Abstract
This paper builds a Near-Field Communication (NFC) based localization system that allows ordinary surfaces to locate surrounding objects with high accuracy in the near-field. While there is rich prior work on device-free localization using far-field wireless technologies, the near-field is less explored. Prior work in this space operates at extremely small ranges (a few centimeters), leading to designs that sense close proximity rather than location. We propose TextileSense, a near-field beamforming system that can track everyday objects made of conductive materials (for example, a human hand) even if they are a few tens of centimeters away. We use multiple flexible NFC coil antennas embedded in ordinary and irregularly shaped surfaces we interact with in smart environments - -furniture, carpets, and so forth. We design and fabricate specialized textile coils woven into the fabric of the furniture and easily hidden by acrylic paint. We then develop a near-field blind beam-forming algorithm to efficiently detect surrounding objects, and use a data-driven approach to further infer their location. A detailed experimental evaluation of TextileSense shows an average accuracy of 3.5 cm in tracking the location of objects of interest within a few tens of centimeters from the furniture.
Cite
CITATION STYLE
Wang, J., Zhang, J., Li, K., Pan, C., Majidi, C., & Kumar, S. (2023). Locating Everyday Objects Using NFC Textiles. Communications of the ACM, 66(10), 107–114. https://doi.org/10.1145/3615450
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