Building structure generation method by collecting and integrating indoor walking sensing data
| Project/Area Number |
16K00144
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Information network
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| Research Institution | Aichi Institute of Technology |
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Principal Investigator |
Kaji Katsuhiko 愛知工業大学, 情報科学部, 准教授 (40466412)
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| Co-Investigator(Kenkyū-buntansha) |
水野 忠則 愛知工業大学, 情報科学部, 教授 (80252162)
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| Project Period (FY) |
2016-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | PDR / スマートフォン / 歩行軌跡 / 建物構造 / 屋内位置推定 / 建物構造生成 / センサ / スマートセンサ情報システム |
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| Outline of Final Research Achievements |
In order to establish a method for generating a pedestrian network structure using indoor walking sensing data of multiple people, I conducted research with the following four sub-themes.
(I) Systematization of the concept of building-likeness, (II) Establishment of highly accurate walking trajectory estimation method, (III) Establishment of walking space network structure estimation method by integrating walking trajectories, (IV) Construction of a participatory sensing platform for collecting walking sensing data.
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| Academic Significance and Societal Importance of the Research Achievements |
複数人の歩行センシングデータを用いて建物構造を構築する，という研究は既に複数存在している．本研究の学術的な特色・独創的な点は，高精度の建物構造を構築するために，建物らしさという概念を体系化して利用する，という点である．申請者自身の研究を含め，幾つかの研究では建物らしさの一部（直線的な通路や直角の曲がり角などの制約）をアドホックに導入した研究は存在しているが，これまで計算機が理解可能なモデルとして建物らしさを表現し，それによって建物構造を自動構築した例はない．
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Report
(5 results)
Research Products
(24 results)
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[Presentation] Method to Improve Accuracy of Indoor PDR Trajectories Using a Large Amount of Trajectories2018
Author(s)
Yotsuya, K., Ito, N., Naito, K., Chujo, N., Mizuno, T., Kaji, K.
Organizer
International Conference on Mobile Computing and Ubiquitous Networking(ICMU2018)
Related Report
Int'l Joint Research
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[Presentation] Partial Matching Estimation Method of Walking Trajectories for Generating Indoor Pedestrian Networks2018
Author(s)
Sugimoto, S., Ito, N., Naito, K., Chujo, N., Mizuno, T., Kaji, K.
Organizer
International Conference on Mobile Computing and Ubiquitous Networking(ICMU2018)
Related Report
Int'l Joint Research
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[Presentation] Pedestrian Direction Estimation for Each Step Using Plane Component of Accelerometer2017
Author(s)
Shimizu, S., Ito, N., Naito, K., Chujo, N., Mizuno, T., Kaji, K.
Organizer
2017 Tenth International Conference on Mobile Computing and Ubiquitous Network (ICMU)
Related Report
Int'l Joint Research
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[Presentation] Detection of Half-turn Stairs from Walking Trajectories Estimated by Pedestrian Dead Reckoning2017
Author(s)
Kosuke, Y., Haruka, I., Nobuyuki, I., Katsuhiro, N., Naoya, C., Tadanori, M., Kaji, K.
Organizer
2017 Tenth International Conference on Mobile Computing and Ubiquitous Network (ICMU)
Related Report
Int'l Joint Research
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[Presentation] Multi-Algorithm On-Site Evaluation System for PDR Challenge2016
Author(s)
Kaji, K., Kanagu, K., Murao, K., Nishio, N., Urano, K., Iida, H., Kawaguchi, N.
Organizer
the Ninth International Conference on Mobile Computing and Ubiquitous Networking (ICMU2016)
Place of Presentation
Kaiserslautern, Germany
Year and Date
2016-10-04
Related Report
Int'l Joint Research
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