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Authors: Muawya Habib Sarnoub Eldaw ; Mark Levene and George Roussos

Affiliation: Birkbeck and University of London, United Kingdom

Keyword(s): Presence Analytics, Density-based Clustering, Social-DBSCAN, WLAN Traces, Wireless Network Traces, Eduroam, Social Groups, Class Attendance, Human Presence, Learning Activity, Mobile Data, Mobile Users.

Abstract: We demonstrate how social density-based clustering of WLAN traces can be utilised to detect granular social groups of mobile users within a university campus. Furthermore, the ability to detect such social groups, which can be linked to the learning activities taking place at target locations, provides an invaluable opportunity to understand the presence and movement of people within such an environment. For example, the proposed density-based clustering procedure, which we call Social-DBSCAN, has real potential to support human mobility studies such as the optimisation of space usage strategies. It can automatically detect the academic term period, the classes, and the attendance data. From a large Eduroam log of an academic site, we chose as a proof concept, selected locations with known capacity for the evaluation of our proposed method, which we successfully utilise to detect the regular learning activities at those locations, and to provide accurate estimates about the attendanc e levels over the academic term period. (More)

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Paper citation in several formats:
Eldaw, M.; Levene, M. and Roussos, G. (2016). Presence Analytics: Density-based Social Clustering for Mobile Users. In Proceedings of the 13th International Joint Conference on e-Business and Telecommunications (ICETE 2016) - WINSYS; ISBN 978-989-758-196-0; ISSN 2184-3236, SciTePress, pages 52-62. DOI: 10.5220/0005970200520062

@conference{winsys16,
author={Muawya Habib Sarnoub Eldaw. and Mark Levene. and George Roussos.},
title={Presence Analytics: Density-based Social Clustering for Mobile Users},
booktitle={Proceedings of the 13th International Joint Conference on e-Business and Telecommunications (ICETE 2016) - WINSYS},
year={2016},
pages={52-62},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005970200520062},
isbn={978-989-758-196-0},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on e-Business and Telecommunications (ICETE 2016) - WINSYS
TI - Presence Analytics: Density-based Social Clustering for Mobile Users
SN - 978-989-758-196-0
IS - 2184-3236
AU - Eldaw, M.
AU - Levene, M.
AU - Roussos, G.
PY - 2016
SP - 52
EP - 62
DO - 10.5220/0005970200520062
PB - SciTePress