Together or alone: Detecting group mobility with wireless fingerprints
Journal
IEEE International Conference on Communications
ISBN
9781467389990
Date Issued
2017-07-28
Author(s)
Solmaz, Gurkan
Abstract
This paper proposes a novel approach for detecting groups of people that walk 'together' (group mobility) as well as the people who walk 'alone' (individual movements) using wireless signals. We exploit multiple wireless sniffers to pervasively collect human mobility data from people with mobile devices and identify similarities and the group mobility based on the wireless fingerprints. We propose a method which initially converts the wireless packets collected by the sniffers into people's wireless fingerprints. The method then determines group mobility by finding the statuses of people at certain times (dynamic/static) and the space correlation of dynamic people. To evaluate the feasibility of our approach, we conduct real world experiments by collecting data from 10 participants carrying Bluetooth Low Energy (BLE) beacons in an office environment for a two-week period. The proposed approach captures space correlation with 95% and group mobility with 79% accuracies on average. With the proposed approach we successfully 1) detect the groups and individual movements and 2) generate social networks based on the group mobility characteristics.
Subjects
crowd mobility | human mobility | internet of things | social networks; Computer Science - Networking and Internet Architecture; Computer Science - Networking and Internet Architecture; eess.SP
Description
This work has received funding from the European Union's Horizon 2020
research and innovation programme within the project "Worldwide
Interoperability for SEmantics IoT" under grant agreement Number 723156
research and innovation programme within the project "Worldwide
Interoperability for SEmantics IoT" under grant agreement Number 723156
Type
conference paper