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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
- 용환승
- 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 beacon; familiarity analysis; indoor positioning; intragroup analysis
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Indexed
- 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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