研究者業績
Profile Information
- Affiliation
- Professor, Graduate School of Engineering, University of Hyogo
- Degree
- Doctor of Engineering, Ph.D(Dec, 1995, University of Tokyo)
- J-GLOBAL ID
- 201801006797934700
- researchmap Member ID
- B000299957
Research Interests
3Research Areas
1Research History
9-
2023 - Present
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2019 - Present
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Oct, 2006 - Present
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Apr, 2005 - Present
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Apr, 2003 - Present
Education
1-
Apr, 1980 - Mar, 1984
Committee Memberships
12-
2024 - Present
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Nov, 2018 - Present
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Apr, 2014 - Present
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Apr, 2005 - Present
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2013 - Mar, 2024
Awards
2-
Sep, 2005
Papers
91-
IEICE Communications Express, 1-4, 2024
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IEICE Communications Express, 12(10) 564-567, Oct, 2023
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J106-B(4) 260-263, Apr 1, 2023 Peer-reviewedIn this study, transmission coils were placed in a metallic enclosure with an open surface, and the near magnetic field leaking from the enclosure was investigated. In addition, a perforated metal plate that can improve the electromagnetic shielding effect was considered.
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IEICE Communications Express, 12(3) 66-71, Mar 1, 2023 Peer-reviewedThe fingerprint technique is used as an indoor localization method. This study uses a CNN-based indoor fingerprint localization method. The estimation accuracy of CNN improves as the number of AP information (AP identifiers and received signal strength indicator) increases. However, gathering AP information is time-consuming and costly. The problem can be solved using UD (AP information users measured). However, the UD measuring method does not know the user’s exact location. Therefore, it is essential to choose UD that is accurately estimate and use it for CNN training. In this study, we propose a method for selecting UDs that makes use of the RSSI similarity between AP information and UD.
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IEICE COMMUNICATIONS EXPRESS, 11(10) 673-678, Oct, 2022 Peer-reviewedIn this study, we performed indoor location estimation using wireless LAN. The estimation method is based on the Finger Print method [1]. We measure the database (DB) and user data (UD) using wireless LAN radio waves to improve the location estimation accuracy of Finger Print indoor location estimation. The Neural Network (NN) that compares UD and DB is ResNet (Residual Network), which is a derivative of CNN (Convolutional Neural Network). The number of layers that provide the best accuracy varies depending on the environment. To confirm this, we experimentally verified the relationship between the number of layers and the estimation accuracy in different environments, and clarified the design method.
Misc.
329-
IEICE Proceeding Series, 72 S12-5, Nov 29, 2022With the recent expansion of electromagnetic (EM) waves, undesired EM waves generated by device can cause malfunctions of other electronic equipment and communication failure. EM wave absorbers are widely used as countermeasures against these problems. Therefore, EMC (Electromagnetic Compatibility) technology is reguired to improve the electromagnetic environment. In this study, a microwave metamaterial EM wave absorbers using a sheet with a periodic array of square metal patterns were designed and its reflection characteristics at vertical incidence were experimentally evaluated.
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IEICE Proceeding Series, 72 O3-4, Nov 29, 2022This contribution focuses on the accuracy and measurement cost of indoor Area Estimation using wireless LAN. The system estimates the area, such as a room or a shopping store, where the user is located. The user-measured AP information (UD), and the pre-measured AP information (DB) are used in the FP method. In the previous study, RSSI probability distributions were obtained from the measured DB and UD. The area with the largest overlap in probability distribution was selected as the estimation result. In this study, we propose Area Estimation by CNN using data measured while walking at various locations within an area. The method using CNN improved the estimation accuracy compared to conventional Area Estimation. Moreover, the method measuring AP information while walking reduced the measurement time.
Books and Other Publications
9
Presentations
305Major Teaching Experience
14Professional Memberships
4Research Projects
3-
Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C), Japan Society for the Promotion of Science, Apr, 2021 - Mar, 2024
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SCOPE, 総務省, 2021 - 2022
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SCOPE, 総務省, 2013 - 2015