Residential College | false |
Status | 已發表Published |
Ultra-Low Power Localization System Using Mobile Cloud Computing | |
Junjian Huang1; Yubin Zhao1; XiaoFan Li2; Cheng-Zhong Xu3 | |
2019-06 | |
Conference Name | 12th International Conference on Cloud Computing, CLOUD 2019 held as part of the Services Conference Federation |
Source Publication | CLOUD 2019: Cloud Computing – CLOUD 2019 |
Volume | 11513 |
Pages | 1-10 |
Conference Date | 25 June 2019 - 30 June 2019 |
Conference Place | San Diego, CA |
Country | USA |
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. |
Keyword | Energy Consumption Mobile Cloud Computing Bluetooth Indoor Localization |
DOI | 10.1007/978-3-030-23502-4_1 |
URL | View the original |
Indexed By | CPCI-S |
Language | 英語English |
WOS Research Area | Computer Science |
WOS Subject | Computer Science, Information Systems ; Computer Science, Theory & Methods |
WOS ID | WOS:000489897400001 |
Scopus ID | 2-s2.0-85068230581 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | Faculty of Science and Technology |
Corresponding Author | Yubin Zhao |
Affiliation | 1.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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