Ye Yuan, L. Pei, Changqing Xu, Qianchen Liu, Tingyu Gu
{"title":"高效WiFi指纹训练使用半监督学习","authors":"Ye Yuan, L. Pei, Changqing Xu, Qianchen Liu, Tingyu Gu","doi":"10.1109/UPINLBS.2014.7033722","DOIUrl":null,"url":null,"abstract":"Fingerfrinting based WiFi positioning approach needs an off-line training phase to build a radio map with received signal strength indication vector of each reference point. In existing systems, this training phase may cost a tremendous amount of workload to achieve satisfying location result. To cut down on the workload notably and guarantee the location result in the meantime, we will introduce an efficient WiFi fingerprint training method: Fa-Fi namely fast fingerprint generation, which uses semi-supervised learning in this article. This proposed method can reduce the training phase time cost to about 1/5, and guarantee the localization accuracy at the same time.","PeriodicalId":133607,"journal":{"name":"2014 Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Efficient WiFi fingerprint training using semi-supervised learning\",\"authors\":\"Ye Yuan, L. Pei, Changqing Xu, Qianchen Liu, Tingyu Gu\",\"doi\":\"10.1109/UPINLBS.2014.7033722\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fingerfrinting based WiFi positioning approach needs an off-line training phase to build a radio map with received signal strength indication vector of each reference point. In existing systems, this training phase may cost a tremendous amount of workload to achieve satisfying location result. To cut down on the workload notably and guarantee the location result in the meantime, we will introduce an efficient WiFi fingerprint training method: Fa-Fi namely fast fingerprint generation, which uses semi-supervised learning in this article. This proposed method can reduce the training phase time cost to about 1/5, and guarantee the localization accuracy at the same time.\",\"PeriodicalId\":133607,\"journal\":{\"name\":\"2014 Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS)\",\"volume\":\"112 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UPINLBS.2014.7033722\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UPINLBS.2014.7033722","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient WiFi fingerprint training using semi-supervised learning
Fingerfrinting based WiFi positioning approach needs an off-line training phase to build a radio map with received signal strength indication vector of each reference point. In existing systems, this training phase may cost a tremendous amount of workload to achieve satisfying location result. To cut down on the workload notably and guarantee the location result in the meantime, we will introduce an efficient WiFi fingerprint training method: Fa-Fi namely fast fingerprint generation, which uses semi-supervised learning in this article. This proposed method can reduce the training phase time cost to about 1/5, and guarantee the localization accuracy at the same time.