research-article

RF-AMOC: Human-related RFID Tag Movement Identification in Access Management of Carries

Authors:

Yanfang ZhangAuthors Info & Claims

ACM Transactions on Sensor Networks (TOSN), Volume 16, Issue 4

Article No.: 33, Pages 1 - 23

https://doi.org/10.1145/3399678

Published: 25 August 2020 Publication History

Abstract

The use of radio-frequency identification (RFID) technology in supply chain has been a fairly mature application in recent years, which can be extended to the field of carrier management for the inventory and access control of sensitive files and mobile storage medium. To address the inherent defects of false readings of RFID, we present RF-AMOC, a tag movement identification system that leverages the signal variation patterns between the opposite antennas and the tag to accurately determine whether someone takes the sensitive carrier out of the room or just the normal carrier usage activity in the room. Particularly, we focus on two kinds of signal variation modes: Direct side models, where the RSSI is sensed by one antenna on the tag side, and obstruction side models, where the RSSI is sensed by the other antenna that was obstructed by the person. Then, Pearson Coefficient and crest comparison algorithms are adopted to match the theoretical and actual RF-signal curves on the two sides, respectively. Additionally, a starting point acquisition method is proposed to extract the meaningful time period. A prototype of RF-AMOC is realized in two different environments with various persons, and the results validate that it is superior in terms of sensitivity and specificity with strong robustness.

References

[1]

2012. IEEE standard for local and metropolitan area networks—Part 15.6: Wireless body area networks. IEEE Std 802.15.6-2012 (Feb. 2012), 1--271.

[2]

Yijian Bai, Fusheng Wang, and Peiya Liu. 2006. Efficiently filtering RFID data streams. In Proceedings of the International VLDB Workshop on Clean Databases (Cleandb’06). 50--57.

[3]

Gi Hwan Bong, Yoon Seok Chang, and Heun Oh Chang. 2014. A practical algorithm for reliability-based RFID event management considering warehouse operational environment. Int. J. Adv. Log. 3, 3 (2014), 100--108.

[4]

J. Brusey, Mg Harrison, and C. Floerkemeier. 2003. Reasoning about uncertainty in location identification with auto-ID. Automatic Identification Rfid Manufacturing (2003).

[5]

Wang Chen, Wei Wei, Hongzhi Lin, Hongbo Jiang, and John C. S. Lui. 2016. BLOW-UP: Toward distributed and scalable space filling curve construction in 3D volumetric WSNs. ACM Trans. Sens. Netw. 12, 4 (2016), 30.

[6]

Tsan Ming Choi, Wing Kwan Yeung, T. C. Edwin Cheng, and Xiaohang Yue. 2018. Optimal scheduling, coordination, and the value of RFID technology in garment manufacturing supply chains. IEEE Trans. Eng. Manage., 99 (2018), 1--13.

[7]

Oscar Delgado-Mohatar, Amparo Fúster-Sabater, and José M. Sierra. 2011. A light-weight authentication scheme for wireless sensor networks. Ad Hoc Netw. 9, 5 (2011), 727--735.

Digital Library

[8]

Xuming Fang, Nan Lei, Zonghua Jiang, and Lijun Chen. 2017. Noise-aware fingerprint localization algorithm for wireless sensor network based on adaptive fingerprint Kalman filter. Comput. Netw. 124 (2017), 97--107.

[9]

T. Germa, F. Lerasle, N. Ouadah, and V. Cadenat. 2010. Vision and RFID data fusion for tracking people in crowds by a mobile robot. Comput. Vis. Image Understand. 114, 6 (2010), 641--651.

Digital Library

[10]

Alexia Giannoula, Alba Gutierrezsacristán, Álex Bravo, Ferran Sanz, and Laura I. Furlong. 2018. Identifying temporal patterns in patient disease trajectories using dynamic time warping: A population-based study. Sci. Rep. 8, 1 (2018), 4216.

[11]

M. Goller, C. Feichtenhofer, and A. Pinz. 2014. Fusing RFID and Computer Vision for Probabilistic Tag Localization. 89--96 pages.

[12]

Ding Han, Jinsong Han, Longfei Shangguan, Xi Wei, Zhiping Jiang, Yang Zheng, Zimu Zhou, Panglong Yang, and Ji Zhong Zhao. 2017. A platform for free-weight exercise monitoring with passive tags. IEEE Trans. Mobile Comput., 99 (2017), 1--1.

[13]

J. [3]. Han and M. Kamber. 2005. Data Mining: Concepts and Technique.

[14]

Matthias Hauser, Daniel Z¨gner, Christoph M. Flath, and Frédéric Thiesse. 2015. Pushing the limits of RFID: Empowering RFID-based electronic article surveillance with data analytics techniques. In Proceedings of the International Conference on Information Systems.

