A Novel Multivariable Algorithm for Detecting and Tracing Metal Mobile Objects Employing a Simple RFID Setup

Radio Frequency Identification (RFID) is a solution for automated inventory and object detection applications. However, if RFID tags are attached to metal objects, detection errors may occur due to Foucault currents and interferences caused by multiple simultaneous reflections. Errors may increase i...

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Bibliographic Details
Main Authors: Wendy Navarro, Juan C. Velez, Norelli Schettini, Maria Calle
Format: Article
Language:English
Published: SAGE Publishing 2015-11-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2015/409617
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spelling doaj-e7ecfedf2ecb4dd69d4ecacdb1d2e9692020-11-25T03:45:17ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772015-11-011110.1155/2015/409617409617A Novel Multivariable Algorithm for Detecting and Tracing Metal Mobile Objects Employing a Simple RFID SetupWendy NavarroJuan C. VelezNorelli SchettiniMaria CalleRadio Frequency Identification (RFID) is a solution for automated inventory and object detection applications. However, if RFID tags are attached to metal objects, detection errors may occur due to Foucault currents and interferences caused by multiple simultaneous reflections. Errors may increase if metal objects are moving. The paper presents a novel algorithm using RFID low-level reader variables, such as RSSI (Received Signal Strength Indicator), phase angle, and Doppler shift, to detect and trace metal objects. The algorithm was designed to identify if a tag is static or moving and, in the latter case, to compute its speed and direction. The algorithm differs from previous approaches since it uses a simple setup with one commercial portal reader coupled with one single element antenna. Experiments employed one tag located on one metal moving object and 12 static interferer tags, in both outdoor and indoor locations. Results show that the algorithm identifies static tags with no errors. For moving tags, the algorithm shows a maximum 12% error. The algorithm correctly estimates direction and computes object speed. Test conditions emulate fork lift speeds when carrying objects in an industrial warehouse.https://doi.org/10.1155/2015/409617
collection DOAJ
language English
format Article
sources DOAJ
author Wendy Navarro
Juan C. Velez
Norelli Schettini
Maria Calle
spellingShingle Wendy Navarro
Juan C. Velez
Norelli Schettini
Maria Calle
A Novel Multivariable Algorithm for Detecting and Tracing Metal Mobile Objects Employing a Simple RFID Setup
International Journal of Distributed Sensor Networks
author_facet Wendy Navarro
Juan C. Velez
Norelli Schettini
Maria Calle
author_sort Wendy Navarro
title A Novel Multivariable Algorithm for Detecting and Tracing Metal Mobile Objects Employing a Simple RFID Setup
title_short A Novel Multivariable Algorithm for Detecting and Tracing Metal Mobile Objects Employing a Simple RFID Setup
title_full A Novel Multivariable Algorithm for Detecting and Tracing Metal Mobile Objects Employing a Simple RFID Setup
title_fullStr A Novel Multivariable Algorithm for Detecting and Tracing Metal Mobile Objects Employing a Simple RFID Setup
title_full_unstemmed A Novel Multivariable Algorithm for Detecting and Tracing Metal Mobile Objects Employing a Simple RFID Setup
title_sort novel multivariable algorithm for detecting and tracing metal mobile objects employing a simple rfid setup
publisher SAGE Publishing
series International Journal of Distributed Sensor Networks
issn 1550-1477
publishDate 2015-11-01
description Radio Frequency Identification (RFID) is a solution for automated inventory and object detection applications. However, if RFID tags are attached to metal objects, detection errors may occur due to Foucault currents and interferences caused by multiple simultaneous reflections. Errors may increase if metal objects are moving. The paper presents a novel algorithm using RFID low-level reader variables, such as RSSI (Received Signal Strength Indicator), phase angle, and Doppler shift, to detect and trace metal objects. The algorithm was designed to identify if a tag is static or moving and, in the latter case, to compute its speed and direction. The algorithm differs from previous approaches since it uses a simple setup with one commercial portal reader coupled with one single element antenna. Experiments employed one tag located on one metal moving object and 12 static interferer tags, in both outdoor and indoor locations. Results show that the algorithm identifies static tags with no errors. For moving tags, the algorithm shows a maximum 12% error. The algorithm correctly estimates direction and computes object speed. Test conditions emulate fork lift speeds when carrying objects in an industrial warehouse.
url https://doi.org/10.1155/2015/409617
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