RFID Data Management: Challenges and Opportunities

Derakhshan, Roozbeh; Orłowska, Maria E.; Li, Xue

doi:10.1109/rfid.2007.346166

Cited by 148 publications

(92 citation statements)

References 11 publications

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“…As stated in [18], the redundancy problem is recognized as a serious issue in RFID and sensor networks. Redundancy can happen at two different levels, i.e., reader level and data level.…”

Section: Redundancy Definitionmentioning

confidence: 99%

Approximate filtering of redundant RFID data streams in mobile environment

Liao

et al. 2016

Teh. vjesn.

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Original scientific paper Recently, RFID technology has been widely used in many applications such as object monitoring and tracing due to the unique features such as noncontact, automatic, fast and multi-target identification simultaneously. However, because of the interference of environmental factors and the requirement of real-time detection, the data collected by the RFID readers are often full of redundancy, which may reduce the processing efficiency of RFID application servers, even lead to making false decisions. Therefore, it is of definite necessity to filter the redundant data in RFID systems before transmitting them to the upper applications. In order to support approximate filtering of RFID data streams in mobile environment, this paper intends to study effective redundant filtering mechanism in the sliding window model. Firstly, we introduce the application background of RFID data streams and the RFID system architecture based on middleware. Then, we propose a temporal-spatial Bloom filter based on sliding windows, which extends the onedimension array in the standard bloom filter to a two-dimension array, storing both reader IDs and the observed timestamps of original observation items. Meanwhile, in order to guarantee the false positive rate does not increase due to the reason that the space of the filter becomes full, we suggest a random decay strategy for deleting the expired elements. The error rates of the suggested filter, including false positives and false negatives, are analysed in theory. Experimental results show that the suggested filter can filter time redundant data effectively and has a good performance to deal with location movement of RFID objects. Keywords: bloom filter; data stream; redundant data filtering; RFID Aproksimativno filtriranje redundantnih RFID nizova podataka u mobilnom okruženjuIzvorni znanstveni članak U zadnje vrijeme RFID tehnologija (Radio Frequency Identification Technology) se naveliko rabi u mnogim aplikacijama kao što su nadgledanje i praćenje objekta, zahvaljujući jedinstvenim značajkama kao što su beskontaktna, brza i simultana identifikacija više ciljeva. Međutim, zbog interferencije faktora okoline i potrebe za detekcijom u realnom vremenu, podaci koje su RFID čitači prikupili često su puni redundancije, a to može smanjiti učinkovitost obrade RFID aplikacijskih servera, pa čak rezultirati i donošenjem krivih zaključaka. Stoga je neophodno potrebno filtrirati redundantne podatke u RFID sustavima prije nego se prenesu do naprednijih aplikacija. U svrhu podržavanja aproksimativnog filtriranja RFID nizova podataka u mobilnom okruženju, u radu se pokušava analizirati mehanizam za učinkovito redundantno filtriranje modelom kliznog prozora. Najprije se daje razvoj aplikacije RFID nizova podataka i arhitektura RFID sustava utemeljeni na međusoftveru. Zatim se predlaže vremensko-prostorni Bloom filtar utemeljen na kliznim prozorima koji proširuje niz podataka s jednom dimenzijom u standardnom Bloom filtru na filtar s dvije dimenzije, pohranjujući i čitača IDs-a ...

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“…As stated in [18], the redundancy problem is recognized as a serious issue in RFID and sensor networks. Redundancy can happen at two different levels, i.e., reader level and data level.…”

Section: Redundancy Definitionmentioning

confidence: 99%

Approximate filtering of redundant RFID data streams in mobile environment

Liao

et al. 2016

Teh. vjesn.

View full text Add to dashboard Cite

show abstract

“…There are certain characteristics associated with the nature of RFID technology (Cocci et al, 2008;Derakhshan et al, 2007). These challenges include Low Level Data, Error-Prone Data, High Data Volumes and its Spatial and Temporal Aspects.…”

Section: Rfid Characteristicsmentioning

confidence: 99%

The Challenges and Issues Facing the Deployment of RFID Technology

Darcy¹,

Pupunwiwat²,

Stantić³

2011

Deploying RFID - Challenges, Solutions, and Open Issues

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“…The RFID architecture is comprised of three main components: the tag, the reader, and the middleware used to interpret the tag data found within the proximity of readers. RFID systems have been integrated into various applications, for example, Supply-Chain situations [1] and Hospital Patient Monitoring [2]. The advent of RFID technology has also ushered in a promise of simplification of time-costly tasks.…”

Section: Rfidmentioning

confidence: 99%

“…Passive tags, however, have several advantages such as an affordable price, ease of integration into applications and, theoretically, they will last forever. Four aspects of RFID systems have been identified as problematic: low level representations of the observations, error-prone data, high information collection volumes and complex spatial and temporal aspects of the data, [3], [1] and [4].…”

Section: Rfidmentioning

confidence: 99%

X-CleLo: intelligent deterministic RFID data and event transformer

Darcy

Stantić

Sattar

2011

Pers Ubiquit Comput

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Abstract. Recently, passive Radio Frequency Identification (RFID) systems have received an exponential amount of attention as researchers have worked tirelessly to implement a stable and reliable system. Unfortunately, despite vast improvements in the quality of RFID technology, a significant amount of erroneous data is still captured in the system. Currently, the problems associated with RFID have been addressed by cleaning algorithms to enhance the data quality. In this paper, we present X-CleLo, a means to intelligently clean and enhance the dirty data using Clausal Defeasible Logic. The extensive experimental study we have conducted has shown that the X-CleLo method has several advantages against a currently utilised cleaning technique and achieves a higher cleaning rate.

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RFID Data Management: Challenges and Opportunities

Cited by 148 publications

References 11 publications

Approximate filtering of redundant RFID data streams in mobile environment

Approximate filtering of redundant RFID data streams in mobile environment

The Challenges and Issues Facing the Deployment of RFID Technology

X-CleLo: intelligent deterministic RFID data and event transformer

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