RFID-Based Smart Shelving Storage Systems

D’Alessandro, A.; Buffi, Alice; Nepa, Paolo; Isola, G.

doi:10.1109/apmc.2012.6421816

Cited by 9 publications

(5 citation statements)

References 20 publications

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“…RFID (Radio Frequency IDentification) technology for item-level identification is gaining increasing attention, and new systems such as smart shelves [1]- [2], smart drawers [3] and smart point readers [4] have been proposed. Beside classical solutions exploiting HF-RFID systems based on nearfield inductive coupling [6], UHF-RFID systems have also been exploited because of their higher read and data rates, and multi-tag scenario applications [1]- [5].…”

Section: Introductionmentioning

confidence: 99%

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A localization technique for smart bookshelves based on UHF-RFID systems

D’Alessandro

Buffi

Nepa

et al. 2013

2013 IEEE Antennas and Propagation Society International Symposium (APSURSI)

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A new localization technique for smart bookshelves based on UHF-RFID systems is presented. Two off-the-shelf reader antennas attached to the bookshelf columns, one in front of the other, are used as an alternative to large-area thin planar antennas integrated onto the shelf top. Exploiting RSSI data acquired by the two antennas, a clustering algorithm is implemented to classify tagged books within one of the regions the shelf has been subdivided into. Preliminary results of the system performance analysis are show

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Section: Introductionmentioning

confidence: 99%

“…Tag location can be determined as a consequence of its identification in a restricted area (read/no read approach), as usual in HF-RFID and NF-UHF RFID systems. More refined localization algorithms have been proposed to locate tagged items on smart shelves [1]- [2] or inside smart drawers [3].…”

Section: Introductionmentioning

confidence: 99%

A localization technique for smart bookshelves based on UHF-RFID systems

D’Alessandro

Buffi

Nepa

et al. 2013

2013 IEEE Antennas and Propagation Society International Symposium (APSURSI)

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“…In such a framework, the basic idea of a new measurement method to determine the belonging region of tagged items within RSSI Measurements for RFID Tag Classification in Smart Storage Systems I UHF-RFID smart drawers was presented in [26]. RSSI measurements were acquired during the drawer opening/closing actions and employed to extract some useful features for the tag classification procedure.…”

Section: Introductionmentioning

confidence: 99%

“…RSSI measurements were acquired during the drawer opening/closing actions and employed to extract some useful features for the tag classification procedure. In [26], preliminary results were presented showing the validity of the method for a two-region classification.…”

Section: Introductionmentioning

confidence: 99%

“…This paper presents a methodology to make more selective the approach suggested in [26] for tag classification in smart storage systems. The basic requirement for an effective classification of the tag belonging region is the creation of a set of different tag interrogation field distributions in the area of interest, so that the vector of the corresponding RSSI values can be used to setup the feature vector of a certain classification algorithm.…”

Section: Introductionmentioning

confidence: 99%

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RSSI Measurements for RFID Tag Classification in Smart Storage Systems

Buffi

Michel

Nepa

et al. 2018

IEEE Trans. Instrum. Meas.

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This paper presents a measurement method for tagged item classification in radio frequency identification (RFID)-based smart drawers. Specifically, the amplitude of the signal backscattered by the UHF-RFID passive tags attached to the items inside the drawer is used to identify at which of an assigned set of drawer subregions each detected tag belongs. The received signal strength indicator (RSSI) may be acquired by almost any UHF-RFID commercial reader chipset compatible with the Electronic Product Code (EPC) Class1 Gen2 protocol. The RSSI model in terms of the position of the tag inside the drawer is introduced, and its selective properties are discussed through both numerical data and measurements. The cases of a single reader antenna measuring during natural opening/closing operations as well as of multiple reader antennas measuring when the drawer is static are investigated. The measurement method performance is shown through an experimental analysis in a realistic scenario, where the RSSI values are collected by using commercial UHF RFID hardware components, and then used as the feature vector of the classification algorithm. As an example, two different classifiers are used to map each detected tag to one of the regions the drawer is subdivided into. The classification performance of the method based on a single antenna exploiting the drawer natural sliding movements is comparable to that achievable with multiple reader antennas, while representing a cost-effective and easy-to-implement practical solution. Index Terms-Antenna near-field region, classification techniques, radio frequency identification (RFID) tag classification, received signal strength indicator (RSSI) measurements, RFID tag indoor localization, RFID-based smart drawers, RFID-based smart storage spaces, UHF-RFID measurements.Andrea Michel (S'08-M'15) received the B.E., M.E. (summa cum laude) and PhD degrees in telecommunications engineering from the University of Pisa, Pisa, Italy, in 2009, 2011 Since 2015 he has been a Post-Doctoral Researcher in applied electromagnetism at the Microwave and Radiation Laboratory, Department of Information Engineering, University of Pisa, focusing on the design of integrated antenna for communication systems and smart antennas for near-field UHF-radio frequency identification (RFID) readers. In 2014, he joined the ElectroScience Laboratory, The Ohio State University, Columbus, OH, USA, as a Visiting Scholar, where he has been involved in research on a theoretical analysis on the accuracy of a novel technique for deep tissue imaging. His current research interests include the design of antennas for automotive applications, multiple-in multiple-out systems, and wearable communication systems, in collaboration with other research institutes and companies.Dr. Michel received the Young Scientist Paolo Nepa (M'07) received the Laurea (Doctor) degree (summa cum laude) in electronics engineering from the University of Pisa, Italy, in 1990. Since 1990, he has been with the Department of Information Engineering, Uni...

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Detection and identification of objects based on radio-frequency signatures

Mukherjee¹

2013

Ann. Telecommun.

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RFID-Based Smart Shelving Storage Systems

Cited by 9 publications

References 20 publications

A localization technique for smart bookshelves based on UHF-RFID systems

A localization technique for smart bookshelves based on UHF-RFID systems

RSSI Measurements for RFID Tag Classification in Smart Storage Systems

Detection and identification of objects based on radio-frequency signatures

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