[15]

Wei Qing Huang, Chang Ding, Si Ye Wang, Junyu Lin, Shao Yi Zhu, and Yue Cui. 2017. Design and realization of an indoor positioning algorithm based on differential positioning method. In Proceedings of the International Conference on Wireless Algorithms, Systems, and Applications. 546--558.

[16]

C. Jiang, Y. He, X. Zheng, and Y. Liu. 2018. Orientation-aware RFID tracking with centimeter-level accuracy. In Proceedings of the 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN’18). 290--301.

[17]

Yu Ju Tu and Selwyn Piramuthu. 2008. Reducing false reads in RFID-embedded supply chains. J. Theor. Appl. Electr. Comm. Res. 3, 2 (2008), 60--70.

Digital Library

[18]

Thorben Keller and Elgar Fleisch. 2014. Classification Models for RFID-Based Real-Time Detection of Process Events in the Supply Chain: An Empirical Study. ACM.

[19]

Thorben Keller, Frédéric Thiesse, and Elgar Fleisch. 2014. Using dynamic time warping to identify RFID tag movement in a logistics scenario with and without additional process knowledge. (2014).

[20]

T. Keller, F. Thiesse, A. Ilic, and E. Fleisch. 2013. Decreasing false-positive RFID tag reads by improved portal antenna setups. In Internet of Things. 99--106.

[21]

Thorben Keller, Frédéric Thiesse, Jens Kungl, and Elgar Fleisch. 2010. Using low-level reader data to detect false-positive RFID tag reads. In Internet of Things. 1--8.

[22]

Yudai Komori, Kazuya Sakai, and Satoshi Fukumoto. 2018. Fast and secure tag authentication in large-scale RFID systems using skip graphs ąî. Comput. Commun. 116 (2018), 77--89.

[23]

LaurieDavies and UrsulaGather. 1993. The identification of multiple outliers. Publ. Am. Stat. Assoc. 88, 423 (1993), 782--792.

[24]

Laurie Davies and Ursula Gather. 1993. The identification of multiple outliers. J. Am. Stat. Assoc. 88, 423 (1993), 782--792.

[25]

Xie Lei, Chuyu Wang, Alex X. Liu, Jianqiang Sun, and Sanglu Lu. 2018. Multi-touch in the air: Concurrent micromovement recognition using RF signals. IEEE/ACM Trans. Netw., 99 (2018), 1--14.

[26]

Tao Li, Shigang Chen, and Yibei Ling. 2013. Efficient protocols for identifying the missing tags in a large RFID system. IEEE/ACM Trans. Netw. 21, 6 (2013), 1974--1987.

Digital Library

[27]

T. Liu, L. Yang, Q. Lin, Y. Guo, and Y. Liu. 2014. Anchor-free backscatter positioning for RFID tags with high accuracy. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM’14). 379--387.

[28]

Haishu Ma, Yi Wang, and Kesheng Wang. 2018. Automatic detection of false positive RFID readings using machine learning algorithms. Expert Syst. Appl. 91 (2018).

[29]

Martin Mayer and Norbert Goertz. 2016. RFID tag acquisition via compressed sensing: Fixed vs. random signature assignment. IEEE Trans. Wireless Commun. 15, 3 (2016), 2118--2129.

Digital Library

[30]

Lionel M. Ni, Yunhao Liu, Yiu Cho Lau, and Abhishek P. Patil. 2004. LANDMARC: Indoor location sensing using active RFID. 10, 6 (2004), 701--710.

[31]

Saiyu Qi, Yuanqing Zheng, Mo Li, Yunhao Liu, and Jinli Qiu. 2016. Scalable industry data access control in RFID-enabled supply chain. IEEE/ACM Trans. Netw. 24, 6 (2016), 3551--3564.

Digital Library

[32]

L. Qiu, X. Liang, and Z. Huang. 2017. PATL: A RFID tag localization based on phased array antenna. Sci. Rep. 7 (2017), 44183.

[33]

Mark Roberti. 2004. EPCglobal ratifies Gen 2 standard. RFID J. 16 (2004).

[34]

A. P. Sample, C. Macomber, Liang Ting Jiang, and J. R. Smith. 2016. Optical localization of passive UHF RFID tags with integrated LEDs. In Proceedings of the IEEE International Conference on RFID.

[35]

L. Shangguan, Z. Yang, A. X. Liu, Z. Zhou, and Y. Liu. 2017. STPP: Spatial-temporal phase profiling-based method for relative RFID tag localization. IEEE/ACM Trans. Netw. 25, 1 (2017), 596--609.

Digital Library

[36]

Rudranshu Sharma and Ankur Singh Bist. 2015. Machine learning: A survey. Int. J. Eng. Sci. Res. Technol. 4, 3 (2015).

