Privacy-Friendly Wi-Fi-Based Occupancy Estimation with Minimal Resources

E. Makri, J. ten Brinke, R. Evers, P. Man and H. Olthof
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E. Makri: School of Governance, Law and Urban Development, Saxion University of Applied Sciences, Enschede, The Netherlands
J. ten Brinke: School of Creative Technology, Saxion University of Applied Sciences, Enschede, The Netherlands
R. Evers: School of Creative Technology, Saxion University of Applied Sciences, Enschede, The Netherlands
P. Man: School of Creative Technology, Saxion University of Applied Sciences, Enschede, The Netherlands
H. Olthof: School of Creative Technology, Saxion University of Applied Sciences, Enschede, The Netherlands

International Journal of Ambient Computing and Intelligence (IJACI), 2018, vol. 9, issue 4, 34-51

Abstract: Occupancy estimation is becoming an increasingly popular research topic, as solutions can be deployed both to the challenges of demand-driven ambient comfort control applications, and to the challenges of building safety and security. With this article, the authors aim to estimate the number of people in a particular area of a building, using only existing infrastructure. To achieve this, information is collected from the Wi-Fi Access Points installed throughout a building, in such a way that the privacy of the persons using the Wi-Fi resources remains intact. While several approaches have been proposed to address the occupancy question, the main contribution lies in that the solution uses only standard Wi-Fi infrastructure, already deployed in any modern building. In addition, the authors claim that their solution comes at virtually zero cost, as their mechanisms add negligible network traffic, using minimal network and processing resources, and it does not require specialised hardware.

Date: 2018
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