The Identification of RFID Signal Using k-Means for Pallet-Level Tagging

Chun Sern Choong; Ahmad Fakhri Ahmad; Anwar P.P. Abdul Majeed; Muhammad Aizzat Zakaria; Mohd Azraai Mohd Razman

doi:10.1007/978-981-15-6025-5_18

The Identification of RFID Signal Using k-Means for Pallet-Level Tagging

Chun Sern Choong^*, Ahmad Fakhri Ahmad, Anwar P.P. Abdul Majeed, Muhammad Aizzat Zakaria, Mohd Azraai Mohd Razman

^*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

Abstract

Radio Frequency Identification (RFID) applications are becoming increasingly popular in a myriad of areas, and therefore, an effective RFID technology-based location would offer a much-needed additional in tracking system. This research focuses on the identification of the location of passive RFID at the pallet-level, which uses the RFID signal strength to cluster the pallet level tagging through k-means. A comparison between the actual and the predicted level attained via the k-means clustering is evaluated through a multi-class performance metrics. It was demonstrated from the investigation that the k-means model is capable of achieving a classification accuracy of 69% and 67% for the train and test data, respectively.

Original language	English
Title of host publication	Embracing Industry 4.0 - Selected Articles from MUCET 2019
Editors	Mohd Azraai Mohd Razman, Jessnor Arif Mat Jizat, Nafrizuan Mat Yahya, Hyun Myung, Amar Faiz Zainal Abidin, Mohamad Shaiful Abdul Karim
Publisher	Springer
Pages	195-203
Number of pages	9
ISBN (Print)	9789811560248
DOIs	https://doi.org/10.1007/978-981-15-6025-5_18
Publication status	Published - 2020
Externally published	Yes
Event	11th Malaysian Technical Universities Conference on Engineering and Technology, MUCET 2019 - Kuantan, Malaysia Duration: 19 Nov 2019 → 22 Nov 2019

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	678
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	11th Malaysian Technical Universities Conference on Engineering and Technology, MUCET 2019
Country/Territory	Malaysia
City	Kuantan
Period	19/11/19 → 22/11/19

Keywords

K-means
Pallet-level tagging
RFID
Unsupervised machine learning

Access to Document

10.1007/978-981-15-6025-5_18

Cite this

Choong, C. S., Ahmad, A. F., Abdul Majeed, A. P. P., Zakaria, M. A., & Mohd Razman, M. A. (2020). The Identification of RFID Signal Using k-Means for Pallet-Level Tagging. In M. A. Mohd Razman, J. A. Mat Jizat, N. Mat Yahya, H. Myung, A. F. Zainal Abidin, & M. S. Abdul Karim (Eds.), Embracing Industry 4.0 - Selected Articles from MUCET 2019 (pp. 195-203). (Lecture Notes in Electrical Engineering; Vol. 678). Springer. https://doi.org/10.1007/978-981-15-6025-5_18

Choong, Chun Sern ; Ahmad, Ahmad Fakhri ; Abdul Majeed, Anwar P.P. et al. / The Identification of RFID Signal Using k-Means for Pallet-Level Tagging. Embracing Industry 4.0 - Selected Articles from MUCET 2019. editor / Mohd Azraai Mohd Razman ; Jessnor Arif Mat Jizat ; Nafrizuan Mat Yahya ; Hyun Myung ; Amar Faiz Zainal Abidin ; Mohamad Shaiful Abdul Karim. Springer, 2020. pp. 195-203 (Lecture Notes in Electrical Engineering).

@inproceedings{94952d1be73342198d35c3cc20fa5729,

title = "The Identification of RFID Signal Using k-Means for Pallet-Level Tagging",

abstract = "Radio Frequency Identification (RFID) applications are becoming increasingly popular in a myriad of areas, and therefore, an effective RFID technology-based location would offer a much-needed additional in tracking system. This research focuses on the identification of the location of passive RFID at the pallet-level, which uses the RFID signal strength to cluster the pallet level tagging through k-means. A comparison between the actual and the predicted level attained via the k-means clustering is evaluated through a multi-class performance metrics. It was demonstrated from the investigation that the k-means model is capable of achieving a classification accuracy of 69% and 67% for the train and test data, respectively.",

keywords = "K-means, Pallet-level tagging, RFID, Unsupervised machine learning",

author = "Choong, {Chun Sern} and Ahmad, {Ahmad Fakhri} and {Abdul Majeed}, {Anwar P.P.} and Zakaria, {Muhammad Aizzat} and {Mohd Razman}, {Mohd Azraai}",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Singapore Pte Ltd.; 11th Malaysian Technical Universities Conference on Engineering and Technology, MUCET 2019 ; Conference date: 19-11-2019 Through 22-11-2019",

year = "2020",

doi = "10.1007/978-981-15-6025-5_18",

language = "English",

isbn = "9789811560248",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer",

pages = "195--203",

editor = "{Mohd Razman}, {Mohd Azraai} and {Mat Jizat}, {Jessnor Arif} and {Mat Yahya}, Nafrizuan and Hyun Myung and {Zainal Abidin}, {Amar Faiz} and {Abdul Karim}, {Mohamad Shaiful}",

