Loading…
Sensing the Crowds Using Bluetooth Low Energy Tags
Sensing the crowds to understand crowd dynamics can be a challenging task. Passive sensing techniques such as camera-based sensing can provide flow detection, people counting, and density estimation, but they fail to provide accurate identification of individuals mobility patterns. Active techniques...
Saved in:
Published in: | IEEE access 2016, Vol.4, p.4225-4233 |
---|---|
Main Author: | |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c474t-f195e3db7272da747b5c589e57ceffeb804fbc8892fde5546fe8706f52c7377f3 |
---|---|
cites | cdi_FETCH-LOGICAL-c474t-f195e3db7272da747b5c589e57ceffeb804fbc8892fde5546fe8706f52c7377f3 |
container_end_page | 4233 |
container_issue | |
container_start_page | 4225 |
container_title | IEEE access |
container_volume | 4 |
creator | Basalamah, Anas |
description | Sensing the crowds to understand crowd dynamics can be a challenging task. Passive sensing techniques such as camera-based sensing can provide flow detection, people counting, and density estimation, but they fail to provide accurate identification of individuals mobility patterns. Active techniques such as Radio Frequency Identification (RFID) tags given to people require expensive RFID readers deployed to perform sensing. In this paper, we propose to use Bluetooth low energy (BLE) tagging as an alternative method. When low-cost BLE tags are set in advertisement mode, they can be detected by smartphones. In this paper, we design an architecture for sensing the crowds by requiring a large population carrying relatively cheap off-the-shelf BLE proximity tags, and considerably fewer participants to run scanning application on their smartphones to collect data. We performed a large experimental deployment with 600 tags and ten smartphones conducted during the five days of the world largest annual gathering (The Hajj). We were able to achieve ~90% detectability rate while effectively reconstructing the routes of the participants. |
doi_str_mv | 10.1109/ACCESS.2016.2594210 |
format | article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1109_ACCESS_2016_2594210</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>7542154</ieee_id><doaj_id>oai_doaj_org_article_b23e3b6deebc446baa7fd0cd494cddcb</doaj_id><sourcerecordid>2455948390</sourcerecordid><originalsourceid>FETCH-LOGICAL-c474t-f195e3db7272da747b5c589e57ceffeb804fbc8892fde5546fe8706f52c7377f3</originalsourceid><addsrcrecordid>eNpNkF1rwjAYhcvYYOL8Bd4Udq1L89G0l664TRB2oV6HfLypFde4pCL--0UrstwknJxz3pcnScYZmmYZKt9mVTVfraYYZfkUs5LiDD0kA5zl5YQwkj_-ez8noxB2KJ4iSowPEryCNjRtnXZbSCvvTiakm6vwvj9C51y3TZfulM5b8PU5Xcs6vCRPVu4DjG73MNl8zNfV12T5_bmoZsuJppx2E5uVDIhRHHNsJKdcMc2KEhjXYC2oAlGrdFGU2BpgjOYWCo5yy7DmhHNLhsmi7zVO7sTBNz_Sn4WTjbgKztdC-q7RexAKEyAqNwBKU5orKbk1SBtaUm2MVrHrte86ePd7hNCJnTv6Nq4vMGURWkFKFF2kd2nvQvBg71MzJC6sRc9aXFiLG-uYGvepBgDuCc7iJ6PkD3QhejQ</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2455948390</pqid></control><display><type>article</type><title>Sensing the Crowds Using Bluetooth Low Energy Tags</title><source>IEEE Xplore Open Access Journals</source><creator>Basalamah, Anas</creator><creatorcontrib>Basalamah, Anas</creatorcontrib><description>Sensing the crowds to understand crowd dynamics can be a challenging task. Passive sensing techniques such as camera-based sensing can provide flow detection, people counting, and density estimation, but they fail to provide accurate identification of individuals mobility patterns. Active techniques such as Radio Frequency Identification (RFID) tags given to people require expensive RFID readers deployed to perform sensing. In this paper, we propose to use Bluetooth low energy (BLE) tagging as an alternative method. When low-cost BLE tags are set in advertisement mode, they can be detected by smartphones. In this paper, we design an architecture for sensing the crowds by requiring a large population carrying relatively cheap off-the-shelf BLE proximity tags, and considerably fewer participants to run scanning application on their smartphones to collect data. We performed a large experimental deployment with 600 tags and ten smartphones conducted during the five days of the world largest annual gathering (The Hajj). We were able to achieve ~90% detectability rate while effectively reconstructing the routes of the participants.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2016.2594210</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Bluetooth ; Bluetooth low energy ; Crowdsensing ; Energy efficiency ; Hajj ; Radio frequency identification ; RFID tags ; Smart phones ; Smartphones ; Tagging ; Tags</subject><ispartof>IEEE access, 2016, Vol.4, p.4225-4233</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-f195e3db7272da747b5c589e57ceffeb804fbc8892fde5546fe8706f52c7377f3</citedby><cites>FETCH-LOGICAL-c474t-f195e3db7272da747b5c589e57ceffeb804fbc8892fde5546fe8706f52c7377f3</cites><orcidid>0000-0001-7420-109X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7542154$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,4024,27633,27923,27924,27925,54933</link.rule.ids></links><search><creatorcontrib>Basalamah, Anas</creatorcontrib><title>Sensing the Crowds Using Bluetooth Low Energy Tags</title><title>IEEE access</title><addtitle>Access</addtitle><description>Sensing the crowds to understand crowd dynamics can be a challenging task. Passive sensing techniques such as camera-based sensing can provide flow detection, people counting, and density estimation, but they fail to provide accurate identification of individuals mobility patterns. Active techniques such as Radio Frequency Identification (RFID) tags given to people require expensive RFID readers deployed to perform sensing. In this paper, we propose to use Bluetooth low energy (BLE) tagging as an alternative method. When low-cost BLE tags are set in advertisement mode, they can be detected by smartphones. In this paper, we design an architecture for sensing the crowds by requiring a large population carrying relatively cheap off-the-shelf BLE proximity tags, and considerably fewer participants to run scanning application on their smartphones to collect data. We performed a large experimental deployment with 600 tags and ten smartphones conducted during the five days of the world largest annual gathering (The Hajj). We were able to achieve ~90% detectability rate while effectively reconstructing the routes of the participants.