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Behavior-based cleaning for unreliable RFID data sets.

Fan H, Wu Q, Lin Y - Sensors (Basel) (2012)

Bottom Line: Radio Frequency IDentification (RFID) technology promises to revolutionize the way we track items and assets, but in RFID systems, missreading is a common phenomenon and it poses an enormous challenge to RFID data management, so accurate data cleaning becomes an essential task for the successful deployment of systems.Moreover, a Reverse Order Filling Mechanism is proposed to ensure a more complete access to get the movement behavior characteristics of tag.Finally, we validate our solution with a common RFID application and demonstrate the advantages of our approach through extensive simulations.

View Article: PubMed Central - PubMed

Affiliation: School of Computer Science, National University of Defense Technology, Changsha 410073, China. huafan@nudt.edu.cn

ABSTRACT
Radio Frequency IDentification (RFID) technology promises to revolutionize the way we track items and assets, but in RFID systems, missreading is a common phenomenon and it poses an enormous challenge to RFID data management, so accurate data cleaning becomes an essential task for the successful deployment of systems. In this paper, we present the design and development of a RFID data cleaning system, the first declarative, behavior-based unreliable RFID data smoothing system. We take advantage of kinematic characteristics of tags to assist in RFID data cleaning. In order to establish the conversion relationship between RFID data and kinematic parameters of the tags, we propose a movement behavior detection model. Moreover, a Reverse Order Filling Mechanism is proposed to ensure a more complete access to get the movement behavior characteristics of tag. Finally, we validate our solution with a common RFID application and demonstrate the advantages of our approach through extensive simulations.

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Read rate of tags in different conditions. (a) Quiet condition; (b) Noisy condition.
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f1-sensors-12-10196: Read rate of tags in different conditions. (a) Quiet condition; (b) Noisy condition.

Mentions: Adopting the statistical methods similar to SMURF, each epoch is viewed as an independent Bernoulli trial with success probability pi [12]. An epoch may be specified as a number of interrogation cycles or a unit of time. A typical epoch range is 0.2–0.25 seconds [5]. For each epoch, the reader keeps track of all the tags that have been identified, and additional information such as the number of interrogation responses for each tag and the last time the tag was read. Assuming, there are n interrogation cycles in an epoch, the number that tagi is monitored is mi. We can get the read rate of tagi at the moment by pi = mi/n. In the process of passing through the reader's read range, tags will be continuously scanned. Also in the whole process, the read rate of tag is not constant but constantly changing with the distance between the tag and reader. Besides, some researchers have proved by experiments that in the reader's detection region there is a linear relationship between read rate p and distance s [12]. For specific readers, the detection range S is a constant. To confirm this conclusion, we have carried out similar experiments and the conclusion is shown in Figure 1. The quiet condition means an ideal working environment of RFID devices with only a few interferences, while the noisy condition means a work environment with more interferences.


Behavior-based cleaning for unreliable RFID data sets.

Fan H, Wu Q, Lin Y - Sensors (Basel) (2012)

Read rate of tags in different conditions. (a) Quiet condition; (b) Noisy condition.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472823&req=5

f1-sensors-12-10196: Read rate of tags in different conditions. (a) Quiet condition; (b) Noisy condition.
Mentions: Adopting the statistical methods similar to SMURF, each epoch is viewed as an independent Bernoulli trial with success probability pi [12]. An epoch may be specified as a number of interrogation cycles or a unit of time. A typical epoch range is 0.2–0.25 seconds [5]. For each epoch, the reader keeps track of all the tags that have been identified, and additional information such as the number of interrogation responses for each tag and the last time the tag was read. Assuming, there are n interrogation cycles in an epoch, the number that tagi is monitored is mi. We can get the read rate of tagi at the moment by pi = mi/n. In the process of passing through the reader's read range, tags will be continuously scanned. Also in the whole process, the read rate of tag is not constant but constantly changing with the distance between the tag and reader. Besides, some researchers have proved by experiments that in the reader's detection region there is a linear relationship between read rate p and distance s [12]. For specific readers, the detection range S is a constant. To confirm this conclusion, we have carried out similar experiments and the conclusion is shown in Figure 1. The quiet condition means an ideal working environment of RFID devices with only a few interferences, while the noisy condition means a work environment with more interferences.

Bottom Line: Radio Frequency IDentification (RFID) technology promises to revolutionize the way we track items and assets, but in RFID systems, missreading is a common phenomenon and it poses an enormous challenge to RFID data management, so accurate data cleaning becomes an essential task for the successful deployment of systems.Moreover, a Reverse Order Filling Mechanism is proposed to ensure a more complete access to get the movement behavior characteristics of tag.Finally, we validate our solution with a common RFID application and demonstrate the advantages of our approach through extensive simulations.

View Article: PubMed Central - PubMed

Affiliation: School of Computer Science, National University of Defense Technology, Changsha 410073, China. huafan@nudt.edu.cn

ABSTRACT
Radio Frequency IDentification (RFID) technology promises to revolutionize the way we track items and assets, but in RFID systems, missreading is a common phenomenon and it poses an enormous challenge to RFID data management, so accurate data cleaning becomes an essential task for the successful deployment of systems. In this paper, we present the design and development of a RFID data cleaning system, the first declarative, behavior-based unreliable RFID data smoothing system. We take advantage of kinematic characteristics of tags to assist in RFID data cleaning. In order to establish the conversion relationship between RFID data and kinematic parameters of the tags, we propose a movement behavior detection model. Moreover, a Reverse Order Filling Mechanism is proposed to ensure a more complete access to get the movement behavior characteristics of tag. Finally, we validate our solution with a common RFID application and demonstrate the advantages of our approach through extensive simulations.

Show MeSH
Related in: MedlinePlus