An analysis algorithm for real-time monitoring of campus crowd density based on campus wireless network logs

Ying Xia; Shuping Wu; Hui Yu

doi:10.1117/12.2679233

8 May 2023 An analysis algorithm for real-time monitoring of campus crowd density based on campus wireless network logs

Ying Xia, Shuping Wu, Hui Yu

Proceedings Volume 12635, Second International Conference on Algorithms, Microchips, and Network Applications (AMNA 2023); 126350G (2023) https://doi.org/10.1117/12.2679233
Event: International Conference on Algorithms, Microchips, and Network Applications 2023, 2023, Zhengzhou, China

Abstract

In order to implement precision management on the campus, the decisions need data support, and the crowd density on campus is one of the important parts. Based on campus wireless network logs, which is widely used on the campus, this paper proposes an analysis algorithm to obtain online wireless network user numbers in real time and draws the conclusion that the numbers of online users can represent crowd density on campus. Experimental results show that this algorithm can effectively get the numbers of online users in each area of the campus, and the campus heat map made with these data can reflect the real-time distribution of campus crowd and crowd density. This method uses log analysis method which is a general solution for some problems and has practical value for in-depth analysis.

Citation Download Citation

Ying Xia, Shuping Wu, and Hui Yu "An analysis algorithm for real-time monitoring of campus crowd density based on campus wireless network logs", Proc. SPIE 12635, Second International Conference on Algorithms, Microchips, and Network Applications (AMNA 2023), 126350G (8 May 2023); https://doi.org/10.1117/12.2679233

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