Detailed Information

Cited 0 time in webofscience Cited 3 time in scopus
Metadata Downloads

Improved location estimation method of trilateration in ubiquitous computing indoor environment

Full metadata record
DC Field Value Language
dc.contributor.authorKwak, Jeonghoon-
dc.contributor.authorJang, Hyunseok-
dc.contributor.authorSung, Yunsick-
dc.contributor.authorJeong, Young-Sik-
dc.date.accessioned2024-08-08T08:00:59Z-
dc.date.available2024-08-08T08:00:59Z-
dc.date.issued2015-12-
dc.identifier.issn1876-1100-
dc.identifier.issn1876-1119-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/20008-
dc.description.abstractEstimating the location of users, Unmanned Aerial Vehicles (UAVs), and devices is the key to provide the diverse kinds of services in ubiquitous computing environments. Given that Global Positioning System (GPS) cannot be utilized in indoor environments, beacon-based and vision-based location estimation approaches are utilized. However, the accuracy of the location does not reaches the demanded amount. This paper propose an indoor location estimation method of beacons based on trilateration. By utilizing three APs and three beacons, the location of one of beacons can be predicted accurately. In the experiment, the proposed method was compared with the traditional trilateration method. Comparing to the result of the traditional trilateration method, the proposed method reduced the distance errors to about 20%. © Springer Science+Business Media Singapore 2015.-
dc.format.extent5-
dc.language영어-
dc.language.isoENG-
dc.publisherSpringer Verlag-
dc.titleImproved location estimation method of trilateration in ubiquitous computing indoor environment-
dc.typeArticle-
dc.publisher.location독일-
dc.identifier.doi10.1007/978-981-10-0281-6_24-
dc.identifier.scopusid2-s2.0-84951292511-
dc.identifier.bibliographicCitationLecture Notes in Electrical Engineering, v.373, pp 165 - 169-
dc.citation.titleLecture Notes in Electrical Engineering-
dc.citation.volume373-
dc.citation.startPage165-
dc.citation.endPage169-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordAuthorBeacon-
dc.subject.keywordAuthorDrone-
dc.subject.keywordAuthorIndoor location-
dc.subject.keywordAuthorTrilateration-
dc.subject.keywordAuthorUAV-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Jeong, Young Sik photo

Jeong, Young Sik
College of Advanced Convergence Engineering (Department of Computer Science and Artificial Intelligence)
Read more

Altmetrics

Total Views & Downloads

BROWSE