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...

Full description

Saved in:
Bibliographic Details
Published in:IEEE access 2016, Vol.4, p.4225-4233
Main Author: Basalamah, Anas
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 &amp; 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