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}

Choong, CS, Ahmad, AF, Abdul Majeed, APP, Zakaria, MA & Mohd Razman, MA 2020, The Identification of RFID Signal Using k-Means for Pallet-Level Tagging. in MA Mohd Razman, JA Mat Jizat, N Mat Yahya, H Myung, AF Zainal Abidin & MS Abdul Karim (eds), Embracing Industry 4.0 - Selected Articles from MUCET 2019. Lecture Notes in Electrical Engineering, vol. 678, Springer, pp. 195-203, 11th Malaysian Technical Universities Conference on Engineering and Technology, MUCET 2019, Kuantan, Malaysia, 19/11/19. https://doi.org/10.1007/978-981-15-6025-5_18

The Identification of RFID Signal Using k-Means for Pallet-Level Tagging. / Choong, Chun Sern; Ahmad, Ahmad Fakhri; Abdul Majeed, Anwar P.P. et al.
Embracing Industry 4.0 - Selected Articles from MUCET 2019. ed. / Mohd Azraai Mohd Razman; Jessnor Arif Mat Jizat; Nafrizuan Mat Yahya; Hyun Myung; Amar Faiz Zainal Abidin; Mohamad Shaiful Abdul Karim. Springer, 2020. p. 195-203 (Lecture Notes in Electrical Engineering; Vol. 678).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - The Identification of RFID Signal Using k-Means for Pallet-Level Tagging

AU - Choong, Chun Sern

AU - Ahmad, Ahmad Fakhri

AU - Abdul Majeed, Anwar P.P.

AU - Zakaria, Muhammad Aizzat

AU - Mohd Razman, Mohd Azraai

PY - 2020

Y1 - 2020

N2 - Radio Frequency Identification (RFID) applications are becoming increasingly popular in a myriad of areas, and therefore, an effective RFID technology-based location would offer a much-needed additional in tracking system. This research focuses on the identification of the location of passive RFID at the pallet-level, which uses the RFID signal strength to cluster the pallet level tagging through k-means. A comparison between the actual and the predicted level attained via the k-means clustering is evaluated through a multi-class performance metrics. It was demonstrated from the investigation that the k-means model is capable of achieving a classification accuracy of 69% and 67% for the train and test data, respectively.

AB - Radio Frequency Identification (RFID) applications are becoming increasingly popular in a myriad of areas, and therefore, an effective RFID technology-based location would offer a much-needed additional in tracking system. This research focuses on the identification of the location of passive RFID at the pallet-level, which uses the RFID signal strength to cluster the pallet level tagging through k-means. A comparison between the actual and the predicted level attained via the k-means clustering is evaluated through a multi-class performance metrics. It was demonstrated from the investigation that the k-means model is capable of achieving a classification accuracy of 69% and 67% for the train and test data, respectively.

KW - K-means

KW - Pallet-level tagging

KW - RFID

KW - Unsupervised machine learning

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DO - 10.1007/978-981-15-6025-5_18

M3 - Conference Proceeding

AN - SCOPUS:85088573594

SN - 9789811560248

T3 - Lecture Notes in Electrical Engineering

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EP - 203

BT - Embracing Industry 4.0 - Selected Articles from MUCET 2019

A2 - Mohd Razman, Mohd Azraai

A2 - Mat Jizat, Jessnor Arif

A2 - Mat Yahya, Nafrizuan

A2 - Myung, Hyun

A2 - Zainal Abidin, Amar Faiz

A2 - Abdul Karim, Mohamad Shaiful

PB - Springer

T2 - 11th Malaysian Technical Universities Conference on Engineering and Technology, MUCET 2019

Y2 - 19 November 2019 through 22 November 2019

ER -

Choong CS, Ahmad AF, Abdul Majeed APP, Zakaria MA, Mohd Razman MA. The Identification of RFID Signal Using k-Means for Pallet-Level Tagging. In Mohd Razman MA, Mat Jizat JA, Mat Yahya N, Myung H, Zainal Abidin AF, Abdul Karim MS, editors, Embracing Industry 4.0 - Selected Articles from MUCET 2019. Springer. 2020. p. 195-203. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-15-6025-5_18

The Identification of RFID Signal Using k-Means for Pallet-Level Tagging

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