Indoor Crowd Density Estimation Through Mobile Smartphone Wi-Fi Probes

Xiaoyong Tang, Bin Xiao, Kenli Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)


Crowd density estimation is one of the critical issues in social activities. The traditional solution to this problem is to leverage video surveillance to monitor a crowd. However, this is not accurate for crowd density estimation because it is still hard to identify people from background. In the past few years, more and more people use Wi-Fi enabled smartphones. Smartphones can send Wi-Fi request packets periodically, even when they are not connected to access points. This gives another promising solution to the crowd density estimation even for the public environment. In this paper, we first develop a Wi-Fi monitor detection that can capture smartphone passive Wi-Fi signal information including MAC address and received signal strength indicator. Then, we propose a positioning algorithm based on smartphone passive Wi-Fi probe and a dynamic fingerprint management strategy. In real-world public social activities, a person may have zero, one, two, or multiple smartphones with variant Wi-Fi signals. Therefore, we design a method of computing the probability of a user generating one Wi-Fi signal to identify people population. Finally, we propose a crowd density estimation solution based on Wi-Fi probe packets positioning algorithm. Experiments were conducted in an indoor laboratory class and three public social activities, clearly demonstrated that the proposed solution can effectively and accurately estimate crowd density.

Original languageEnglish
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Publication statusAccepted/In press - 25 Apr 2018


  • Crowd density
  • Estimation
  • Feature extraction
  • Heuristic algorithms
  • indoor positioning algorithm
  • Monitoring
  • Probes
  • received signal strength indicator (RSSI)
  • smartphones
  • Wi-Fi probe
  • Wireless communication
  • Wireless fidelity

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


Dive into the research topics of 'Indoor Crowd Density Estimation Through Mobile Smartphone Wi-Fi Probes'. Together they form a unique fingerprint.

Cite this