Image-Based Traffic Data Collection in Traffic-Related Air Pollution Analysis
Journal
Lecture Notes in Civil Engineering
Start Page
207
End Page
218
ISSN
2366-2557
2366-2565
ISBN
9783031842238
9783031842245
Date Issued
2024-08-25
Author(s)
Abstract
Traffic-related air pollution (TRAP) emissions significantly contribute to the fine particle matter (PM). Numerous studies have emphasized the adverse health effects of fine PM on respiratory and cardiovascular systems. PM1.0, PM with a diameter of 1.0 µm or less, can penetrate deeper into the respiratory system, even reaching the alveoli. There may be more toxic chemicals presented in PM1.0 because they can carry a greater number of harmful pollutants such as heavy metals and organic compounds. Fine PM is responsible for millions of fatalities annually. Thus, analyzing traffic emission patterns is of importance. This research aims to explore the relationship between traffic flow and TRAP concentrations at urban intersections adjacent to residential buildings. We collected data from IMPACT (Integrated Measurements of Pollution and Aerosol Composition & Transformation), encompassing information such as time, weather conditions, combined with traffic flow data obtained through image-based object detection and tracking, and utilized linear regression to analyze an intersection nearby National Taiwan University. The study serves as a valuable insight for subsequent studies, facilitating investigations into pollution reduction strategies and the development of efficient traffic management approaches to mitigate TRAP.
Event(s)
20th International Conference on Computing in Civil and Building Engineering, ICCCBE 2024, Montreal, 25 August 2024 through 28 August 2024. Code 328229
Subjects
PM1.0
Traffic flow
TRAP
Yolo v8
Publisher
Springer Nature Switzerland
Type
conference paper