A Machine Learning Approach for Estimating Person Counts Using Anonymous WiFi Data in a University Library

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Project publication · Sensors

Summary

The article estimates occupancy in a university library using anonymized WiFi data and machine-learning techniques.

Flujo de trabajo para estimar ocupación mediante datos WiFi anonimizados
Figure from the original article. Source: Sensors/MDPI, reproduced without modification under CC BY 4.0.

Authors: Lucio Hernando-Cánovas, Alejandro S. Martínez-Sala, Juan C. Sánchez-Aarnoutse, Juan J. Alcaraz

Journal: Sensors

DOI: 10.3390/s25227065

Funding: PID2023-148214OB-C21.

UPCT Repository: http://hdl.handle.net/10317/23388

Bibliometric indicators

JCR quartileQ2
Impact factor3.5
Google Scholar citations0
JCR area
Engineering, Electrical & Electronic
JCR year
2024
Scholar query
21 May 2026

Main contribution

The proposal shows that connectivity traces can become a useful signal for estimating people presence while preserving privacy. The approach combines low cost, already available data and models able to capture patterns in how spaces are used.

Link with BoND1

BoND1 studies IoT connectivity as a source of operational information, not only as a communication channel. This publication connects with that vision by using network data to obtain contextual knowledge in smart environments.

DOI UPCT Repository
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