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Next2Me: Capturing Social Interactions through Smartphone Devices using WiFi and Audio signals

Baker, Jon, Efstratiou, Christos (2017) Next2Me: Capturing Social Interactions through Smartphone Devices using WiFi and Audio signals. In: Proceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. . pp. 412-421. ACM ISBN 978-1-4503-5368-7. (doi:10.1145/3144457.3144500) (KAR id:63969)


Typical approaches in detecting social interactions consider the use of co-location as a proxy for real-world interactions. Such approaches can underperform in challenging situations where multiple social interactions can occur in close proximity to each other. In this paper, we present a novel approach to detect co-located social interactions using smartphones. Next2Me relies on the use of WiFi signals and audio signals to accurately distinguish social groups interacting within a few meters from each other. Through a range of real-world experiments, we demonstrate a technique that utilises WiFi fingerprinting, along with sound fingerprinting to identify social groups. Experimental results show that Next2Me can achieve a precision of 88% within noisy environments, including smartphones that are placed in users’ pockets, whilst maintaining a very low energy footprint (<3% of battery capacity per day).

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1145/3144457.3144500
Uncontrolled keywords: Smartphone sensing, social sensing, WiFi, audio
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Christos Efstratiou
Date Deposited: 12 Oct 2017 13:10 UTC
Last Modified: 09 Dec 2022 07:14 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

Baker, Jon.

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Efstratiou, Christos.

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