An RFID-based object localisation framework

Chawla, Kirti; Robins, Gabriel

doi:10.1504/ijrfita.2011.039780

Cited by 24 publications

(35 citation statements)

References 38 publications

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“…Internal factors related to RFID such as tags, readers can also create interference. The interference causes RF propagation and eventually lead to error in localisation [20]. The interference problem can affect both active and passive tags in localisation.…”

Section: Interference Challengesmentioning

confidence: 99%

RFID Localisation for Internet of Things Smart Homes : A Survey

Alsinglawi¹,

Elkhodr²,

Nguyễn³

et al. 2017

IJCNC

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Section: Interference Challengesmentioning

confidence: 99%

RFID Localisation for Internet of Things Smart Homes : A Survey

Alsinglawi¹,

Elkhodr²,

Nguyễn³

et al. 2017

IJCNC

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“…In ideal condition, they localize an antenna with an average error of 20 cm while greatly increasing the speed of the process. Chawla & Robins [19] developed a model based on the variation of antenna power to estimate the distance of nearby reference tags. They incrementally adjust the antenna decibel until the tag is in range.…”

Section: Rfid Localizationmentioning

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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“…Existing localization solutions that use RFID technology [3]- [6] address the problem of localization in 3D space [4], provide high accuracies in ideal settings. However, when applied on 3D cluttered environments, the accuracy is affected as they do not effectively account for the signal behaviour in such environments.…”

Section: Introductionmentioning

confidence: 99%

“…Some of these localization algorithms use kNN approaches [3] or particle filter based approaches [5] that require an expensive process of generation and maintenance of 2D or 3D RSSI radio maps. The computationally cheaper localization algorithms based on RSSI measure, use non-probabilistic methods that include multilateration [4] and ring overlap techniques [6] to find the location of the target tag. Ring overlap technique requires that the power of the RF wave be altered using external equipment.…”

Section: Introductionmentioning

confidence: 99%

“…For lateration in indoor environments the path loss models have to account for the structures within the indoor space. Existing path loss models, such as log-distance model [6] and the ITU model [7] compensate for the attenuation caused by the structures present in indoor environments to an extent. However, an efficient scaling down of such models to cluttered indoor environments has not been established.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

InPLaCE RFID: Indoor path loss translation for object localization in cluttered environments

Chandrasekaran

Narayan

Vasani

et al. 2015

2015 IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)

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Radio Frequency Identification (RFID) is widely used in indoor positioning systems for object tracking and localization. However, there are several challenges that are yet to be addressed especially in 3-D space. When objects are cluttered densely, an arrangement synonymous to that of heaps of haphazardly arranged files in an office, locating and retrieving a file manually from the heap becomes a laborious task. In this paper, we address the challenge of localization and retrieval of objects in cluttered environments using passive RFID tags, by developing a novel indoor path loss translational model that considers the signal properties across the clutter. The proposed InPLaCE RFID system estimates the position of the object within a clutter by employing a robust translation model that accounts for the properties of the clutter and helps compensate for estimation errors over existing path loss models. Our experiments over different cluttered environments show that the proposed translational model improves the localization accuracy of objects over existing path loss models.

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An RFID-based object localisation framework

Cited by 24 publications

References 38 publications

RFID Localisation for Internet of Things Smart Homes : A Survey

RFID Localisation for Internet of Things Smart Homes : A Survey

Human activity recognition in smart homes based on passive RFID localization

InPLaCE RFID: Indoor path loss translation for object localization in cluttered environments

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