Beacon-based active media control interface in indoor ubiquitous computing environment
- Authors
- Sung, Yunsick; Jeong, Young-Sik; Park, Jong Hyuk
- Issue Date
- Mar-2016
- Publisher
- SPRINGER
- Keywords
- Active media control; NUI/NUX; Natural user interface; Natural user experience; Ubiquitous cluster computing
- Citation
- CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, v.19, no.1, pp 547 - 556
- Pages
- 10
- Indexed
- SCIE
SCOPUS
- Journal Title
- CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
- Volume
- 19
- Number
- 1
- Start Page
- 547
- End Page
- 556
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/18082
- DOI
- 10.1007/s10586-016-0532-6
- ISSN
- 1386-7857
1573-7543
- Abstract
- In ubiquitous computing, diverse media technologies have recently been extensively researched and applied to various fields. The goal of media technologies is to improve our daily lives by enabling us to control activemedia devices such as smart phones, tablets, and TVs. The locations of users are important to providing a variety of services to users. In addition, given that all devices cannot be simultaneously utilized, and only one device is sometimes being used, the location information can be utilized to help determine one of the core active media devices at a specific instant in time. This paper proposes an active media-control interface that is based on location recognition methods using beacons in indoor ubiquitous computing. In the proposed environment, users have a beacon that denotes the location of each user. The one that is the nearest from the beacon is selected from among multiple active media devices for servicing. In the experiments, four access points and one beacon was used to validate the proposed method. The advantage of the proposed method is that it enables us to apply active media technology to indoor environments. By recognizing user locations in indoor environments, several kinds of active media services become available.
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Collections - College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

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