The Acquisition of Sand Vibration Information in Hinterland of Desert Based on Advanced Remote Sensing System and Network Technologies

  • Xin Ma (马 鑫)
  • Shunge Deng (邓顺戈)
  • Xinwan Li (李新碗)


The deep understanding on sand and sand dunes scale can be useful to reveal the formation mechanism of the sandstorm for early sandstorm forecast. The current sandstorm observation methods are mainly based on conventional meteorological station and satellites remote sensing, which are difficult to acquire sand scale information. A wireless sensing network is implemented in the hinterland of desert, which includes ad hoc network, sensor, global positioning system (GPS) and system integration technology. The wireless network is a three-layer architecture and daisy chain topology network, which consists of control station, master robots and slave robots. Every three robots including one master robot and its two slave robots forms an ad hoc network. Master robots directly communicate with radio base station. Information will be sent to remote information center. Data sensing system including different kinds of sensors and desert robots is developed. A desert robot is designed and implemented as unmanned probing movable nodes and sensors’ carrier. A new optical fiber sensor is exploited to measure vibration of sand in particular. The whole system, which is delivered to the testing field in hinterland of desert (25 km far from base station), has been proved efficient for data acquisition.

Key words

sandstorm sand-scale information optical fiber sensor desert robot wireless sensor network 

CLC number

TN 29 


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The authors express their thanks to Professor KODITSCHEK Daniel E. (Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania), Professor DONG Zhibao, Professor ZHANG Zhengcai (Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences), Professor WANG Hesheng, associate professor PONG Hongli, associate professor QIAN Liang (School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University), Professor YANG Zelin, Professor WANG Xuming (School of Physics and Electronic-Electrical Engineering, Ningxia University) for their contribution.


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Copyright information

© Shanghai Jiaotong University and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Xin Ma (马 鑫)
    • 1
  • Shunge Deng (邓顺戈)
    • 1
  • Xinwan Li (李新碗)
    • 1
    • 2
    • 3
  1. 1.State Key Laboratory of Advanced Optical Communication Systems and Networks, Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghaiChina
  2. 2.University of Michigan - Shanghai Joint InstituteShanghai Jiao Tong UniversityShanghaiChina
  3. 3.Shanghai Institute for Advanced Communication and Data ScienceShanghai Jiao Tong UniversityShanghaiChina

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