[37]

Chuyu Wang, Lei Xie, Wei Wang, Yingying Chen, Yanling Bu, and Sanglu Lu. 2018. RF-ECG: Heart rate variability assessment based on COTS RFID tag array. Proc. ACM Interact. Mobile Wear. Ubiq. Technol. 2, 07 (2018), 1--26.

Digital Library

[38]

Gu Yu, Jinhai Zhan, Yusheng Ji, Li Jie, and Shangbing Gao. 2017. MoSense: A RF-based motion detection system via off-the-shelf WiFi devices. IEEE IofT J., 99 (2017), 1--1.

[39]

Wang Zhongqin, Xu Min, Ye Ning, Wang Ruchuan, and Huang Haiping. 2019. Computer vision-assisted region-of-interest RFID tag recognition and localization in multipath-prevalent environments. Proc. ACM Interact. Mobile Wear. Ubiq. Technol. 3, 29 (2019), 1--30.

[40]

Dali Zhu, Bobai Zhao, and Siye Wang. 2018. Mobile target indoor tracking based on multi-direction weight position Kalman filter. Comput. Netw. 141 (2018), 115--127.

[41]

Shaoyi Zhu, Siye Wang, Fangtao Zhang, Yanfang Zhang, Yue Feng, and Weiqing Huang. 2018. Environmentally adaptive real-time detection of RFID false readings in a new practical scenario. In Proceedings of the 2018 IEEE SmartWorld, Ubiquitous Intelligence 8 Computing, Advanced 8 Trusted Computing, Scalable Computing 8 Communications, Cloud 8 Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI’18). 338--345.

Cited By

Wu S(2024)RETRACTED ARTICLE: RFID tag recognition model for Internet of Things for training room managementEURASIP Journal on Information Security10.1186/s13635-024-00154-72024:1Online publication date: 24-Feb-2024
https://doi.org/10.1186/s13635-024-00154-7
Shi BLv B(2023)Accuracy of badminton swing action recognition based on fractional time networkJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-23140945:2(2409-2418)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.3233/JIFS-231409
Li Y(2023)Detection of Moving Object Using Superpixel Fusion NetworkACM Transactions on Multimedia Computing, Communications, and Applications10.1145/357999819:5(1-15)Online publication date: 12-Jan-2023
https://dl.acm.org/doi/10.1145/3579998
Show More Cited By

Index Terms

RF-AMOC: Human-related RFID Tag Movement Identification in Access Management of Carries

Recommendations

A new unpredictability-based radio frequency identification forward privacy model and a provably secure construction

The privacy model of radio frequency identification RFID systems is for formalizing the adversarial capabilities and the security requirements of RFID anonymity and untraceability. Existing unpredictability-based privacy models such as unp-privacy, eunp-...
On two RFID privacy notions and their relations

Privacy of RFID systems is receiving increasing attention in the RFID community. Basically, there are two kinds of RFID privacy notions in the literature: one based on the indistinguishability of two tags, denoted as ind-privacy, and the other based on ...
Computer-aided design of a CPW-fed slot antenna for MM-wave applications: Original Articles

This article presents a comprehensive parametric study with experimental characterization of an inductively coupled CPW-fed slot antenna on a GaAs substrate for MMIC applications. The length, width, and feed inset of the antenna are varied and their ...

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 16, Issue 4

November 2020

311 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/3414039

Editor:
Yunhao Liu
Tsinghua University, China

Issue’s Table of Contents

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 25 August 2020

Accepted: 01 May 2020

Revised: 01 April 2020

Received: 01 May 2019

Published in TOSN Volume 16, Issue 4

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Funding Sources

National Key Research and Development Project

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
181
Total Downloads

Downloads (Last 12 months)18
Downloads (Last 6 weeks)1

Reflects downloads up to 12 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

Wu S(2024)RETRACTED ARTICLE: RFID tag recognition model for Internet of Things for training room managementEURASIP Journal on Information Security10.1186/s13635-024-00154-72024:1Online publication date: 24-Feb-2024
https://doi.org/10.1186/s13635-024-00154-7
Shi BLv B(2023)Accuracy of badminton swing action recognition based on fractional time networkJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-23140945:2(2409-2418)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.3233/JIFS-231409
Li Y(2023)Detection of Moving Object Using Superpixel Fusion NetworkACM Transactions on Multimedia Computing, Communications, and Applications10.1145/357999819:5(1-15)Online publication date: 12-Jan-2023
https://dl.acm.org/doi/10.1145/3579998
Ding YLiu LYang YLiu YZhang DHe T(2022)From Conception to Retirement: A Lifetime Story of a 3-Year-Old Wireless Beacon System in the WildIEEE/ACM Transactions on Networking10.1109/TNET.2021.310704330:1(47-61)Online publication date: Feb-2022
https://doi.org/10.1109/TNET.2021.3107043

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Media

Figures

Other

Tables

View Issue’s Table of Contents