Efficacy of Bluetooth-Based Data Collection for Road Traffic Analysis and Visualization Using Big Data Analytics
Effective management of daily road traffic is a huge challenge for traffic personnel. Urban traffic management has come a long way from manual control to artificial intelligence techniques. Still real-time adaptive traffic control is an unfulfilled dream due to lack of low cost and easy to install t...
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2023-06-01
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| Series: | Big Data Mining and Analytics |
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| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2022.9020039 |
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| author | Ashish Rajeshwar Kulkarni Narendra Kumar K. Ramachandra Rao |
| author_facet | Ashish Rajeshwar Kulkarni Narendra Kumar K. Ramachandra Rao |
| author_sort | Ashish Rajeshwar Kulkarni |
| collection | DOAJ |
| description | Effective management of daily road traffic is a huge challenge for traffic personnel. Urban traffic management has come a long way from manual control to artificial intelligence techniques. Still real-time adaptive traffic control is an unfulfilled dream due to lack of low cost and easy to install traffic sensor with real-time communication capability. With increasing number of on-board Bluetooth devices in new generation automobiles, these devices can act as sensors to convey the traffic information indirectly. This paper presents the efficacy of road-side Bluetooth scanners for traffic data collection and big-data analytics to process the collected data to extract traffic parameters. Extracted information and analysis are presented through visualizations and tables. All data analytics and visualizations are carried out off-line in R Studio environment. Reliability aspects of the collected and processed data are also investigated. Higher speed of traffic in one direction owing to the geometry of the road is also established through data analysis. Increased penetration of smart phones and fitness bands in day to day use is also established through the device type of the data collected. The results of this work can be used for regular data collection compared to the traditional road surveys carried out annually or bi-annually. It is also found that compared to previous studies published in the literature, the device penetration rate and sample size found in this study are quite high and very encouraging. This is a novel work in literature, which would be quite useful for effective road traffic management in future. |
| format | Article |
| id | doaj-art-68dd6b15cc694fb5ad03088c913f1ffa |
| institution | Kabale University |
| issn | 2096-0654 |
| language | English |
| publishDate | 2023-06-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj-art-68dd6b15cc694fb5ad03088c913f1ffa2025-02-03T06:28:07ZengTsinghua University PressBig Data Mining and Analytics2096-06542023-06-016213915310.26599/BDMA.2022.9020039Efficacy of Bluetooth-Based Data Collection for Road Traffic Analysis and Visualization Using Big Data AnalyticsAshish Rajeshwar Kulkarni0Narendra Kumar1K. Ramachandra Rao2Department of Electrical Engineering, Delhi Technological University, Delhi 110042, IndiaDepartment of Electrical Engineering, Delhi Technological University, Delhi 110042, IndiaDepartment of Civil Engineering, Indian Institute of Technology Delhi, Delhi 110016, IndiaEffective management of daily road traffic is a huge challenge for traffic personnel. Urban traffic management has come a long way from manual control to artificial intelligence techniques. Still real-time adaptive traffic control is an unfulfilled dream due to lack of low cost and easy to install traffic sensor with real-time communication capability. With increasing number of on-board Bluetooth devices in new generation automobiles, these devices can act as sensors to convey the traffic information indirectly. This paper presents the efficacy of road-side Bluetooth scanners for traffic data collection and big-data analytics to process the collected data to extract traffic parameters. Extracted information and analysis are presented through visualizations and tables. All data analytics and visualizations are carried out off-line in R Studio environment. Reliability aspects of the collected and processed data are also investigated. Higher speed of traffic in one direction owing to the geometry of the road is also established through data analysis. Increased penetration of smart phones and fitness bands in day to day use is also established through the device type of the data collected. The results of this work can be used for regular data collection compared to the traditional road surveys carried out annually or bi-annually. It is also found that compared to previous studies published in the literature, the device penetration rate and sample size found in this study are quite high and very encouraging. This is a novel work in literature, which would be quite useful for effective road traffic management in future.https://www.sciopen.com/article/10.26599/BDMA.2022.9020039bluetooth scannersbig datavisualizationspeedsensors |
| spellingShingle | Ashish Rajeshwar Kulkarni Narendra Kumar K. Ramachandra Rao Efficacy of Bluetooth-Based Data Collection for Road Traffic Analysis and Visualization Using Big Data Analytics Big Data Mining and Analytics bluetooth scanners big data visualization speed sensors |
| title | Efficacy of Bluetooth-Based Data Collection for Road Traffic Analysis and Visualization Using Big Data Analytics |
| title_full | Efficacy of Bluetooth-Based Data Collection for Road Traffic Analysis and Visualization Using Big Data Analytics |
| title_fullStr | Efficacy of Bluetooth-Based Data Collection for Road Traffic Analysis and Visualization Using Big Data Analytics |
| title_full_unstemmed | Efficacy of Bluetooth-Based Data Collection for Road Traffic Analysis and Visualization Using Big Data Analytics |
| title_short | Efficacy of Bluetooth-Based Data Collection for Road Traffic Analysis and Visualization Using Big Data Analytics |
| title_sort | efficacy of bluetooth based data collection for road traffic analysis and visualization using big data analytics |
| topic | bluetooth scanners big data visualization speed sensors |
| url | https://www.sciopen.com/article/10.26599/BDMA.2022.9020039 |
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