{"title":"使用配备阅读器的智能手机进行RFID标签的低成本映射","authors":"Yuki Sato, Marius Noreikis, Yu Xiao","doi":"10.1109/MASS.2018.00052","DOIUrl":null,"url":null,"abstract":"This paper proposes a low-cost solution for mapping and locating UHF-band RFID tags in a 3D space using reader-equipped smartphones. Our solution includes a mobile augmented reality application for data collection and information visualization, and a cloud-based application server for calculating locations of the reader-equipped smartphones and the read RFID tags. Our solution applies computer vision and motion sensing techniques to track 3D locations of the RFID reader based on the visual and inertial sensor data collected from the companion smartphones. Meanwhile, it obtains the exact locations of RFID tags by calculating their relative positions from the readers based on the Angle of Arrival (AoA) concept. Our solution can be implemented with any low-cost fixed transmit power RFID readers, since it only requires the readers to report identifiers of read RFID tags. Furthermore, our solution does not require machine-controlled uniform movement of RFID readers, as it can handle the bias in the readings collected from randomly scattered positions. We have evaluated our solution with experiments in real environments using a commercially-off-the-shelf RFID reader and an Android phone. Results show that the average error in the positions of RFID tags is around 25cm for each of orthogonal axes on the floor plane, with the orders of RFID tags correctly detected in most cases.","PeriodicalId":146214,"journal":{"name":"2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Low-Cost Mapping of RFID Tags Using Reader-Equipped Smartphones\",\"authors\":\"Yuki Sato, Marius Noreikis, Yu Xiao\",\"doi\":\"10.1109/MASS.2018.00052\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a low-cost solution for mapping and locating UHF-band RFID tags in a 3D space using reader-equipped smartphones. Our solution includes a mobile augmented reality application for data collection and information visualization, and a cloud-based application server for calculating locations of the reader-equipped smartphones and the read RFID tags. Our solution applies computer vision and motion sensing techniques to track 3D locations of the RFID reader based on the visual and inertial sensor data collected from the companion smartphones. Meanwhile, it obtains the exact locations of RFID tags by calculating their relative positions from the readers based on the Angle of Arrival (AoA) concept. Our solution can be implemented with any low-cost fixed transmit power RFID readers, since it only requires the readers to report identifiers of read RFID tags. Furthermore, our solution does not require machine-controlled uniform movement of RFID readers, as it can handle the bias in the readings collected from randomly scattered positions. We have evaluated our solution with experiments in real environments using a commercially-off-the-shelf RFID reader and an Android phone. Results show that the average error in the positions of RFID tags is around 25cm for each of orthogonal axes on the floor plane, with the orders of RFID tags correctly detected in most cases.\",\"PeriodicalId\":146214,\"journal\":{\"name\":\"2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)\",\"volume\":\"29 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.2018.00052\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","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.2018.00052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
本文提出了一种低成本的解决方案,用于使用配备阅读器的智能手机在3D空间中绘制和定位uhf频段RFID标签。我们的解决方案包括一个用于数据收集和信息可视化的移动增强现实应用程序,以及一个用于计算配备阅读器的智能手机和读取RFID标签位置的基于云的应用程序服务器。我们的解决方案应用计算机视觉和运动感应技术,根据从配套智能手机收集的视觉和惯性传感器数据来跟踪RFID阅读器的3D位置。同时,基于到达角(Angle of Arrival, AoA)的概念,通过计算标签与阅读器的相对位置,得到RFID标签的准确位置。我们的解决方案可以与任何低成本的固定发射功率RFID阅读器一起实现,因为它只需要阅读器报告读取的RFID标签的标识符。此外,我们的解决方案不需要机器控制RFID读取器的均匀运动,因为它可以处理从随机分散位置收集的读数中的偏差。我们已经通过在真实环境中使用商用RFID阅读器和Android手机的实验来评估我们的解决方案。结果表明,在地板平面上,每个正交轴对RFID标签位置的平均误差在25cm左右,大多数情况下RFID标签的顺序是正确的。
Low-Cost Mapping of RFID Tags Using Reader-Equipped Smartphones
This paper proposes a low-cost solution for mapping and locating UHF-band RFID tags in a 3D space using reader-equipped smartphones. Our solution includes a mobile augmented reality application for data collection and information visualization, and a cloud-based application server for calculating locations of the reader-equipped smartphones and the read RFID tags. Our solution applies computer vision and motion sensing techniques to track 3D locations of the RFID reader based on the visual and inertial sensor data collected from the companion smartphones. Meanwhile, it obtains the exact locations of RFID tags by calculating their relative positions from the readers based on the Angle of Arrival (AoA) concept. Our solution can be implemented with any low-cost fixed transmit power RFID readers, since it only requires the readers to report identifiers of read RFID tags. Furthermore, our solution does not require machine-controlled uniform movement of RFID readers, as it can handle the bias in the readings collected from randomly scattered positions. We have evaluated our solution with experiments in real environments using a commercially-off-the-shelf RFID reader and an Android phone. Results show that the average error in the positions of RFID tags is around 25cm for each of orthogonal axes on the floor plane, with the orders of RFID tags correctly detected in most cases.