Fall Detection and 3-D Indoor Localization by a Custom RFID Reader Embedded in a Smart e-Health Platform
In this article, we describe a customized 2.45-GHz radio frequency identification (RFID) reader designed to simultaneously perform 3-D tracking of multiple tagged entities (objects or people), static or dynamic, in harsh electromagnetic indoor environments. This is obtained by a bi-dimensional elect...
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Veröffentlicht in: | IEEE transactions on microwave theory and techniques 2019-12, Vol.67 (12), p.5329-5339 |
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creator | Paolini, Giacomo Masotti, Diego Antoniazzi, Francesco Salmon Cinotti, Tullio Costanzo, Alessandra |
description | In this article, we describe a customized 2.45-GHz radio frequency identification (RFID) reader designed to simultaneously perform 3-D tracking of multiple tagged entities (objects or people), static or dynamic, in harsh electromagnetic indoor environments. This is obtained by a bi-dimensional electronic beam-steering, implementing the monopulse radar concept simultaneously in the elevation and azimuth directions, with tags-reader distance estimation based on received signal strength indicator (RSSI) measurements. Experimental results show that the system is able to perform a tri-dimensional scanning of a monitored room with decimeter-accuracy over the three reference axes. The RF front end is designed to be lightweight, thin, and compact in such a way that it is portable and embeddable in domestic objects. For this purpose, a multi-layer solution is adopted with a 2-D patch antenna array aperture coupled with the RF front end. 3-D localization data are computed onboard by means of a seamless connection of the RF front end with a low-power microcontroller, which is able to store tags 3-D localization data over a multi-hour time frame. A useful method to remotely control the whole system is presented, using a Raspberry Pi 3B, directly connecting the reader with a flexible and extensive digital platform for Smart Homes. The presented architecture is experimentally demonstrated to perform a reliable fall detection of tagged people in indoor environments. |
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This is obtained by a bi-dimensional electronic beam-steering, implementing the monopulse radar concept simultaneously in the elevation and azimuth directions, with tags-reader distance estimation based on received signal strength indicator (RSSI) measurements. Experimental results show that the system is able to perform a tri-dimensional scanning of a monitored room with decimeter-accuracy over the three reference axes. The RF front end is designed to be lightweight, thin, and compact in such a way that it is portable and embeddable in domestic objects. For this purpose, a multi-layer solution is adopted with a 2-D patch antenna array aperture coupled with the RF front end. 3-D localization data are computed onboard by means of a seamless connection of the RF front end with a low-power microcontroller, which is able to store tags 3-D localization data over a multi-hour time frame. A useful method to remotely control the whole system is presented, using a Raspberry Pi 3B, directly connecting the reader with a flexible and extensive digital platform for Smart Homes. The presented architecture is experimentally demonstrated to perform a reliable fall detection of tagged people in indoor environments.</description><identifier>ISSN: 0018-9480</identifier><identifier>EISSN: 1557-9670</identifier><identifier>DOI: 10.1109/TMTT.2019.2939807</identifier><identifier>CODEN: IETMAB</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>3-D indoor localization ; Ambient-assisted living (AAL) ; Antenna arrays ; Antenna feeds ; Apertures ; Beam steering ; e-Health ; Fall detection ; Indoor environments ; Localization ; Microcontrollers ; Microstrip antennas ; Monitoring ; Monopulse radar ; Multilayers ; Patch antennas ; Radar tracking ; Radio frequency ; Radio frequency identification ; radio frequency identification (RFID) ; Radiofrequency identification ; Remote control ; remote fall detection ; Signal strength ; Smart buildings ; Tags ; tracking</subject><ispartof>IEEE transactions on microwave theory and techniques, 2019-12, Vol.67 (12), p.5329-5339</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c359t-a8120541594a6422f621761de8177317cfca230c6b17cf90c77d5e242ef622bf3</citedby><cites>FETCH-LOGICAL-c359t-a8120541594a6422f621761de8177317cfca230c6b17cf90c77d5e242ef622bf3</cites><orcidid>0000-0001-5073-000X ; 0000-0002-6877-5254 ; 0000-0002-8173-8044 ; 0000-0001-5340-2781 ; 