Abstract
In this paper, we have reported an effective model for familiarity analysis in indoor environments based on proximity and direction. We employ the positioning data of users; thus, we avoid recording the action or any conversation pertaining to the users. We use the beacon signal to find a user’s location and choose a subgroup, which is a temporary group obtained using the location of the users. The proposed method analyzes the familiarity using two different methods. The proximity-based method is used to calculate the familiarity based on the time for which the user has stayed in the subgroup. The direction-based method is used to calculate the familiarity based on the direction of each user in the subgroup. This study addressed situations arising in an event or a group activity in indoors to analyze the degree of familiarity by determining the location of a user.
Original language | English |
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Title of host publication | Proceedings of the 7th International Conference on Emerging Databases - Technologies, Applications, and Theory |
Editors | Wonik Choi, Wookey Lee, Min Song, Sungwon Jung |
Publisher | Springer Verlag |
Pages | 309-318 |
Number of pages | 10 |
ISBN (Print) | 9789811065194 |
DOIs | |
State | Published - 2018 |
Event | 7th International Conference on Emerging Databases: Technologies, Applications, and Theory, EDB 2017 - Busan, Korea, Republic of Duration: 7 Aug 2017 → 9 Aug 2017 |
Publication series
Name | Lecture Notes in Electrical Engineering |
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Volume | 461 |
ISSN (Print) | 1876-1100 |
ISSN (Electronic) | 1876-1119 |
Conference
Conference | 7th International Conference on Emerging Databases: Technologies, Applications, and Theory, EDB 2017 |
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Country/Territory | Korea, Republic of |
City | Busan |
Period | 7/08/17 → 9/08/17 |
Bibliographical note
Publisher Copyright:© 2018, Springer Nature Singapore Pte Ltd.
Keywords
- Bluetooth low-energy beacon
- Familiarity analysis
- Indoor positioning
- Subgroup analysis