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Using Bluetooth to track mobility patterns: depicting its potential based on various case studies

Published: 05 November 2013 Publication History

Abstract

During the past years the interest in the exploitation of mobility information has increased significantly. A growing number of companies and research institutions are interested in the analysis of mobility data with demand of a high level of spatial detail. Means of tracking persons in our environment can nowadays be fulfilled by utilizing several technologies, for example the Bluetooth technology, offering means to obtain movement data. This paper gives an overview of four case studies in the field of Bluetooth tracking which were conducted in order to provide helpful insights on movement aspects for decision makers in their specific microcosm. Aim is to analyse spatio-temporal validity of Bluetooth tracking, and in doing so, to describe the potential of Bluetooth in pedestrian mobility mining.

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Cited By

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  • (2023)Pair-Less Bluetooth for Touchless Interaction2023 IEEE 20th Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51644.2023.10059727(871-874)Online publication date: 8-Jan-2023
  • (2022)Sensing Multi-modal Mobility Patterns: A Case Study of Helsinki using Bluetooth Beacons and a Mobile Application2022 IEEE International Conference on Big Data (Big Data)10.1109/BigData55660.2022.10020578(2007-2016)Online publication date: 17-Dec-2022
  • (2018)A Survey of Techniques for Automatically Sensing the Behavior of a CrowdACM Computing Surveys10.1145/312934351:1(1-40)Online publication date: 19-Feb-2018
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  1. Using Bluetooth to track mobility patterns: depicting its potential based on various case studies

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      cover image ACM Conferences
      ISA '13: Proceedings of the Fifth ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness
      November 2013
      59 pages
      ISBN:9781450325264
      DOI:10.1145/2533810
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Publication History

      Published: 05 November 2013

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      Author Tags

      1. Bluetooth
      2. event monitoring
      3. mobility mining
      4. visual analytics

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      Cited By

      View all
      • (2023)Pair-Less Bluetooth for Touchless Interaction2023 IEEE 20th Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51644.2023.10059727(871-874)Online publication date: 8-Jan-2023
      • (2022)Sensing Multi-modal Mobility Patterns: A Case Study of Helsinki using Bluetooth Beacons and a Mobile Application2022 IEEE International Conference on Big Data (Big Data)10.1109/BigData55660.2022.10020578(2007-2016)Online publication date: 17-Dec-2022
      • (2018)A Survey of Techniques for Automatically Sensing the Behavior of a CrowdACM Computing Surveys10.1145/312934351:1(1-40)Online publication date: 19-Feb-2018
      • (2017)Characterizing driving environments through Bluetooth discovery2017 International Conference on Information and Communication Technology Convergence (ICTC)10.1109/ICTC.2017.8191028(501-506)Online publication date: Oct-2017
      • (2016)Tracking Visitors in a Real Museum for Behavioral Analysis2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS)10.1109/SCIS-ISIS.2016.0030(80-85)Online publication date: Aug-2016
      • (2016)Understanding user daily mobility using mobile and wearable sensing systems2016 International Conference on Information and Communication Technology Convergence (ICTC)10.1109/ICTC.2016.7763503(387-392)Online publication date: Oct-2016
      • (2016)An RF-based wearable sensor system for indoor tracking to facilitate efficient healthcare management2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)10.1109/EMBC.2016.7591808(4828-4831)Online publication date: Aug-2016
      • (2015)Opportunistic Sampling for Joint Population Size and Density EstimationIEEE Transactions on Mobile Computing10.1109/TMC.2015.239330214:12(2530-2543)Online publication date: 1-Dec-2015

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