Registo de Dados de Investigação

MoniCrowd: A Real-World WiFi Probe Labelled Dataset with Device-Level Ground Truth

This dataset, released under the MoniCrowd project, provides a real-world and controlled collection of WiFi probe request traces designed to support research in crowd sensing, device fingerprinting, and privacy-preserving wireless analytics.

The dataset combines high-fidelity labelled data collected in a controlled laboratory environment, performed inside a custom-designed Faraday cage to ensure electromagnetic isolation and eliminate external interference, enabling the generation of reliable ground truth at the device level. Each device was individually characterized, with per-device packet capture (PCAP) traces and associated metadata including brand, model, operating system, and operating system version.

The dataset is intended to support reproducible research in areas such as crowd monitoring, wireless device fingerprinting, anomaly detection, and machine learning-based identification methods.

To the best of our knowledge, this is one of the largest publicly available datasets combining per-device PCAP traces and multi-level device ground truth.

The dataset is accompanied by processing scripts and documentation to facilitate reuse and benchmarking by the research community.

WiFi Probe Requests; Device Fingerprinting; Crowd Sensing; Ground Truth Data; Packet Capture (PCAP);
Nome do Ficheiro Tamanho Ficheiro
CITATION.cff 1 KB
LICENSE 0 KB
README.md 3 KB
monicrowd-dataset.zip 7026 KB
Nome Afiliação ORCID
Martins, Miguel Iscte – Instituto Universitário de Lisboa 0009-0003-2922-1771
Nunes de Oliveira, João Pedro Iscte – Instituto Universitário de Lisboa 0009-0003-7675-5290
Neto Marinheiro, Rui Iscte – Instituto Universitário de Lisboa 0000-0002-0385-8876
Brito e Abreu, Fernando Iscte – Instituto Universitário de Lisboa 0000-0002-9086-4122
Nome Afiliação ORCID Tipo de Contribuidor
Vieira, Tiago Iscte – Instituto Universitário de Lisboa 0009-0006-6657-6039 Other
Santos, Tomás 0009-0004-0255-8638 Other
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Ano Tipo de publicação Título da publicação
2025 Publicação em atas de evento científico Adaptive crowd sensing with privacy-preserving WiFi fingerprinting
2025 Publicação em atas de evento científico Building optimized wireless pedestrian counting sensors combining passive and active technologies

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