The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Efficacy of Bluetooth-Based Data Collection for Road Traffic Analysis and Visualization Using Big Data Analytics
Open accessAbstract
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.
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“Additionally, adopting an effective monitoring and alerting system can result in significant cost savings and an enhanced end-user experience [4].”
From Real-Time Monitoring of Data Pipelines: Exploring and Experimentally Proving that the Continuous Monitoring in Data Pipelines Reduces Cost and Elevates Quality (2024) · cites this paper as [4]
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Narayanan, S., S, M., & Zephan, P. (2024) · ICST Transactions on Scalable Information Systems · doi:10.4108/eetsis.5065 · Cited by 8
“Additionally, adopting an effective monitoring and alerting system can result in significant cost savings and an enhanced end-user experience [4].”
Metadata
- Authors
- Kulkarni, A. R., Kumar, N., & Rao, K. R.
- Affiliations
- Delhi Technological University (IN)
- Indian Institute of Technology Delhi (IN)
- Venue
- Big Data Mining and Analytics
- Publisher
- Tsinghua University Press
- Published
- 2023-06
- Volume
- 6
- Issue
- 2
- Pages
- 139-153
- ISSN
- 2096-0654 (ISSN-L)
- 2097-406X
- OpenAlex
- W4320525894
- Cited by
- 24
- References
- 33
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 14 · 2023: 5
- FWCI
- 2.89
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Big Data Mining and Analytics (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Greater South Information System
- Topics
- Social Sciences › Transportation › Traffic Prediction and Management Techniques
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Physical Sciences › Engineering › Civil and Structural Engineering › Transport Systems and Technology
- Keywords
- vehicle-to-vehicle communication, traffic visualization, data reliability, fitness bands, urban traffic management
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