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■論文No. |
CMN24021 |
■ページ数 |
6ページ |
■発行日
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2024/03/25 |
■タイトル |
Indoor Localization Method Based on the Analyses of Surrounding Wi-Fi Access Points Using ChatGPT |
■タイトル(英語) |
Indoor Localization Method Based on the Analyses of Surrounding Wi-Fi Access Points Using ChatGPT |
■著者名 |
Rahmadya Budi (Andalas University),Takeda Shigeki(Ibaraki University),Sun Ran(Ibaraki University),Song Zequn(Ibaraki University),Kumara Hadi Danang(Ibaraki University) |
■著者名(英語) |
Budi Rahmadya(Andalas University),Shigeki Takeda(Ibaraki University),Ran Sun(Ibaraki University),Zequn Song(Ibaraki University),Danang Kumara Hadi(Ibaraki University) |
■価格 |
会員 ¥440 一般 ¥660 |
■書籍種類 |
研究会(論文単位) |
■グループ名 |
【C】電子・情報・システム部門 通信研究会 |
■本誌 |
2024年3月28日-2024年3月29日通信研究会
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■本誌掲載ページ |
25-30ページ |
■原稿種別 |
英語 |
■電子版へのリンク |
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■キーワード |
Indoor localization|Wi-Fi|ChatGPT|RTLS|AI/ML|ISAC|Indoor localization|Wi-Fi|ChatGPT|RTLS|AI/ML|ISAC |
■要約(日本語) |
Argent demands on indoor real-time localization systems (RTLS) are accelerating research and developments on these technologies. Recent advances in Wi-Fi technologies, including Wi-Fi 6 and 7, further facilitate the development of RTLS technologies by utilizing wireless communications and artificial intelligence/machine learning (AI/ML) technologies. These research and development activities also accelerate future wireless communication for achieving the integrated sensing and communication (ISAC) concept. The recent developments in Wi-Fi technologies have led to increased numbers of APs for gaining reliable wireless links. Therefore, we observe a large number of SSIDs in workplaces, office environments, and homes. These situations enable exploiting observed Wi-Fi information for localizations. This paper proposed an indoor localization method based on analyzing surrounding Wi-Fi access points using ChatGPT. The experiments validated that ChatGPT provided corresponding room names to the given unknown Wi-Fi logs, based on analyzing Wi-Fi logs observed in priori in individual rooms. |
■要約(英語) |
Argent demands on indoor real-time localization systems (RTLS) are accelerating research and developments on these technologies. Recent advances in Wi-Fi technologies, including Wi-Fi 6 and 7, further facilitate the development of RTLS technologies by utilizing wireless communications and artificial intelligence/machine learning (AI/ML) technologies. These research and development activities also accelerate future wireless communication for achieving the integrated sensing and communication (ISAC) concept. The recent developments in Wi-Fi technologies have led to increased numbers of APs for gaining reliable wireless links. Therefore, we observe a large number of SSIDs in workplaces, office environments, and homes. These situations enable exploiting observed Wi-Fi information for localizations. This paper proposed an indoor localization method based on analyzing surrounding Wi-Fi access points using ChatGPT. The experiments validated that ChatGPT provided corresponding room names to the given unknown Wi-Fi logs, based on analyzing Wi-Fi logs observed in priori in individual rooms. |
■版 型 |
A4 |
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