{"title":"可见光无线定位系统中的机器学习研究进展","authors":"Pan Zhu, Shibo Gong, Xuerui Zhao, Xinhuan Sun","doi":"10.1109/INSAI56792.2022.00032","DOIUrl":null,"url":null,"abstract":"In the era of solid development of artificial intelligence, the combination of machine learning methods and wireless localization systems has led researchers to new research ideas to improve the performance of wireless localization in space and the plane. In this paper, we describe wireless localization systems and related traditional localization methods, in addition to classifying and analyzing a summary of machine learning methods in recent related localization problems. The performance of wireless localization systems is evaluated according to three traditional classifications of machine learning: supervised, unsupervised, and deep learning. We also provide insight into the algorithms used in machine learning and wireless localization system-related articles over the years. Finally, we provide an overview summary of wireless localization systems based on machine learning methods and give directions for the future development of wireless optical localization systems.","PeriodicalId":318264,"journal":{"name":"2022 2nd International Conference on Networking Systems of AI (INSAI)","volume":"327 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Review: Machine Learning in Visible Light Wireless Positioning System\",\"authors\":\"Pan Zhu, Shibo Gong, Xuerui Zhao, Xinhuan Sun\",\"doi\":\"10.1109/INSAI56792.2022.00032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the era of solid development of artificial intelligence, the combination of machine learning methods and wireless localization systems has led researchers to new research ideas to improve the performance of wireless localization in space and the plane. In this paper, we describe wireless localization systems and related traditional localization methods, in addition to classifying and analyzing a summary of machine learning methods in recent related localization problems. The performance of wireless localization systems is evaluated according to three traditional classifications of machine learning: supervised, unsupervised, and deep learning. We also provide insight into the algorithms used in machine learning and wireless localization system-related articles over the years. Finally, we provide an overview summary of wireless localization systems based on machine learning methods and give directions for the future development of wireless optical localization systems.\",\"PeriodicalId\":318264,\"journal\":{\"name\":\"2022 2nd International Conference on Networking Systems of AI (INSAI)\",\"volume\":\"327 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 2nd International Conference on Networking Systems of AI (INSAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INSAI56792.2022.00032\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Conference on Networking Systems of AI (INSAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INSAI56792.2022.00032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Review: Machine Learning in Visible Light Wireless Positioning System
In the era of solid development of artificial intelligence, the combination of machine learning methods and wireless localization systems has led researchers to new research ideas to improve the performance of wireless localization in space and the plane. In this paper, we describe wireless localization systems and related traditional localization methods, in addition to classifying and analyzing a summary of machine learning methods in recent related localization problems. The performance of wireless localization systems is evaluated according to three traditional classifications of machine learning: supervised, unsupervised, and deep learning. We also provide insight into the algorithms used in machine learning and wireless localization system-related articles over the years. Finally, we provide an overview summary of wireless localization systems based on machine learning methods and give directions for the future development of wireless optical localization systems.