SociTrack: Infrastructure-free interaction tracking through mobile sensor networks

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Abstract

Social scientists, psychologists, and epidemiologists use empirical human interaction data to research human behaviour, social bonding, and disease spread. Historically, systems measuring interactions have been forced to choose between deployability and measurement fidelity—they operate only in instrumented spaces, under line-of-sight conditions, or provide coarse-grained proximity data. We introduce SociTrack, a platform for autonomous social interaction tracking via wireless distance measurements. Deployments require no supporting infrastructure and provide sub-second, decimeter-accurate ranging information over multiple days. The key insight that enables both deployability and fidelity in one system is to decouple node mobility and network management from range measurement, which results in a novel dual-radio architecture. SociTrack leverages an energy-efficient and scalable ranging protocol that is accurate to 14.8 cm (99th percentile) in complex indoor environments and allows our prototype to operate for 12 days on a 2000 mAh battery. Finally, to validate its deployability and efficacy, SociTrack is used by early childhood development researchers to capture caregiver-infant interactions.

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APA

Biri, A., Jackson, N., Thiele, L., Pannuto, P., & Dutta, P. (2020). SociTrack: Infrastructure-free interaction tracking through mobile sensor networks. In Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM (Vol. 2020-July, pp. 433–446). Association for Computing Machinery. https://doi.org/10.1145/3372224.3419190

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