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Data Networking for Autonomous Fatigue Crack Detection

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Smart Sensors for Health and Environment Monitoring

Part of the book series: KAIST Research Series ((KAISTRS))

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Abstract

One of the useful applications of wireless sensor networks is structural health monitoring, where sensors are distributed to monitor buildings, bridges, large dams, etc. Out of a large number of application domains we focus on the fatigue crack detection of a structure, e.g., bridge. In this chapter, we summarize the required components for data networking for autonomous fatigue crack detection and explore the design choices there. We first discuss the unique characteristics in delivering data stemming from autonomous fatigue crack detection such as data traffic pattern, and network topology, and the necessary degree of performance metrics, e.g., energy efficiency and latency. From the data networking perspective, we present and compare the strength and weakness of various design choices in wireless sensor networks, covering multiple layers in networking protocol stack.

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Notes

  1. 1.

    China wind power capacity is expected to reach 150 million kilowatts.

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Acknowledgements

This work is supported by the Center for Integrated Smart Sensors funded by the Ministry of Science, ICT and Future Planning as the Global Frontier Project.

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Authors and Affiliations

  1. Electrical Engineering, KAIST, Daejeon, South Korea

    Jinhwan Jung, Deawoo Kim, Hankyeol Lee & Yung Yi

Authors
  1. Jinhwan Jung
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  2. Deawoo Kim
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  3. Hankyeol Lee
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  4. Yung Yi
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Corresponding author

Correspondence to Jinhwan Jung .

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Editors and Affiliations

  1. Electrical Engineering Center for Integrated Smart Sensors, KAIST, Daejoen, Korea, Republic of (South Korea)

    Chong-Min Kyung

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Jung, J., Kim, D., Lee, H., Yi, Y. (2015). Data Networking for Autonomous Fatigue Crack Detection. In: Kyung, CM. (eds) Smart Sensors for Health and Environment Monitoring. KAIST Research Series. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9981-2_11

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  • DOI: https://doi.org/10.1007/978-94-017-9981-2_11

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-017-9980-5

  • Online ISBN: 978-94-017-9981-2

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