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Research on Intelligent Perception and Accident Prediction System of Smart City Traffic Information Supported by Spatiotemporal Big Data Mining and GIS Visualization

Author(s)

Yuanzhu Sun

Affiliation(s)

Department of Spatial Information Engineering University of Seoul, Seoul South, 137-070, Korea

Abstract

This research focuses on the intelligent perception and accident prediction system of smart city traffic information supported by spatiotemporal big data mining and GIS visualization. This paper analyzes the research background and significance, the current situation at home and abroad, and expounds the relevant theoretical basis, including spatio-temporal big data, GIS visualization and smart city transportation system architecture. The application of spatio-temporal big data mining in traffic is introduced in detail, such as data collection and integration, clustering, pattern and association rule mining, and the support of GIS visualization for intelligent perception of traffic information, covering traffic network, traffic flow, bus and event visualization. The smart city traffic information intelligent perception system is constructed, including sensor layout optimization, data transmission and storage, and intelligent perception algorithm design. A traffic accident prediction system based on spatiotemporal big data was established, risk factors were analyzed, models were constructed, and training and verification were carried out. Finally, we summarize the research results and look forward to the future research direction, aiming at promoting the development of smart city transportation.

Keywords

Spatio-Temporal Big Data Mining; GIS Visualization; Smart City Transportation; Intelligent Perception; Accident Prediction

References

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