Article Details

Title · Authors · Abstract · Keywords · DOI · References

Design of Trusted Data Platform for Crowd Movement Based on Multi-source Spatio-temporal Data

GONG Yuming1,2, WANG Yangzhou1,2, YAN Zengyong1,2, XIE Hongtao1,2, OU Jiankai1,2

(1.CETC Big Data Research Institute Co., Ltd., Guiyang 550000, China; 2.National Engineering Research Center for Big Data Application Technology to Improve Government Governance, Guiyang 550081, China)

Section：Internet of Things · Vol. 2025, Issue 7 · Pages：192-198 · 2096-4706（2025）07-0192-07 · CLC number：TP311；TP309 · Document code：A · DOI：10.19850/j.cnki.2096-4706.2025.07.035

Abstract

In order to solve the problems of urban traffic congestion, uneven population distribution, and unreasonable infrastructure planning caused by the rapid growth of urban population, this paper takes multi-source spatio-temporal data as the research object, and constructs a trusted data governance platform based on multi-source spatio-temporal data. The platform analyzes the distribution and aggregation of urban population from different time dimensions by processing multi-source spatio-temporal data. Meanwhile, in order to ensure the credibility of the data space, the platform integrates blockchain technology, synchronizes business data and analysis results on the chain, and realizes the synchronous update of platform data and chain data. The results show that the platform not only inherits the high performance of data warehouse, but also solves the one-sided problem of single data source. At the same time, it increases the credibility of data governance platform and provides a new idea for urban traffic planning and facilities construction.

Keywords

multi-source data; trusted data space; blockchain; spatio-temporal data

References

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About the authors

Gong Yuming (1993-), male, Han nationality, from Wuzhou, Guangxi, engineer, master's student, research direction: data governance, data development, data implementation.