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Ultra-Low Power Localization System Using Mobile Cloud Computing
Junjian Huang1; Yubin Zhao1; XiaoFan Li2; Cheng-Zhong Xu3
2019-06
Conference Name12th International Conference on Cloud Computing, CLOUD 2019 held as part of the Services Conference Federation
Source PublicationCLOUD 2019: Cloud Computing – CLOUD 2019
Volume11513
Pages1-10
Conference Date25 June 2019 - 30 June 2019
Conference PlaceSan Diego, CA
CountryUSA
Abstract

In the existing positioning system based on bluetooth (BT), the interference of the positioning device signal, the slow processing speed of the positioning data and the large energy consumption of the positioning device affect the system positioning accuracy and service quality. In this paper, we propose an Ultra-Low power indoor localization system using mobile cloud computing. The mobile cloud server reduces the signal interference of the positioning device, improves the positioning accuracy and reduces the system energy consumption by controlling the working mode of the positioning device. A simultaneous localization and power adaptation scheme is developed. In the real experiment evaluation, our proposed system can localize the area of a terminal located within 3 m distance with 98% accuracy and average positioning error less then 1.55 m. Compare with other BLE system, 97% average energy consumption of our system is reduced.

KeywordEnergy Consumption Mobile Cloud Computing Bluetooth Indoor Localization
DOI10.1007/978-3-030-23502-4_1
URLView the original
Indexed ByCPCI-S
Language英語English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Information Systems ; Computer Science, Theory & Methods
WOS IDWOS:000489897400001
Scopus ID2-s2.0-85068230581
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Citation statistics
Document TypeConference paper
CollectionFaculty of Science and Technology
Corresponding AuthorYubin Zhao
Affiliation1.Shenzhen Institutes of Advanced Technology, Chinese Academy of Science, Shenzhen, China
2.State Radio Monitoring Center Testing Center, Beijing, China
3.3 State Key Lab of IoTSC, Department of Computer and Information Science, University of Macau, Macau, Macao, Special Administrative Region of China
Recommended Citation
GB/T 7714
Junjian Huang,Yubin Zhao,XiaoFan Li,et al. Ultra-Low Power Localization System Using Mobile Cloud Computing[C], 2019, 1-10.
APA Junjian Huang., Yubin Zhao., XiaoFan Li., & Cheng-Zhong Xu (2019). Ultra-Low Power Localization System Using Mobile Cloud Computing. CLOUD 2019: Cloud Computing – CLOUD 2019, 11513, 1-10.
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