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Data Driven Cyber-Physical System for Landslide Detection

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Abstract

Natural disaster is one of the most important research topics worldwide. In this paper, a data driven cyber-physical system is introduced to detect landslides. This system is composed of Wi-Sun acceleration sensors, which can detect the acceleration of the nearby environment in 3D domain, and the sensors are linked with the router (act as ’sink’ node) via Wi-Sun transmission (i.e. IEEE802.15.4g). The details of the detection system are explained and the landslide detection mechanism with low computational complexity is proposed. A traffic reduction method is proposed thereafter to help reduce the data needed for transmission by exploring the intra-correlations of the sensor data. This method can save the energy consumption without degrading the detection performance. Field test is conducted and the results show that the landslide can be detected and amount of data to be transmitted can be reduced, which verifies the system’s effectiveness.

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Notes

  1. http://www.wi-sun.org/

  2. http://www.ieee802.org/15/pub/TG4g.html

  3. Please note that the method could also be applied to other WSNs, especially which uses the same sensor

  4. Note that other type of sensors such as video cameras [36] could be used to help reduce the false alarm, this is left as the future work.

  5. Please note that sensors broadcast generated samples every two minutes, which is insufficient in emergency cases. Whether it is possible to use adaptive transmission rate, i.e. samples with adaptive total number to be delivered, is left as the future work. The most difficult part of the adaptive transmission frequency is the limitation of the hardware.

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Acknowledgments

The research results have been achieved by ”Research and Development on Fundamental and Utilization Technologies for Social Big Data,” the Commissioned Research of National Institute of Information and Communications Technology (NICT), Japan.

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Authors and Affiliations

  1. Waseda University, 3-4-1 Ohkubo, Shinju-ku, Tokyo, 169-8555, Japan

    Zhi Liu, Toshitaka Tsuda & Hiroshi Watanabe

  2. Railway Technical Research Institute, Tokyo, 185-8540, Japan

    Satoko Ryuo & Nagateru Iwasawa

Authors
  1. Zhi Liu
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  2. Toshitaka Tsuda
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  3. Hiroshi Watanabe
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  4. Satoko Ryuo
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  5. Nagateru Iwasawa
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Correspondence to Zhi Liu.

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Liu, Z., Tsuda, T., Watanabe, H. et al. Data Driven Cyber-Physical System for Landslide Detection. Mobile Netw Appl 24, 991–1002 (2019). https://doi.org/10.1007/s11036-018-1031-1

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