We used LiDAR to detect and track people in an exhibition facility for better crowd management. The results were treated as time series data and visualized using a web application. In addition, we verified visitors’ stopping points to quantify interest in various exhibits, and found that by checking the time visitors spent in front of exhibits in 10-second intervals, the places in the exhibition hall that interested visitors could be visualized. The results suggest that the time classified as viewing is not necessarily longer, but that a threshold that takes into account the facilities and routes within the exhibition facility should be set.

1. [1] C. Feliciani, K. Shimura, and K. Nishinari, “Introduction to crowd management: Managing crowds in the digital era: Theory and Practice,” Springer, p. 67, 2021. https://doi.org/10.1007/978-3-030-90012-0
2. [2] Y. Li and J. Ibanez-Guzman, “Lidar for Autonomous Driving: The Principles, Challenges, and Trends for Automotive Lidar and Perception Systems,” IEEE Signal Processing Magazine, Vol.37, No.4, pp. 50-61, 2020. https://doi.org/10.1109/MSP.2020.2973615
3. [3] Japanese Garden Yuushien Ltd. https://www.yuushien.com/ [Accessed February 26, 2024]
4. [4] Quanergy M8 Series. https://quanergy.com/products/m8/ [Accessed February 26, 2024]