Estimating pedestrian traffic with Bluetooth sensor technology
The increasing availability of ubiquitous sensor data on the built environment holds great potential for a new generation of travel and mobility research. Bluetooth technology, for example, is already vastly used in vehicular transportation management solutions and services. Current studies discuss...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-09-01
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| Series: | Geo-spatial Information Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10095020.2023.2247446 |
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| _version_ | 1850285194507976704 |
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| author | Avital Angel Achituv Cohen Sagi Dalyot Pnina Plaut |
| author_facet | Avital Angel Achituv Cohen Sagi Dalyot Pnina Plaut |
| author_sort | Avital Angel |
| collection | DOAJ |
| description | The increasing availability of ubiquitous sensor data on the built environment holds great potential for a new generation of travel and mobility research. Bluetooth technology, for example, is already vastly used in vehicular transportation management solutions and services. Current studies discuss the potential of this emerging technology for pedestrian mobility research, but it has yet to be examined in a large urban setting. One of the main problems is detecting pedestrians from Bluetooth records since their behavior and movement patterns share similarities with other urban transportation modes. This study aims to accurately detect pedestrians using a network of 65 Bluetooth detectors located in Tel-Aviv, Israel, which record on average over 60,000 unique daily Bluetooth Media-Access-Control addresses. We propose a detection methodology that includes system calibration, effective travel time calculation, and classification by velocity that takes into consideration the probability of vehicular traffic jams. An evaluation of the proposed methodology presents a promising pedestrian detection accuracy rate of 89%. We showcase the results of pedestrian traffic analysis, together with a discussion on the data analysis challenges and limitations. To the best of our knowledge, this work is the first to analyze pedestrian records detection from a Bluetooth network employed in a dynamic urban environment setting. |
| format | Article |
| id | doaj-art-75c0d60184c64e67a8a26befa321617f |
| institution | OA Journals |
| issn | 1009-5020 1993-5153 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geo-spatial Information Science |
| spelling | doaj-art-75c0d60184c64e67a8a26befa321617f2025-08-20T01:47:22ZengTaylor & Francis GroupGeo-spatial Information Science1009-50201993-51532024-09-012751391140410.1080/10095020.2023.2247446Estimating pedestrian traffic with Bluetooth sensor technologyAvital Angel0Achituv Cohen1Sagi Dalyot2Pnina Plaut3Faculty of Architecture and Town Planning, Technion–Israel Institute of Technology, Haifa, IsraelFaculty of Civil and Environmental Engineering, Technion–Israel Institute of Technology, Haifa, IsraelFaculty of Civil and Environmental Engineering, Technion–Israel Institute of Technology, Haifa, IsraelFaculty of Architecture and Town Planning, Technion–Israel Institute of Technology, Haifa, IsraelThe increasing availability of ubiquitous sensor data on the built environment holds great potential for a new generation of travel and mobility research. Bluetooth technology, for example, is already vastly used in vehicular transportation management solutions and services. Current studies discuss the potential of this emerging technology for pedestrian mobility research, but it has yet to be examined in a large urban setting. One of the main problems is detecting pedestrians from Bluetooth records since their behavior and movement patterns share similarities with other urban transportation modes. This study aims to accurately detect pedestrians using a network of 65 Bluetooth detectors located in Tel-Aviv, Israel, which record on average over 60,000 unique daily Bluetooth Media-Access-Control addresses. We propose a detection methodology that includes system calibration, effective travel time calculation, and classification by velocity that takes into consideration the probability of vehicular traffic jams. An evaluation of the proposed methodology presents a promising pedestrian detection accuracy rate of 89%. We showcase the results of pedestrian traffic analysis, together with a discussion on the data analysis challenges and limitations. To the best of our knowledge, this work is the first to analyze pedestrian records detection from a Bluetooth network employed in a dynamic urban environment setting.https://www.tandfonline.com/doi/10.1080/10095020.2023.2247446Bluetooth technologyubiquitous sensor networkpedestrian mobilitypedestrian detectionwalking |
| spellingShingle | Avital Angel Achituv Cohen Sagi Dalyot Pnina Plaut Estimating pedestrian traffic with Bluetooth sensor technology Geo-spatial Information Science Bluetooth technology ubiquitous sensor network pedestrian mobility pedestrian detection walking |
| title | Estimating pedestrian traffic with Bluetooth sensor technology |
| title_full | Estimating pedestrian traffic with Bluetooth sensor technology |
| title_fullStr | Estimating pedestrian traffic with Bluetooth sensor technology |
| title_full_unstemmed | Estimating pedestrian traffic with Bluetooth sensor technology |
| title_short | Estimating pedestrian traffic with Bluetooth sensor technology |
| title_sort | estimating pedestrian traffic with bluetooth sensor technology |
| topic | Bluetooth technology ubiquitous sensor network pedestrian mobility pedestrian detection walking |
| url | https://www.tandfonline.com/doi/10.1080/10095020.2023.2247446 |
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