Prediction of the crowd behavior in campus based on time series model. (August 2020) - Chen, Liangwei; Yang, Jingjing; Chen, Zhigang; Huang, Ming
Abstract: Recognizing and understanding the behavior of the campus crowd is of great significance for improving the comprehensive management capabilities of the campus. The increasingly abundant of mobile terminal WIFI signals provide a unique data source for studying the behavior of the campus crowd. A Wifi-based personnel activity monitoring system is developed in this paper. Through monitoring and analyzing the MAC address (Media Access Control Address), RSSI (Received Signal Strength Indication) and Wireless AP (Access Point) in and around the Science Museum, Huaizhou building of Yunnan University, the association between WIFI signal and the crowd behavior is studied. Time series analysis is used to make predictions, and some valuable information about the gathering and activity status of campus crowd behavior is obtained. It provides an experimental platform for studying the dynamic behavior of people in campus or other crowd areas.