| アイテムタイプ |
共通アイテムタイプ(1) |
| 公開日 |
2025-08-08 |
| タイトル |
|
|
タイトル |
Method for Reliable Detection of Vehicles with Location Information Errors in Spatio-Temporal Data Retention System |
|
言語 |
en |
| その他のタイトル |
|
|
その他のタイトル |
Reliable detection method for location malfunction vehicles in Spatio-Temporal Data Retention System |
|
言語 |
en |
| 著者 |
Takabe, Tatsuya
Yamamoto, Hiroshi
野林, 大起
池永, 全志
塚本, 和也
|
| 著作権関連情報 |
|
|
権利情報 |
Copyright (c) 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG. This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes on Data Engineering and Communications Technologies. The final authenticated version is available online at: https://doi.org/10.1007/978-3-031-72322-3_41. |
|
言語 |
en |
| 抄録 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
Some types of Internet of Things data depend on the time and location at which they were generated. We refer to such data as spatio-temporal data (STD). To effectively utilize STD, we previously proposed an STD retention system called STD-RS that uses vehicles to retain STD within a specific area. In STD-RS, vehicles autonomously operate based on their location information. However, location information errors at vehicle nodes may lead to STD being distributed outside the target area. This could lead to an increase in packet loss and pose the risk of information leakage. Therefore, this study proposes a method for detecting vehicles with location information errors based on the attenuation of signal strength with distance. Specifically, the distance to vehicle nodes and the received signal strength obtained during STD distribution are collected and stored on multi-access edge computing servers. Machine learning is then applied to this information for detection. Simulations demonstrate that vehicles with location information errors can be detected with an accuracy of approximately 80%. |
|
言語 |
en |
| 備考 |
|
|
内容記述タイプ |
Other |
|
内容記述 |
The 16th International Conference on Intelligent Networking and Collaborative Systems (InCoS-2024), Workshop of The 16th International Workshop on Information Network Design (WIND-2024), September 19 - 21, 2024, Soonchunhyang (SCH) University, Asan, South Korea |
|
言語 |
en |
| 書誌情報 |
en : Lecture Notes on Data Engineering and Communications Technologies
巻 225,
p. 414-423,
発行日 2024-09-15
|
| 出版社 |
|
|
出版者 |
Springer |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 出版タイプ |
|
|
出版タイプ |
AM |
|
出版タイプResource |
http://purl.org/coar/version/c_ab4af688f83e57aa |
| DOI |
|
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
https://doi.org/10.1007/978-3-031-72322-3_41 |
| ISSN |
|
|
収録物識別子タイプ |
PISSN |
|
収録物識別子 |
2367-4512 |
| ISSN |
|
|
収録物識別子タイプ |
EISSN |
|
収録物識別子 |
2367-4520 |
| 会議記述 |
|
|
|
会議名 |
The 16th International Conference on Intelligent Networking and Collaborative Systems (InCoS-2024), Workshop of The 16th International Workshop on Information Network Design (WIND-2024) |
|
|
言語 |
en |
|
|
開始年 |
2024 |
|
|
開始月 |
09 |
|
|
開始日 |
19 |
|
|
終了年 |
2024 |
|
|
終了月 |
09 |
|
|
終了日 |
21 |
|
|
開催会場 |
Soonchunhyang (SCH) University |
|
|
言語 |
en |
|
|
開催地 |
Asan |
|
|
言語 |
en |
|
開催国 |
KOR |
| 研究者情報 |
|
|
URL |
https://hyokadb02.jimu.kyutech.ac.jp/html/218_ja.html |
| 研究者情報 |
|
|
URL |
https://hyokadb02.jimu.kyutech.ac.jp/html/81_ja.html |
| 論文ID（連携） |
|
|
値 |
10461716 |
| 連携ID |
|
|
値 |
14752 |
10461716.pdf (998 KB)
