학술논문

A Remote Sensing Framework for Automated Monitoring of Roadside Water Quality
Document Type
Conference
Source
2023 International Conference on Machine Learning and Applications (ICMLA) ICMLA Machine Learning and Applications (ICMLA), 2023 International Conference on. :1765-1770 Dec, 2023
Subject
Computing and Processing
Engineering Profession
Robotics and Control Systems
Signal Processing and Analysis
Rain
Storms
Surface contamination
Snow
Transportation
Water quality
Watersheds
Remote Sensing
Environment Monitoring
Internet-of-Things
Big Data
Edge Computing
Language
ISSN
1946-0759
Abstract
While air pollution is the most visible environmental impact of transportation systems, water pollution and water quality issues are also of great importance in the transportation and environment nexus. However, how the transportation sector impacts the water quality of adjacent receiving water bodies is not fully understood or well studied. In this paper, we present our work in designing and implementing a cost-effective, portable system to provide continuous monitoring of roadside water quality. We have deployed the system at multiple locations within the Salmon Creek watershed to collect data, demonstrating the feasibility of using the system to provide long-term monitoring. Combined with advanced data analytics technologies, this system provides potentials to reveal and understand the correlation between transportation activities and water pollution parameters, which can effectively guide the design of the next-generation of environmental friendly and sustainable transportation systems.