a significant change in water levels was observed before and after blockages. As a result, V_avg at the downstream location was larger than V_avg at the upstream, which depicted a strong indication of the blockages. Also, a potential indication of blockage showed as the variation between average velocities (V_avg), and the surface velocities (V_sur) from UHF-RFID sensors. Subsequently, sensors were tested for various I/I flow variations. This stage of study results showed that variation in V_sur profiles were depicted as increased inflows (3.0–72 L/s, n=24 test runs), with R2 = 0.93 and 0.89 in dry and wet weather scenarios. The method was successfully applied to field studies in a real-life sewer network gravity main, where V_sur and sewage hydraulic retention time (HRT) was successfully estimated from UHF-RFID sensors. Overall, this study collected and demonstrated the application of UHF-RFID-based smart sensors to address common issues in sewer systems, such as identifying illicit connections, measuring wastewater surface velocity and water depth, detecting sewer blockages, and estimating I/I flow behaviors. The sensors have also been evaluated in the field trials conducted in gravity mains. Therefore, the UHF-RFID-based sensors developed in this study: (1) Can be used efficiently to address these issues; (2) Are low-cost, high-throughput, and robust solutions as compared with conventional technologies for pipes quick surveys; and (3) Can be used for real-time data transfer in large-scale sewer monitoring applications that contributes to the development of smart cities.
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