Cleansing indoor RFID data using regular expressions

Asif Iqbal Baba; Hua Lu; Wei-Shinn Ku; Torben Bach Pedersen

doi:10.1145/2996913.2996979

Cleansing indoor RFID data using regular expressions

Asif Iqbal Baba, Hua Lu, Wei-Shinn Ku, Torben Bach Pedersen

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

Abstract

RFID (Radio Frequency Identification)-based object tracking is increasingly deployed and used in indoor environments such as airports, shopping malls, etc. However, the inherent noise in the raw RFID data makes it difficult to support queries and analyses on the data. In this paper, we propose an RFID data cleansing based on regular expressions. We generate the regular expressions in an automaton that captures all possible indoor paths from the spatial and temporal aspects of indoor space and deployed readers. Given the raw data of an object, the proposed matching algorithm finds all the matching paths using the automaton. We evaluate the proposed approach by conducting experimental studies using real dataset. The results demonstrate the effectiveness of the propose approach.

Originalsprog	Engelsk
Titel	Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016, Burlingame, California, USA, October 31 - November 3, 2016 : (ACM SIGSPATIAL GIS 2015)
Redaktører	Mohammed Eunus Ali, Shawn D. Newsam, Siva Ravada, Matthias Renz, Goce Trajcevski
Antal sider	4
Forlag	Association for Computing Machinery
Publikationsdato	2016
Artikelnummer	77
ISBN (Elektronisk)	9781450345897
DOI	https://doi.org/10.1145/2996913.2996979
Status	Udgivet - 2016
Udgivet eksternt	Ja
Begivenhed	24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems - San Francisco, USA Varighed: 31 okt. 2016 → 3 nov. 2016 Konferencens nummer: 24 http://sigspatial2016.sigspatial.org/

Konference

Konference	24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Nummer	24
Land/Område	USA
By	San Francisco
Periode	31/10/2016 → 03/11/2016
Internetadresse	http://sigspatial2016.sigspatial.org/

Link til dokument

10.1145/2996913.2996979

Citer dette

Baba, A. I., Lu, H., Ku, W-S., & Pedersen, T. B. (2016). Cleansing indoor RFID data using regular expressions. I M. E. Ali, S. D. Newsam, S. Ravada, M. Renz, & G. Trajcevski (red.), Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016, Burlingame, California, USA, October 31 - November 3, 2016: (ACM SIGSPATIAL GIS 2015) [77] Association for Computing Machinery. https://doi.org/10.1145/2996913.2996979

Baba, Asif Iqbal ; Lu, Hua ; Ku, Wei-Shinn ; Pedersen, Torben Bach. / Cleansing indoor RFID data using regular expressions. Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016, Burlingame, California, USA, October 31 - November 3, 2016: (ACM SIGSPATIAL GIS 2015) . red. / Mohammed Eunus Ali ; Shawn D. Newsam ; Siva Ravada ; Matthias Renz ; Goce Trajcevski. Association for Computing Machinery, 2016.

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title = "Cleansing indoor RFID data using regular expressions",

abstract = "RFID (Radio Frequency Identification)-based object tracking is increasingly deployed and used in indoor environments such as airports, shopping malls, etc. However, the inherent noise in the raw RFID data makes it difficult to support queries and analyses on the data. In this paper, we propose an RFID data cleansing based on regular expressions. We generate the regular expressions in an automaton that captures all possible indoor paths from the spatial and temporal aspects of indoor space and deployed readers. Given the raw data of an object, the proposed matching algorithm finds all the matching paths using the automaton. We evaluate the proposed approach by conducting experimental studies using real dataset. The results demonstrate the effectiveness of the propose approach.",

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booktitle = "Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016, Burlingame, California, USA, October 31 - November 3, 2016",

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Baba, AI, Lu, H, Ku, W-S & Pedersen, TB 2016, Cleansing indoor RFID data using regular expressions. i ME Ali, SD Newsam, S Ravada, M Renz & G Trajcevski (red), Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016, Burlingame, California, USA, October 31 - November 3, 2016: (ACM SIGSPATIAL GIS 2015) ., 77, Association for Computing Machinery, 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, San Francisco, California, USA, 31/10/2016. https://doi.org/10.1145/2996913.2996979

Cleansing indoor RFID data using regular expressions. / Baba, Asif Iqbal; Lu, Hua; Ku, Wei-Shinn; Pedersen, Torben Bach.

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016, Burlingame, California, USA, October 31 - November 3, 2016: (ACM SIGSPATIAL GIS 2015) . red. / Mohammed Eunus Ali; Shawn D. Newsam; Siva Ravada; Matthias Renz; Goce Trajcevski. Association for Computing Machinery, 2016. 77.

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

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T1 - Cleansing indoor RFID data using regular expressions

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AU - Lu, Hua

AU - Ku, Wei-Shinn

AU - Pedersen, Torben Bach

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PY - 2016

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N2 - RFID (Radio Frequency Identification)-based object tracking is increasingly deployed and used in indoor environments such as airports, shopping malls, etc. However, the inherent noise in the raw RFID data makes it difficult to support queries and analyses on the data. In this paper, we propose an RFID data cleansing based on regular expressions. We generate the regular expressions in an automaton that captures all possible indoor paths from the spatial and temporal aspects of indoor space and deployed readers. Given the raw data of an object, the proposed matching algorithm finds all the matching paths using the automaton. We evaluate the proposed approach by conducting experimental studies using real dataset. The results demonstrate the effectiveness of the propose approach.

AB - RFID (Radio Frequency Identification)-based object tracking is increasingly deployed and used in indoor environments such as airports, shopping malls, etc. However, the inherent noise in the raw RFID data makes it difficult to support queries and analyses on the data. In this paper, we propose an RFID data cleansing based on regular expressions. We generate the regular expressions in an automaton that captures all possible indoor paths from the spatial and temporal aspects of indoor space and deployed readers. Given the raw data of an object, the proposed matching algorithm finds all the matching paths using the automaton. We evaluate the proposed approach by conducting experimental studies using real dataset. The results demonstrate the effectiveness of the propose approach.

U2 - 10.1145/2996913.2996979

DO - 10.1145/2996913.2996979

M3 - Article in proceedings

BT - Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016, Burlingame, California, USA, October 31 - November 3, 2016

A2 - Ali, Mohammed Eunus

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A2 - Ravada, Siva

A2 - Renz, Matthias

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PB - Association for Computing Machinery

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Baba AI, Lu H, Ku W-S, Pedersen TB. Cleansing indoor RFID data using regular expressions. I Ali ME, Newsam SD, Ravada S, Renz M, Trajcevski G, red., Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016, Burlingame, California, USA, October 31 - November 3, 2016: (ACM SIGSPATIAL GIS 2015) . Association for Computing Machinery. 2016. 77 https://doi.org/10.1145/2996913.2996979