Item type |
SIG Technical Reports(1) |
公開日 |
2021-05-27 |
タイトル |
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タイトル |
Incremental BLE beacon placement optimization for crowd density monitoring applications |
タイトル |
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言語 |
en |
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タイトル |
Incremental BLE beacon placement optimization for crowd density monitoring applications |
言語 |
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言語 |
eng |
キーワード |
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主題Scheme |
Other |
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主題 |
位置推定,都市 |
資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_18gh |
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資源タイプ |
technical report |
著者所属 |
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Department of Computer Science, School of Engineering, Tokyo Institute of Technology |
著者所属 |
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Department of Computer Science, School of Engineering, Tokyo Institute of Technology |
著者所属 |
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The University of Tokyo |
著者所属 |
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Yahoo Japan Corporation |
著者所属 |
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Department of Computer Science, School of Engineering, Tokyo Institute of Technology |
著者所属(英) |
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en |
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Department of Computer Science, School of Engineering, Tokyo Institute of Technology |
著者所属(英) |
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en |
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Department of Computer Science, School of Engineering, Tokyo Institute of Technology |
著者所属(英) |
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en |
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The University of Tokyo |
著者所属(英) |
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en |
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Yahoo Japan Corporation |
著者所属(英) |
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en |
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Department of Computer Science, School of Engineering, Tokyo Institute of Technology |
著者名 |
Yang, Zhen
Masato, Sugasaki
Yoshihiro, Kawahara
Kota, Tsubouchi
Masamichi, Shimosaka
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著者名(英) |
Yang, Zhen
Masato, Sugasaki
Yoshihiro, Kawahara
Kota, Tsubouchi
Masamichi, Shimosaka
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論文抄録 |
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内容記述タイプ |
Other |
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内容記述 |
With the pandemic of COVID-19, indoor crowd density monitoring is on-demand by public service providers. Due to the fact that its performance on crowd density monitoring highly depends on how BLE beacons are allocated, BLE beacon placement optimization has been tackled as fundamental research work in the ubiquitous computing community. However, the previous researches focus on the batch optimization and ignore the actual workload to obtain the optimal placement result. In this research, we propose a novel approach to incrementally optimize the beacon placement by detecting the optimal placement of BLE sensors in favor of Bayesian optimization and determining the optimal location to place the beacon. Our proposed method can optimize the beacon placement effectively to improve the signal coverage quality in the given environment and also minimize the human workload. The experiment results on actual BLE sensing results show that our proposed method can provide over 13% area coverage than the average placement while reducing 67% optimization time. |
論文抄録(英) |
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内容記述タイプ |
Other |
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内容記述 |
With the pandemic of COVID-19, indoor crowd density monitoring is on-demand by public service providers. Due to the fact that its performance on crowd density monitoring highly depends on how BLE beacons are allocated, BLE beacon placement optimization has been tackled as fundamental research work in the ubiquitous computing community. However, the previous researches focus on the batch optimization and ignore the actual workload to obtain the optimal placement result. In this research, we propose a novel approach to incrementally optimize the beacon placement by detecting the optimal placement of BLE sensors in favor of Bayesian optimization and determining the optimal location to place the beacon. Our proposed method can optimize the beacon placement effectively to improve the signal coverage quality in the given environment and also minimize the human workload. The experiment results on actual BLE sensing results show that our proposed method can provide over 13% area coverage than the average placement while reducing 67% optimization time. |
書誌レコードID |
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収録物識別子タイプ |
NCID |
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収録物識別子 |
AA11838947 |
書誌情報 |
研究報告ユビキタスコンピューティングシステム(UBI)
巻 2021-UBI-70,
号 11,
p. 1-7,
発行日 2021-05-27
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ISSN |
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収録物識別子タイプ |
ISSN |
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収録物識別子 |
2188-8698 |
Notice |
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SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc. |
出版者 |
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言語 |
ja |
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出版者 |
情報処理学会 |