Literature DB >> 33895588

Development of radio-frequency identification (RFID) sensors suitable for smart-monitoring applications in sewer systems.

Sundra R Tatiparthi1, Yashika G De Costa1, Colin N Whittaker1, Shihu Hu2, Zhiguo Yuan2, Ray Y Zhong3, Wei-Qin Zhuang4.   

Abstract

Sanitary and stormwater sewers are buried assets that play important roles in the prevention of diseases and the reduction of health risks for our societies. Due to their hidden nature, these assets are not frequently assessed and maintained to optimal conditions. The lack of maintenance can cause sewer blockages and overflows that result in the release of pathogens into the environment. For cities, monitoring sewer conditions on a large-scale can be costly, time-consuming, and labor-intensive if using current low-throughput technologies, such as dye testing or closed-circuit television. Alternatively, smart sensor systems can provide low-cost, high-throughput, and automatic data-driven features for real-time monitoring applications. In this study, we developed ultrahigh-frequency radio-frequency identification (UHF RFID)-based sensors that are flushable and suitable for sanitary and stormwater pipes quick surveys. 3D printed RFID sensors were designed to float at the water-air interface and minimize the water interference to RF signal communications. The optimal detection range was also determined to support the design and installation of the reader in various utility holes. 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.
Copyright © 2021 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  High-throughput monitoring; Passive UHF-RFID sensors; Radio-frequency identification (RFID); Sewer blockages; Smart sewer networks; Surface flow rate

Year:  2021        PMID: 33895588     DOI: 10.1016/j.watres.2021.117107

Source DB:  PubMed          Journal:  Water Res        ISSN: 0043-1354            Impact factor:   11.236


  1 in total

1.  Scientific Developments and New Technological Trajectories in Sensor Research.

Authors:  Mario Coccia; Saeed Roshani; Melika Mosleh
Journal:  Sensors (Basel)       Date:  2021-11-24       Impact factor: 3.576

  1 in total

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