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Real-time intragroup familiarity analysis model using beacon based on proximity

Title
Real-time intragroup familiarity analysis model using beacon based on proximity
Authors
Choi J.-I.Yong H.-S.
Ewha Authors
용환승
SCOPUS Author ID
용환승scopus
Issue Date
2016
Journal Title
2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016
Citation
2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016
Keywords
Bluetooth low-energy beaconfamiliarity analysisindoor positioningintragroup analysis
Publisher
Institute of Electrical and Electronics Engineers Inc.
Indexed
SCOPUS scopus
Document Type
Conference Paper
Abstract
An analysis of the familiarity between users in a group requires large amounts of information. We could determine the degree of familiarity by using personal information gleaned from a social networking service. For a realtime service, we usually use video data. Unfortunately, this data is closely related to a user's privacy, so the user may feel uncomfortable about its use. Therefore, in this study, we set out to devise a real-time familiarity analysis model using a minimal amount of information and a Bluetooth low-energy beacon. Unlike the traditional approach, the devices receiving the beacon signal are placed on a desk, wall, or ceiling and the user carries a beacon. The beacon transmits only its ID and a received signal strength indication (RSSI) signal. Using the device for receiving the beacon signal, a user's location can be monitored so that the server can analyze the intragroup and calculate the degree of familiarity between users. This study addressed those situations arising in a party-like event, in a school, in a company, etc. to attempt to analyze the degree of familiarity by determining a person's location at specific times. This technology could also be applied to exhibitions, parks, and amusement parks to determine the most popular exhibits, spots, and facilities in real time. © 2016 IEEE.
DOI
10.1109/UEMCON.2016.7777869
ISBN
9781509014965
Appears in Collections:
인공지능대학 > 컴퓨터공학과 > Journal papers
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