A novel method for UHF RFID tag tracking based on acceleration data

Parr, Andreas; Miesen, Robert; Kirsch, Fabian; Vossiek, Martin

doi:10.1109/rfid.2012.6193037

Cited by 22 publications

(7 citation statements)

References 9 publications

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“…Wang et al [ 30 ] and Li et al [ 31 ] combined the RFID and Kinect camera to realize the identification and localization of multiple dynamic objects, but its accuracy is low. Parr et al [ 32 ] realized tag tracking by combining the information of RFID and IMU. Faramondi et al [ 33 ] combined the information of IMU, RFID, and triad-magnetometer in order to realize the identification and localization of rescuers, but the accuracy is low.…”

Section: Related Workmentioning

confidence: 99%

A Method of Multiple Dynamic Objects Identification and Localization Based on Laser and RFID

Liu

Wang

et al. 2020

Sensors

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In an indoor environment, object identification and localization are paramount for human-object interaction. Visual or laser-based sensors can achieve the identification and localization of the object based on its appearance, but these approaches are computationally expensive and not robust against the environment with obstacles. Radio Frequency Identification (RFID) has a unique tag ID to identify the object, but it cannot accurately locate it. Therefore, in this paper, the data of RFID and laser range finder are fused for the better identification and localization of multiple dynamic objects in an indoor environment. The main method is to use the laser range finder to estimate the radial velocities of objects in a certain environment, and match them with the object’s radial velocities estimated by the RFID phase. The method also uses a fixed time series as “sliding time window” to find the cluster with the highest similarity of each RFID tag in each window. Moreover, the Pearson correlation coefficient (PCC) is used in the update stage of the particle filter (PF) to estimate the moving path of each cluster in order to improve the accuracy in a complex environment with obstacles. The experiments were verified by a SCITOS G5 robot. The results show that this method can achieve an matching rate of 90.18% and a localization accuracy of 0.33m in an environment with the presence of obstacles. This method effectively improves the matching rate and localization accuracy of multiple objects in indoor scenes when compared to the Bray-Curtis (BC) similarity matching-based approach as well as the particle filter-based approach.

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Section: Related Workmentioning

confidence: 99%

A Method of Multiple Dynamic Objects Identification and Localization Based on Laser and RFID

Liu

Wang

et al. 2020

Sensors

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“…Work [25] track the trajectory of target tag using grating lobes, while the working distance is only tens of centimeters. To reduce the hardware cost, work [26]- [29] utilizes SAR to simulate multiple antennas. Minsen et al [28] employs a moving antenna to simulate the SAR and location the target by constructing a hologram.…”

Section: Related Workmentioning

confidence: 99%

Towards Large-Scale RFID Positioning: A Low-cost, High-precision Solution Based on Compressive Sensing

Chang¹,

Li²,

Wang³

et al. 2018

2018 IEEE International Conference on Pervasive Computing and Communications (PerCom)

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RFID-based positioning is emerging as a promising solution for inventory management in places like warehouses and libraries. However, existing solutions either are too sensitive to the environmental noise, or require deploying a large number of reference tags which incur expensive deployment cost and increase the chance of data collisions. This paper presents CSRP, a novel RFID based positioning system, that is highly accurate and robust to environmental noise, but relies on much less reference tags compared with the state-of-the-art. CSRP achieves this by employing an noise-resilient RFID fingerprint scheme and a compressive sensing based algorithm that can recover the target tag's position using a small number of signal measurements. It provides a set of new analysis, algorithms and heuristics to guide the deployment of reference tags and to optimize the computational overhead. We evaluate CSRP in a deployment site with 270 commercial RFID tags. Experimental results show that CSRP can correctly identify 84.7% of the test items, achieving an accuracy that is comparable to the state-of-the-art, using an order of magnitude less reference tags.

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“…They enhanced the tags with LEDs to enable a robot equipped with a camera to precisely locate a tag in the environment. Recently, Parr & Miesen [15] introduced a novel method for RFID tag tracking by fusing an inertial measurement unit (IMU) to a handheld reader. Their technique uses acceleration data, without the knowledge of antenna position, to achieve an accurate positioning at a reasonably low cost.…”

Section: Hybrid Rfid Approachesmentioning

confidence: 99%

Human activity recognition in smart homes based on passive RFID localization

Bouchard

Bilodeau

Fortin-Simard

et al. 2014

Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments

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Modern societies are facing an important ageing of their population leading to arising economical and sociological challenges such as the pressure on health support services for semi-autonomous persons. Smart home technology is considered by many researchers as a promising potential solution to help supporting the needs of elders. It aims to provide cognitive assistance by taking decisions, such as giving hints, suggestions and reminders, with different kinds of effectors (light, sound, screen, etc.) to a resident suffering from cognitive deficits in order to foster their autonomy. To implement such technology, the first challenge we need to overcome is the recognition of the ongoing inhabitant activity of daily living (ADL). Moreover, to assist him correctly, we also need to be able to detect the cognitive errors he performs. Therefore, we present in this paper a new affordable activity recognition system, based on passive RFID technology, able to detect errors related to cognitive impairment in morning routines. The entire system relies on an innovative model of elliptical trilateration with several filters, and on an ingenious representation of activities with spatial zones. This system has been implemented and deployed in a real smart home prototype. We also present the promising results of a first experiment conducted on this new activity recognition system with real cases scenarios about morning routines.

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A novel method for UHF RFID tag tracking based on acceleration data

Cited by 22 publications

References 9 publications

A Method of Multiple Dynamic Objects Identification and Localization Based on Laser and RFID

A Method of Multiple Dynamic Objects Identification and Localization Based on Laser and RFID

Towards Large-Scale RFID Positioning: A Low-cost, High-precision Solution Based on Compressive Sensing

Human activity recognition in smart homes based on passive RFID localization

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