Estimating indoor crowd density and movement behavior using WiFi Sensing

TL;DR

This paper presents a WiFi sensing system that passively tracks smartphone locations to estimate indoor crowd density and movement patterns, with promising results for use in enclosed spaces.

Contribution

It introduces a novel passive WiFi probing system for indoor crowd analysis, demonstrating its effectiveness in real-world office environments.

Findings

Accurate crowd density estimation achieved

Effective tracking of movement flows within indoor spaces

Potential applications in security and urban planning

Abstract

The fact that almost every person owns a smartphone device that can be precisely located is both empowering and worrying. If methods for accurate tracking of devices (and their owners) via WiFi probing are developed in a responsible way, they could be applied in many different fields, from data security to urban planning. Numerous approaches to data collection and analysis have been covered, some of which use active sensing equipment, while others rely on passive probing, which takes advantage of nearly universal smartphone usage and WiFi network coverage. In this study, we introduce a system that uses WiFi probing technologies aimed at tracking user locations and understanding individual behavior. We built our own devices to passively capture WiFi request probe packets from smartphones, without the phones being connected to the network. The devices were tested at the headquarters of the research sector of the Elm Company. The results of the analyses carried out to estimate the crowd density in offices and the flows of the crowd from one place to another are promising and illustrate the importance of such solutions in indoor and closed spaces.