Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 용환승 | * |
dc.date.accessioned | 2017-03-10T01:03:47Z | - |
dc.date.available | 2017-03-10T01:03:47Z | - |
dc.date.issued | 2016 | * |
dc.identifier.isbn | 9781509014965 | * |
dc.identifier.other | OAK-20138 | * |
dc.identifier.uri | https://dspace.ewha.ac.kr/handle/2015.oak/234734 | - |
dc.description.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. | * |
dc.description.sponsorship | IEEE;IEEE New York Section;IEEE Region R1 | * |
dc.language | English | * |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | * |
dc.subject | Bluetooth low-energy beacon | * |
dc.subject | familiarity analysis | * |
dc.subject | indoor positioning | * |
dc.subject | intragroup analysis | * |
dc.title | Real-time intragroup familiarity analysis model using beacon based on proximity | * |
dc.type | Conference Paper | * |
dc.relation.index | SCOPUS | * |
dc.relation.journaltitle | 2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016 | * |
dc.identifier.doi | 10.1109/UEMCON.2016.7777869 | * |
dc.identifier.scopusid | 2-s2.0-85010297878 | * |
dc.author.google | Choi J.-I. | * |
dc.author.google | Yong H.-S. | * |
dc.contributor.scopusid | 용환승(7101899751) | * |
dc.date.modifydate | 20240322133226 | * |