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Design and Evaluation of IoT-Enabled Instrumentation for a Soil-Bentonite Slurry Trench Cutoff Wall

Autor(en): ORCID


Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Infrastructures, , n. 1, v. 4
Seite(n): 5
DOI: 10.3390/infrastructures4010005
Abstrakt:

In this work, we describe our approach and experiences bringing an instrumented soil-bentonite slurry trench cutoff wall into a modern IoT data collection and visualization pipeline. Soil-bentonite slurry trench cutoff walls have long been used to control ground water flow and contaminant transport. A Raspberry Pi computer on site periodically downloads the sensor data over a serial interface from an industrial datalogger and transmits the data wirelessly to a gateway computer located 1.3 km away using a reliable transmission protocol. The resulting time-series data is stored in a MongoDB database and data is visualized in real-time by a custom web application. The system has been in operation for over two years achieving 99.42% reliability and no data loss from the collection, transport, or storage of data. This project demonstrates the successful bridging of legacy scientific instrumentation with modern IoT technologies and approaches to gain timely web-based data visualization facilitating rapid data analysis without negatively impacting data integrity or reliability. The instrumentation system has proven extremely useful in understanding the changes in the stress state over time and could be deployed elsewhere as a means of on-demand slurry trench cutoff wall structural health monitoring for real-time stress detection linked to hydraulic conductivity or adapted for other infrastructure monitoring applications.

Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10723313
  • Veröffentlicht am:
    22.04.2023
  • Geändert am:
    10.05.2023
 
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