Shuiwen dizhi gongcheng dizhi (Nov 2023)

Exploration of blockchain technology application in the construction of National Risk Warning System on Landslides

  • Mingzhi ZHANG,
  • Fei YANG,
  • Juan MA,
  • Zheng FU,
  • Zhe HUANG,
  • Junfeng LI

DOI
https://doi.org/10.16030/j.cnki.issn.1000-3665.202302012
Journal volume & issue
Vol. 50, no. 6
pp. 168 – 174

Abstract

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Since 2019, the Ministry of Natural Resources has comprehensively promoted the research and development of universal equipment and the automatic monitoring and forewarning of geological hazard. As of June 2023, it has been applied to 55 000 potential points of geological hazard in 17 key geological hazard prevention provinces, and the national geological hazard monitoring and forewarning system has entered a rapid development stage. At present, the system receives more than 10 million monitoring data every day, and has made positive progress in massive data storage management, parallel processing of time series data, intelligent analysis of big data and multi-parameter risk early warning. However, there are many challenges in data security of the system, especially in data consistency, data tamper resistance and system reliability. On the basis of systematic research on the characteristics of the blockchain technology and its typical application in related fields, this paper proposes a “trusted data flow” technology based on distributed ledger and consensus mechanism, according to which the overall framework of “blockchain + NRWSL” is formed, and a prototype system is established. The test data show that the improved system can solve the problem of data inconsistency between provinces and Ministry of Natural Resources, identify and prevent illegal data tampering, ensure the stable operation of the system under multi-node failure conditions, and the overall performance loss of the system is less than 20%. The research results provide technical methods for the application of blockchain technology to geological hazard risk early warning systems at all levels in China, and also provide top-level design ideas for improving the security of geological hazard monitoring data and the early warning system.

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