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Smart city article details
| Title | Big Data Analytics And Visualization In Traffic Monitoring |
|---|---|
| ID_Doc | 12008 |
| Authors | Bachechi C.; Po L.; Rollo F. |
| Year | 2022 |
| Published | Big Data Research, 27 |
| DOI | http://dx.doi.org/10.1016/j.bdr.2021.100292 |
| Abstract | This paper presents a system that employs information visualization techniques to analyze urban traffic data and the impact of traffic emissions on urban air quality. Effective visualizations allow citizens and public authorities to identify trends, detect congested road sections at specific times, and perform monitoring and maintenance of traffic sensors. Since road transport is a major source of air pollution, also the impact of traffic on air quality has emerged as a new issue that traffic visualizations should address. Trafair Traffic Dashboard exploits traffic sensor data and traffic flow simulations to create an interactive layout focused on investigating the evolution of traffic in the urban area over time and space. The dashboard is the last step of a complex data framework that starts from the ingestion of traffic sensor observations, anomaly detection, traffic modeling, and also air quality impact analysis. We present the results of applying our proposed framework on two cities (Modena, in Italy, and Santiago de Compostela, in Spain) demonstrating the potential of the dashboard in identifying trends, seasonal events, abnormal behaviors, and understanding how urban vehicle fleet affects air quality. We believe that the framework provides a powerful environment that may guide the public decision-makers through effective analysis of traffic trends devoted to reducing traffic issues and mitigating the polluting effect of transportation. © 2021 Elsevier Inc. |
| Author Keywords | Air quality maps; Real-time data; Smart cities; Spatio-temporal data; Time series; Traffic |
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