| 研究課題/領域番号 |
22K12011
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| 研究種目 |
基盤研究(C)
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| 配分区分 | 基金 |
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| 応募区分 | 一般 |
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| 審査区分 |
小区分60060:情報ネットワーク関連
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| 研究機関 | 大阪大学 |
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研究代表者 |
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| 研究期間 (年度) |
2022-04-01 – 2025-03-31
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| 研究課題ステータス |
交付 (2022年度)
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| 配分額 *注記 |
4,160千円 (直接経費: 3,200千円、間接経費: 960千円)
2024年度: 650千円 (直接経費: 500千円、間接経費: 150千円)
2023年度: 1,170千円 (直接経費: 900千円、間接経費: 270千円)
2022年度: 2,340千円 (直接経費: 1,800千円、間接経費: 540千円)
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| キーワード | Localization / Applied Machine Learning / Ubiquitous Computing / Wireless Networks / Spatial Intelligence / Geo-spatial science / Mobile Computing / Deep Learning |
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| 研究開始時の研究の概要 |
#1-study of existing methods. -Collecting and analyzing data.
#2-Designing and Implementing techniques that realize the concept. -Writing papers and preparing demos.
#3-Handling the different practical aspects. -Writing international papers and preparing demos.
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| 研究実績の概要 |
We conducted a comprehensive literature review to identify state-of-the-art approaches and establish a strong research foundation. We established three testbeds with WiFi access points and mobile devices, providing a reliable infrastructure for our experiments. Mobile App was developed to collect data using different android phones and individuals, ensuring robust findings. Data analysis techniques revealed insights into the relationship between user location and WiFi signal propagation, considering hardware diversity. We also developed methods to address the localization challenges in different scenarios. Rigorous validation processes were employed to ensure the reliability of our results. We published papers in reputable international journals and presented at top-tier conferences.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
1: 当初の計画以上に進展している
理由
We held a lot of experiments and hired students for data collection purposes. Additionally, I collaborated with my colleagues at Osaka University and also top worldwide researchers. As a result, the progress was very smooth, and we had a lot of achievements so far.
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| 今後の研究の推進方策 |
For the next year, the plan of the research scheme is to further advance the project by: 1) expanding the number of testbeds to include additional indoor environments. This will provide a more diverse datasets. 2) Enhancing the Data Collection by collecting data with more modalities that the reflects the smartphone's capabilities and modern technology. 3) Build upon the analysis conducted in the previous year by refining and expanding the analytical techniques used to gain deeper insights into the collected data and extract valuable information for indoor positioning. 4) Extend the research by investigating the validity additional methods and techniques for indoor positioning. Staying up-to-date with the latest literature and advancements in the field, and consider exploring emerging technologies sensor fusion algorithms to enhance the accuracy and efficiency of the proposed positioning system. 5) Engaging with other researchers and experts in the field through collaborations and discussions. This collaboration can help validate our work, uncover potential improvements, and identify novel research directions. Write More Research Papers: Continue writing research papers based on the new findings and advancements that will be made. Then submit these papers to reputable journals and conferences in the field. 6) Prepare Demonstrations/prototypes of our achievements. 7) Attending conferences, workshops, and seminars relevant to this research area to exposure to the latest developments, network with other researchers, and present our findings.
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