research-article

ID'em: Inductive Sensing for Embedding and Extracting Information in Robust Materials

Authors:

Perumal Varun Chadalavada,

Goutham Palaniappan,

Vimal Kumar Chandran,

Daniel WigdorAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 2, Issue 3

Article No.: 97, Pages 1 - 28

https://doi.org/10.1145/3264907

Published: 18 September 2018 Publication History

Abstract

We present ID'em, a novel tagging and localization method that employs an array of Inductive Sensors to 'image' patterns of electrically conductive dots that are embedded underneath the surfaces of materials that cover the environments that we inhabit. ID'em addresses drawbacks found with existing tagging/localization technologies, while drawing on some of their attributes and strengths, thus creating a cost-effective, scalable system that is robust enough to be deployed pervasively. We present a detailed description of the system, applications that leverage ID'em's unique affordances, and address ID'em's strengths and limitations. With ID'em, we envision a future where the materials that we use to cover and build our everyday environments come imbued with information that can provide valuable context for rich, diverse interactions and capabilities.

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Cited By

Jiang WWang CSarsenbayeva ZIrlitti AWei JKnibbe JDingler TGoncalves JKostakos V(2023)InfoPrintProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36109337:3(1-29)Online publication date: 27-Sep-2023
https://dl.acm.org/doi/10.1145/3610933
Jiang WYu DWang CSarsenbayeva Zvan Berkel NGoncalves JKostakos V(2022)Near-infrared Imaging for Information Embedding and Extraction with Layered StructuresACM Transactions on Graphics10.1145/353342642:1(1-26)Online publication date: 2-May-2022
https://dl.acm.org/doi/10.1145/3533426
Gong JWu YYan LSeyed TYang XGuimbretière FBernstein MReinecke K(2019)TessutivoProceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology10.1145/3332165.3347897(29-41)Online publication date: 17-Oct-2019
https://dl.acm.org/doi/10.1145/3332165.3347897

Index Terms

ID'em: Inductive Sensing for Embedding and Extracting Information in Robust Materials

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 2, Issue 3

September 2018

1536 pages

EISSN:2474-9567

DOI:10.1145/3279953

Issue’s Table of Contents

Copyright © 2018 ACM.

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Publication History

Published: 18 September 2018

Accepted: 01 September 2018

Revised: 01 May 2018

Received: 01 November 2017

Published in IMWUT Volume 2, Issue 3

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Cited By

Jiang WWang CSarsenbayeva ZIrlitti AWei JKnibbe JDingler TGoncalves JKostakos V(2023)InfoPrintProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36109337:3(1-29)Online publication date: 27-Sep-2023
https://dl.acm.org/doi/10.1145/3610933
Jiang WYu DWang CSarsenbayeva Zvan Berkel NGoncalves JKostakos V(2022)Near-infrared Imaging for Information Embedding and Extraction with Layered StructuresACM Transactions on Graphics10.1145/353342642:1(1-26)Online publication date: 2-May-2022
https://dl.acm.org/doi/10.1145/3533426
Gong JWu YYan LSeyed TYang XGuimbretière FBernstein MReinecke K(2019)TessutivoProceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology10.1145/3332165.3347897(29-41)Online publication date: 17-Oct-2019
https://dl.acm.org/doi/10.1145/3332165.3347897

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