0000-0002-5001-2689</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8846604$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8846604$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Paolini, Giacomo</creatorcontrib><creatorcontrib>Masotti, Diego</creatorcontrib><creatorcontrib>Antoniazzi, Francesco</creatorcontrib><creatorcontrib>Salmon Cinotti, Tullio</creatorcontrib><creatorcontrib>Costanzo, Alessandra</creatorcontrib><title>Fall Detection and 3-D Indoor Localization by a Custom RFID Reader Embedded in a Smart e-Health Platform</title><title>IEEE transactions on microwave theory and techniques</title><addtitle>TMTT</addtitle><description>In this article, we describe a customized 2.45-GHz radio frequency identification (RFID) reader designed to simultaneously perform 3-D tracking of multiple tagged entities (objects or people), static or dynamic, in harsh electromagnetic indoor environments. 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A useful method to remotely control the whole system is presented, using a Raspberry Pi 3B, directly connecting the reader with a flexible and extensive digital platform for Smart Homes. The presented architecture is experimentally demonstrated to perform a reliable fall detection of tagged people in indoor environments.</description><subject>3-D indoor localization</subject><subject>Ambient-assisted living (AAL)</subject><subject>Antenna arrays</subject><subject>Antenna feeds</subject><subject>Apertures</subject><subject>Beam steering</subject><subject>e-Health</subject><subject>Fall detection</subject><subject>Indoor environments</subject><subject>Localization</subject><subject>Microcontrollers</subject><subject>Microstrip antennas</subject><subject>Monitoring</subject><subject>Monopulse radar</subject><subject>Multilayers</subject><subject>Patch antennas</subject><subject>Radar tracking</subject><subject>Radio frequency</subject><subject>Radio frequency identification</subject><subject>radio frequency identification (RFID)</subject><subject>Radiofrequency identification</subject><subject>Remote control</subject><subject>remote fall detection</subject><subject>Signal strength</subject><subject>Smart buildings</subject><subject>Tags</subject><subject>tracking</subject><issn>0018-9480</issn><issn>1557-9670</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kMtOwzAQRS0EEqXwAYiNJdYpfsb2ErWUVioClbC2HGeipkrq4qSL8vUktGLlsebcmdFB6J6SCaXEPGVvWTZhhJoJM9xooi7QiEqpEpMqcolGhFCdGKHJNbpp223_FZLoEdrMXV3jGXTguyrssNsVmCczvNwVIUS8Ct7V1Y_76-VH7PD00Hahwev5cobX4AqI-KXJoSigwFWfx5-Nix2GZAGu7jb4o3ZdGWJzi65KV7dwd37H6Gv-kk0Xyer9dTl9XiWeS9MlTlNGpKDSCJcKxsqUUZXSAjRVilPlS-8YJz7Nh9oQr1QhgQkGPcnyko_R42nuPobvA7Sd3YZD3PUrLeOcS66V5D1FT5SPoW0jlHYfq_7wo6XEDkLtINQOQu1ZaJ95OGUqAPjntRZpSgT_BQB9byA</recordid><startdate>20191201</startdate><enddate>20191201</enddate><creator>Paolini, Giacomo</creator><creator>Masotti, Diego</creator><creator>Antoniazzi, Francesco</creator><creator>Salmon Cinotti, Tullio</creator><creator>Costanzo, Alessandra</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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This is obtained by a bi-dimensional electronic beam-steering, implementing the monopulse radar concept simultaneously in the elevation and azimuth directions, with tags-reader distance estimation based on received signal strength indicator (RSSI) measurements. Experimental results show that the system is able to perform a tri-dimensional scanning of a monitored room with decimeter-accuracy over the three reference axes. The RF front end is designed to be lightweight, thin, and compact in such a way that it is portable and embeddable in domestic objects. For this purpose, a multi-layer solution is adopted with a 2-D patch antenna array aperture coupled with the RF front end. 3-D localization data are computed onboard by means of a seamless connection of the RF front end with a low-power microcontroller, which is able to store tags 3-D localization data over a multi-hour time frame. 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subjects | 3-D indoor localization Ambient-assisted living (AAL) Antenna arrays Antenna feeds Apertures Beam steering e-Health Fall detection Indoor environments Localization Microcontrollers Microstrip antennas Monitoring Monopulse radar Multilayers Patch antennas Radar tracking Radio frequency Radio frequency identification radio frequency identification (RFID) Radiofrequency identification Remote control remote fall detection Signal strength Smart buildings Tags tracking |
title | Fall Detection and 3-D Indoor Localization by a Custom RFID Reader Embedded in a Smart e-Health Platform |
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