Article

Temporal management of RFID data

Authors:

Peiya LiuAuthors Info & Claims

VLDB '05: Proceedings of the 31st international conference on Very large data bases

Pages 1128 - 1139

Published: 30 August 2005 Publication History

Abstract

RFID technology can be used to significantly improve the efficiency of business processes by providing the capability of automatic identification and data capture. This technology poses many new challenges on current data management systems. RFID data are time-dependent, dynamically changing, in large volumes, and carry implicit semantics. RFID data management systems need to effectively support such large scale temporal data created by RFID applications. These systems need to have an explicit temporal data model for RFID data to support tracking and monitoring queries. In addition, they need to have an automatic method to transform the primitive observations from RFID readers into derived data used in RFID-enabled applications. In this paper, we present an integrated RFID data management system -- Siemens RFID Middleware -- based on an expressive temporal data model for RFID data. Our system enables semantic RFID data filtering and automatic data transformation based on declarative rules, provides powerful query support of RFID object tracking and monitoring, and can be adapted to different RFID-enabled applications.

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Cited By

Peng SLiu CHe JYu HLi F(2019)Optimization RFID-enabled Retail Store Management with Complex Event ProcessingInternational Journal of Automation and Computing10.1007/s11633-018-1164-516:1(52-64)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1007/s11633-018-1164-5
Baba A(2017)Removing Object Bouncing from Indoor Tracking DataProceedings of the 2017 ACM Southeast Conference10.1145/3077286.3077568(134-141)Online publication date: 13-Apr-2017
https://dl.acm.org/doi/10.1145/3077286.3077568
He ZWong PKao BLo ECheng RFeng Z(2017)Efficient Pattern-Based Aggregation on Sequence DataIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2016.261885629:2(286-299)Online publication date: 1-Feb-2017
https://dl.acm.org/doi/10.1109/TKDE.2016.2618856
Show More Cited By

Index Terms

Temporal management of RFID data
1. Information systems

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cover image DL Hosted proceedings

VLDB '05: Proceedings of the 31st international conference on Very large data bases

August 2005

1392 pages

ISBN:1595931546

General Chair:
Kjell Bratbergsengen
Norwegian University of Science & Technology, Trondheim, Norway

Publisher

VLDB Endowment

Publication History

Published: 30 August 2005

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ICMI05

ICMI05: Seventh International Conference on Multimodal Interfaces 2005

August 30 - September 2, 2005

Trondheim, Norway

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Cited By

Peng SLiu CHe JYu HLi F(2019)Optimization RFID-enabled Retail Store Management with Complex Event ProcessingInternational Journal of Automation and Computing10.1007/s11633-018-1164-516:1(52-64)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1007/s11633-018-1164-5
Baba A(2017)Removing Object Bouncing from Indoor Tracking DataProceedings of the 2017 ACM Southeast Conference10.1145/3077286.3077568(134-141)Online publication date: 13-Apr-2017
https://dl.acm.org/doi/10.1145/3077286.3077568
He ZWong PKao BLo ECheng RFeng Z(2017)Efficient Pattern-Based Aggregation on Sequence DataIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2016.261885629:2(286-299)Online publication date: 1-Feb-2017
https://dl.acm.org/doi/10.1109/TKDE.2016.2618856
Ma MWang P(2017)On the consistency of event processingKnowledge-Based Systems10.1016/j.knosys.2017.08.021137:C(29-41)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1016/j.knosys.2017.08.021
Fazzinga BFlesca SFurfaro FParisi F(2016)Exploiting Integrity Constraints for Cleaning Trajectories of RFID-Monitored ObjectsACM Transactions on Database Systems10.1145/293936841:4(1-52)Online publication date: 2-Nov-2016
https://dl.acm.org/doi/10.1145/2939368
Baba AJaeger MLu HPedersen TKu WXie XÖzcan FKoutrika GMadden S(2016)Learning-Based Cleansing for Indoor RFID DataProceedings of the 2016 International Conference on Management of Data10.1145/2882903.2882907(925-936)Online publication date: 26-Jun-2016
https://dl.acm.org/doi/10.1145/2882903.2882907
Lu TZha XZhao X(2016)Multi-stage Monitoring of Abnormal Situation Based on Complex Event ProcessingProcedia Computer Science10.1016/j.procs.2016.08.18196:C(1361-1370)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1016/j.procs.2016.08.181
Li MLiu YCai Y(2015)A dynamic processing system for sensor data in IoTInternational Journal of Distributed Sensor Networks10.1155/2015/7504522015(18-18)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1155/2015/750452
Cugola GMargara APezzè MPradella MEliassen FVitenberg R(2015)Efficient analysis of event processing applicationsProceedings of the 9th ACM International Conference on Distributed Event-Based Systems10.1145/2675743.2771834(10-21)Online publication date: 24-Jun-2015
https://dl.acm.org/doi/10.1145/2675743.2771834
Kolchinsky ISharfman ISchuster AEliassen FVitenberg R(2015)Lazy evaluation methods for detecting complex eventsProceedings of the 9th ACM International Conference on Distributed Event-Based Systems10.1145/2675743.2771832(34-45)Online publication date: 24-Jun-2015
https://dl.acm.org/doi/10.1145/2675743.2771832
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