Research Article
Next2Me: Capturing Social Interactions through Smartphone Devices using WiFi and Audio signals
@INPROCEEDINGS{10.4108/eai.7-11-2017.2274985, author={Jon Baker and Christos Efstratiou}, title={Next2Me: Capturing Social Interactions through Smartphone Devices using WiFi and Audio signals}, proceedings={14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services}, publisher={ACM}, proceedings_a={MOBIQUITOUS}, year={2018}, month={4}, keywords={smartphone sensing social sensing wifi audio}, doi={10.4108/eai.7-11-2017.2274985} }- Jon Baker
Christos Efstratiou
Year: 2018
Next2Me: Capturing Social Interactions through Smartphone Devices using WiFi and Audio signals
MOBIQUITOUS
ACM
DOI: 10.4108/eai.7-11-2017.2274985
Abstract
Typical approaches in detecting social interactions consider the use of co-location as a proxy for real-world interactions. Such approaches can under-perform 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).
