A wireless sensor network based pipeline monitoring system

This paper proposes a Pipeline Monitoring system using the technology of Wireless Sensor Networks. This research involves the development of a Remote Condition Based Monitoring application for Oil and Gas pipelines using over 100 Wireless Sensor Network Motes. This paper describes the research metho...

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Bibliographic Details
Published in:2014 International Conference on Signal Processing and Integrated Networks (SPIN) pp. 412 - 419
Main Authors: Anupama, K. R., Kamdar, Nishad, Kamalampet, Santosh Kumar, Vyas, Dhruv, Sahu, Siddharth, Shah, Supan
Format: Conference Proceeding
Language:English
Published: IEEE 01-02-2014
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Summary:This paper proposes a Pipeline Monitoring system using the technology of Wireless Sensor Networks. This research involves the development of a Remote Condition Based Monitoring application for Oil and Gas pipelines using over 100 Wireless Sensor Network Motes. This paper describes the research methodology and a step-wise system development procedure. It starts with the description of an application specific Test Bed for the Pipeline Monitoring System. The subsequent section describes the development of experimental protocols required for designing a Cross-Layered Protocol Stack for the monitoring application. Further, a performance metric based comparative analysis of the experimental protocols is presented giving rise to a high performance and energy efficient Cross-Layered Protocol Stack. This study also includes a short literature survey which conveys the advantages of WSN based Pipeline Monitoring system over contemporary condition based pipeline monitoring systems. The proposed protocol stack consists of Time Synchronization, Routing, Topology Control and Media Access Control protocols. The protocol stack exhibits inherent characteristics of low energy consumption and low memory usage which are vital in the development of a Wireless Sensor Network framework. In addition to this, a user friendly Graphical User Interface for data logging and real time data analysis has also been developed and presented as a part of this study.
DOI:10.1109/SPIN.2014.6776989