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

Jung In Choi; Hwan Seung Yong

doi:10.1109/UEMCON.2016.7777869

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

Jung In Choi, Hwan Seung Yong

Department of Computer Science & Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

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.

Original language	English
Title of host publication	2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016
Editors	Himadri Nath Saha, Satyajit Chakrabarti
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509014965
DOIs	https://doi.org/10.1109/UEMCON.2016.7777869
State	Published - 7 Dec 2016
Event	7th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016 - New York City, United States Duration: 20 Oct 2016 → 22 Oct 2016

Publication series

Name	2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016

Conference

Conference	7th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016
Country/Territory	United States
City	New York City
Period	20/10/16 → 22/10/16

Bibliographical note

Funding Information:
This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, Science and Technology(2012R1A1A2003764)

Publisher Copyright:
© 2016 IEEE.

Keywords

Bluetooth low-energy beacon
familiarity analysis
indoor positioning
intragroup analysis

Access to Document

10.1109/UEMCON.2016.7777869

Cite this

Choi, J. I., & Yong, H. S. (2016). Real-time intragroup familiarity analysis model using beacon based on proximity. In H. N. Saha, & S. Chakrabarti (Eds.), 2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016 Article 7777869 (2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/UEMCON.2016.7777869

Choi, Jung In ; Yong, Hwan Seung. / Real-time intragroup familiarity analysis model using beacon based on proximity. 2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016. editor / Himadri Nath Saha ; Satyajit Chakrabarti. Institute of Electrical and Electronics Engineers Inc., 2016. (2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016).

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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.",

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Choi, JI & Yong, HS 2016, Real-time intragroup familiarity analysis model using beacon based on proximity. in HN Saha & S Chakrabarti (eds), 2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016., 7777869, 2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016, Institute of Electrical and Electronics Engineers Inc., 7th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016, New York City, United States, 20/10/16. https://doi.org/10.1109/UEMCON.2016.7777869

Real-time intragroup familiarity analysis model using beacon based on proximity. / Choi, Jung In; Yong, Hwan Seung.
2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016. ed. / Himadri Nath Saha; Satyajit Chakrabarti. Institute of Electrical and Electronics Engineers Inc., 2016. 7777869 (2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Choi JI, Yong HS. Real-time intragroup familiarity analysis model using beacon based on proximity. In Saha HN, Chakrabarti S, editors, 2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7777869. (2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016). doi: 10.1109/UEMCON.2016.7777869

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

Abstract

Publication series

Conference

Bibliographical note

Keywords

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