{"title":"Enhancing Smartphone-Based Multi-modal Indoor Localization with Camera and WiFi Signal","authors":"Jing Xu, Yanchao Zhao, Jie Wu, Hongyan Qian","doi":"10.1109/MASS.2018.00031","DOIUrl":null,"url":null,"abstract":"One of the major challenges in indoor localization is the matching difficulty and prediction accuracy of anchor points. In this work, we innovate in proposing a camera-based, sensorand WiFi-assisted, and easy-to-deploy system for localization. The proposed method is based on muliti-modal sensing to enhancing localization measurement. We implement a prototype with smartphones and commercial WiFi devices and evaluate it in distinct indoor environments. Experimental results show that the 85-percentile error is within 0.21m for indoor POIs that sheds light on sub-meter level localization.","PeriodicalId":146214,"journal":{"name":"2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MASS.2018.00031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
One of the major challenges in indoor localization is the matching difficulty and prediction accuracy of anchor points. In this work, we innovate in proposing a camera-based, sensorand WiFi-assisted, and easy-to-deploy system for localization. The proposed method is based on muliti-modal sensing to enhancing localization measurement. We implement a prototype with smartphones and commercial WiFi devices and evaluate it in distinct indoor environments. Experimental results show that the 85-percentile error is within 0.21m for indoor POIs that sheds light on sub-meter level localization.
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