</description><subject>Bluetooth</subject><subject>Bluetooth low energy</subject><subject>Crowdsensing</subject><subject>Energy efficiency</subject><subject>Hajj</subject><subject>Radio frequency identification</subject><subject>RFID tags</subject><subject>Smart phones</subject><subject>Smartphones</subject><subject>Tagging</subject><subject>Tags</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>DOA</sourceid><recordid>eNpNkF1rwjAYhcvYYOL8Bd4Udq1L89G0l664TRB2oV6HfLypFde4pCL--0UrstwknJxz3pcnScYZmmYZKt9mVTVfraYYZfkUs5LiDD0kA5zl5YQwkj_-ez8noxB2KJ4iSowPEryCNjRtnXZbSCvvTiakm6vwvj9C51y3TZfulM5b8PU5Xcs6vCRPVu4DjG73MNl8zNfV12T5_bmoZsuJppx2E5uVDIhRHHNsJKdcMc2KEhjXYC2oAlGrdFGU2BpgjOYWCo5yy7DmhHNLhsmi7zVO7sTBNz_Sn4WTjbgKztdC-q7RexAKEyAqNwBKU5orKbk1SBtaUm2MVrHrte86ePd7hNCJnTv6Nq4vMGURWkFKFF2kd2nvQvBg71MzJC6sRc9aXFiLG-uYGvepBgDuCc7iJ6PkD3QhejQ</recordid><startdate>2016</startdate><enddate>2016</enddate><creator>Basalamah, Anas</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7SR</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-7420-109X</orcidid></search><sort><creationdate>2016</creationdate><title>Sensing the Crowds Using Bluetooth Low Energy Tags</title><author>Basalamah, Anas</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-f195e3db7272da747b5c589e57ceffeb804fbc8892fde5546fe8706f52c7377f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Bluetooth</topic><topic>Bluetooth low energy</topic><topic>Crowdsensing</topic><topic>Energy efficiency</topic><topic>Hajj</topic><topic>Radio frequency identification</topic><topic>RFID tags</topic><topic>Smart phones</topic><topic>Smartphones</topic><topic>Tagging</topic><topic>Tags</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Basalamah, Anas</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Xplore Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEL</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>DOAJ: Directory of Open Access Journals</collection><jtitle>IEEE access</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Basalamah, Anas</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Sensing the Crowds Using Bluetooth Low Energy Tags</atitle><jtitle>IEEE access</jtitle><stitle>Access</stitle><date>2016</date><risdate>2016</risdate><volume>4</volume><spage>4225</spage><epage>4233</epage><pages>4225-4233</pages><issn>2169-3536</issn><eissn>2169-3536</eissn><coden>IAECCG</coden><abstract>Sensing the crowds to understand crowd dynamics can be a challenging task. Passive sensing techniques such as camera-based sensing can provide flow detection, people counting, and density estimation, but they fail to provide accurate identification of individuals mobility patterns. Active techniques such as Radio Frequency Identification (RFID) tags given to people require expensive RFID readers deployed to perform sensing. In this paper, we propose to use Bluetooth low energy (BLE) tagging as an alternative method. When low-cost BLE tags are set in advertisement mode, they can be detected by smartphones. In this paper, we design an architecture for sensing the crowds by requiring a large population carrying relatively cheap off-the-shelf BLE proximity tags, and considerably fewer participants to run scanning application on their smartphones to collect data. We performed a large experimental deployment with 600 tags and ten smartphones conducted during the five days of the world largest annual gathering (The Hajj). We were able to achieve ~90% detectability rate while effectively reconstructing the routes of the participants.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2016.2594210</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0001-7420-109X</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2169-3536 |
ispartof | IEEE access, 2016, Vol.4, p.4225-4233 |
issn | 2169-3536 2169-3536 |
language | eng |
recordid | cdi_crossref_primary_10_1109_ACCESS_2016_2594210 |
source | IEEE Xplore Open Access Journals |
subjects | Bluetooth Bluetooth low energy Crowdsensing Energy efficiency Hajj Radio frequency identification RFID tags Smart phones Smartphones Tagging Tags |
title | Sensing the Crowds Using Bluetooth Low Energy Tags |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T07%3A53%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Sensing%20the%20Crowds%20Using%20Bluetooth%20Low%20Energy%20Tags&rft.jtitle=IEEE%20access&rft.au=Basalamah,%20Anas&rft.date=2016&rft.volume=4&rft.spage=4225&rft.epage=4233&rft.pages=4225-4233&rft.issn=2169-3536&rft.eissn=2169-3536&rft.coden=IAECCG&rft_id=info:doi/10.1109/ACCESS.2016.2594210&rft_dat=%3Cproquest_cross%3E2455948390%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c474t-f195e3db7272da747b5c589e57ceffeb804fbc8892fde5546fe8706f52c7377f3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2455948390&rft_id=info:pmid/&rft_ieee_id=7542154&rfr_iscdi=true |