Tag movement direction estimation methods in an RFID gate system

Oikawa, Yoshinori

doi:10.1109/iswcs.2009.5285228

Cited by 11 publications

(2 citation statements)

References 3 publications

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“…For example, in warehouse applications it is very important to determine if tagged goods are moving into or out of a warehouse. This problem can in principle be easily solved if we use two antennas and by measuring the times of detection of the tagged object from the signals of the antennas [21]. However, due to the small physical distances of the whole setup, the more distant antenna from the incoming object would "read" the tag basically at the same time as the nearer antenna, which would prevent easy determination of the DOM.…”

Section: B Direction Of Movement Estimationmentioning

confidence: 99%

Novel Semi-Passive RFID System for Indoor Localization

et al. 2013

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Abstract-In this paper we present a novel semi-passive Radio Frequency Identification (RFID) system for accurate indoor localization. The system is composed of a standard Ultra High Frequency (UHF), ISO-18000-6C compliant RFID reader, a set of standard passive RFID tags whose locations are known, and a newly developed tag-like RFID component, which is attached to the items that need to be localized. The new semi-passive component, referred to as sensatag (sense-a-tag), has a dual functionality in that it can sense the communication between the reader and standard tags in its proximity and can communicate with the reader like standard tags using backscatter modulation. Based on the information conveyed by the sensatags to the reader, localization algorithms based on binary sensor principles can be developed. We conducted a number of experiments in a laboratory to quantify the performance of our system, including two real applications, one finding the exact placement of items on shelves and another, estimating the direction of item movement.

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Section: B Direction Of Movement Estimationmentioning

confidence: 99%

Novel Semi-Passive RFID System for Indoor Localization

et al. 2013

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“…The traditional measures include deploying alarms on doors or windows, such as pressuresensitive mats [4] at the door, or having a person carry a GPS location tracking device [5]. The prior work on walking direction detection is based on passive infrared (PIR) sensor grid solutions [6] [7] [8] [9], RFID based solutions [10] [11] and smartphone-based solutions [12] [13]. However, passive infrared sensor grid solutions require instrumenting the space with specialised sensor equipment, whereas wearable devices or phone-based solutions [12] [13] require periodic maintenance, such as recharging or replacing the batteries, which elderly people cannot always be relied upon.…”

Section: Introductionmentioning

confidence: 99%

Tracking Human Motion Direction With Commodity Wireless Networks

Rahaman

Dyo

2021

IEEE Sensors J.

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Detecting when a person leaves a room, or a house is essential to create a safe living environment for people suffering from dementia or other mental disorders. The approaches based on wearable devices, e.g. GPS bracelets may detect such events require periodic maintenance to recharge or replace batteries, and therefore may not be suitable for certain types of users. On the other hand, camera-based systems require illumination and raise potential privacy concerns. In this paper, we propose a device-free walking direction detection approach based on RF-sensing, which does not require a person to wear any equipment. The proposed approach monitors the signal strength fluctuations caused by the human body on ambient wireless links and analyses its spatial patterns using a convolutional neural network to identify the walking direction. The approach has been evaluated experimentally to achieve up to 98% classification accuracy depending on the environment.

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