This paper presents a mobile crowdsensing approach to identify the indoor points of interest (POI) by exploiting Wi-Fi similarity measurements. Since indoor environments are lacking the GPS positioning accuracy when compared to outdoors, we rely on widely available Wi-Fi access points (AP) in contemporary urban indoor environments, to accurately identify user POI. We propose a smartphone application based system architecture to scan the surrounding Wi-Fi AP and measure the cosine similarity of received signal strengths (RSS), and demonstrate through the experimental results that it is possible to identify the distinct POI of users, and the common POI among users of a given indoor environment.
@article{arxiv.1908.08929,
title = {Identifying Indoor Points of Interest via Mobile Crowdsensing: An Experimental Study},
author = {Sumudu Hasala Marakkalage and Ran Liu and Sanjana Kadaba Viswanath and Chau Yuen},
journal= {arXiv preprint arXiv:1908.08929},
year = {2019}
}
Comments
16th IEEE Asia Pacific Wireless Communications Symposium (APWCS 2019), 28-30 August 2019, Singapore University of Technology and Design, Singapore