Zhenlin An
Abstract
Radio Frequency IDentification (RFID) is emerging as a vital technology of the Internet of Things (IoT). Billions of RFID tags have been deployed to locate daily objects such as equipment, pharmaceuticals, vehicles, and so on. Unlike previous solutions that focus on localizing tagged objects in the world coordinate system in reference to reader antennas, this work exploits a system, called RFCamera, that can identify and locate RFID-tagged objects in images with pixel dimensions. Our core insight is that an image is a visual AoA profile in terms of lights, which is resulted from the pinhole camera model. Similarly, we generate an RF image derived from the AoA profile of a tag using the same pinhole model as the camera. Consequently, the locations of visual entities corresponding to tagged objects are highlighted by comparing two types of images. To this end, we customized a camera system equipped with a pair of rotatable reader antennas. Our experimental evaluation demonstrates that RFCamera enables a mean error of 5.7∘ and 2.9∘ at azimuth and elevation angle estimation, respectively. It can locate a visual entity with a mean error of 51 pixels (i.e., ≈1.3 cm at 96 dpi) in a 640× 480 image.
- [1] Raghu Das. 2017. RFID Forecasts, Players and Opportunities 2017–2027. IDTechEx. Retrieved from http://www.idtechex.com/.Google Scholar
- [2] Impinj. 2017. RFID Report. United States Securities and Exchange Commission. Retrieved from https://www.sec.gov/Archives/edgar/data/1114995/000119312\516651676/d94993ds1a.htm.Google Scholar
- [3] . 2020. General-purpose deep tracking platform across protocols for the internet of things. In Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services. 94–106.Google ScholarDigital Library
- [4] . 2003. Matching words and pictures. J. Mach. Learn. Res. 3, Feb. (2003), 1107–1135.Google ScholarDigital Library
- [5] . 2003. A neural probabilistic language model. J. Mach. Learn. Res. 3, Feb. (2003), 1137–1155.Google ScholarDigital Library
- [6] . 2010. RFID tag antenna based sensing: Does your beverage glass need a refill? In IEEE RFID. IEEE, 126–133.Google Scholar
- [7] . 2005. Combination of RFID and vision for mobile robot localization. In ISSNIP. IEEE, 75–80.Google Scholar
- [8] . 2017. Fusing RFID and computer vision for fine-grained object tracking. In IEEE INFOCOM.Google Scholar
- [9] . 2010. Every picture tells a story: Generating sentences from images. In ECCV. Springer, 15–29.Google Scholar
- [10] . 2013. A sentence is worth a thousand pixels. In IEEE CVPR. 1995–2002.Google Scholar
- [11] . 2010. Vision and RFID data fusion for tracking people in crowds by a mobile robot. Comput. Vis. Image Underst. 114, 6 (2010), 641–651.Google ScholarDigital Library
- [12] . 2014. Fusing RFID and computer vision for probabilistic tag localization. In IEEE RFID. IEEE, 89–96.Google Scholar
- [13] . 2009. Decomposing a scene into geometric and semantically consistent regions. In IEEE CVPR. IEEE, 1–8.Google Scholar
- [14] . 2010. Mutual coupling in antenna arrays. Int. J. Antenn. Propag. 2010 (2010).Google ScholarCross Ref
- [15] . 2010. Speedway revolution reader application note: Low level user data support. In Speedway Revolution Reader Application Note. Retrieved from https://support.impinj.com/hc/en-us/articles/202755318-Application-Note-Low-Level-User-Data-Support.Google Scholar
- [16] . 2005. Activity recognition using visual tracking and RFID. In WACV/MOTIONS’05, Vol. 1. IEEE, 494–500.Google Scholar
- [17] . 2014. Accurate indoor localization with zero start-up cost. In ACM MobiCom.Google Scholar
- [18] . 2007. What, where and who? Classifying events by scene and object recognition. In IEEE CVPR. IEEE, 1–8.Google Scholar
- [19] . 2015. Surpassing human-level face verification performance on LFW with GaussianFace. In AAAI. 3811–3819.Google Scholar
- [20] . 2017. Drone relays for battery-free networks. In ACM SIGCOMM. ACM, 335–347.Google Scholar
- [21] . 2014. Development of an UHF RFID chemical sensor array for battery-less ambient sensing. IEEE Sensors J. 14, 10 (2014), 3616–3623.Google ScholarCross Ref
- [22] . 2013. Distributed representations of words and phrases and their compositionality. In NIPS. 3111–3119.Google Scholar
- [23] . 2018. Indoor distance estimation for passive UHF RFID tag based on RSSI and RCS. Measurement 127 (2018), 425–430.Google ScholarCross Ref
- [24] . 2011. Im2Text: Describing images using 1 million captioned photographs. In NIPS. 1143–1151.Google Scholar
- [25] . 2009. Autonomous mobile robot navigation using passive RFID in indoor environment. IEEE Trans. Industr. Electron. 56, 7 (2009), 2366–2373.Google ScholarCross Ref
- [26] . 2014. GloVe: Global vectors for word representation. In EMNLP. 1532–1543.Google Scholar
- [27] . 2020. RTSense: Passive RFID based temperature sensing. In SenSys. 42–55.Google Scholar
- [28] . 2016. The design and implementation of a mobile RFID tag sorting robot. In MobiSys. ACM, New York, NY.Google Scholar
- [29] . 2020. Voice localization using nearby wall reflections. In MobiCom. 1–14.Google Scholar
- [30] . 2010. Connecting modalities: Semi-supervised segmentation and annotation of images using unaligned text corpora. In IEEE CVPR. IEEE, 966–973.Google Scholar
- [31] . 2014. Grounded compositional semantics for finding and describing images with sentences. Trans. Assoc. Computat. Ling. 2 (2014), 207–218.Google ScholarCross Ref
- [32] . 2017. Structural health monitoring framework based on internet of things: A survey. IEEE Internet Things J. 4, 3 (2017), 619–635.Google ScholarCross Ref
- [33] . 2005. Fundamentals of Wireless Communication. Cambridge University Press.Google ScholarCross Ref
- [34] . 2013. RF-compass: Robot object manipulation using RFIDs. In ACM MobiCom.Google Scholar
- [35] . 2020. Soil moisture sensing with commodity RFID systems. In MobiSys. 273–285.Google Scholar
- [36] . 2013. Dude, where’s my card? RFID positioning that works with multipath and non-line of sight. In ACM SIGCOMM.Google Scholar
- [37] . 2013. Learning a deep compact image representation for visual tracking. In NIPS. 809–817.Google Scholar
- [38] . 2016. Gyro in the air: Tracking 3D orientation of batteryless internet-of-things. In MobiCom. 55–68.Google Scholar
- [39] . 2019. mD-Track: Leveraging multi-dimensionality for passive indoor Wi-Fi tracking. In MobiCom. 1–16.Google Scholar
- [40] . 2018. SWAN: Stitched Wi-Fi antennas. In MobiCom. 51–66.Google Scholar
- [41] . 2014. Tagoram: Real-time tracking of mobile RFID tags to high precision using COTS devices. In ACM MobiCom.Google Scholar
- [42] . 2017. A review of passive RFID tag antenna-based sensors and systems for structural health monitoring applications. Sensors 17, 2 (2017), 265.Google ScholarCross Ref
- [43] . 2007. RFID-based exploration for large robot teams. In ICRA. IEEE, 4606–4613.Google Scholar
Index Terms
- Localizing RFIDs in Pixel Dimensions
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