Spatiotemporal air quality inference of low-cost sensor data: Evidence from multiple sensor testbeds
Recent advances in sensor and IoT technologies allow for denser and mobile air quality
measurements. These measurements are still spatiotemporally sparse at city-level, but can …
measurements. These measurements are still spatiotemporally sparse at city-level, but can …
Fine-grained urban air quality mapping from sparse mobile air pollution measurements and dense traffic density
Urban air quality mapping has been widely applied in urban planning, air pollution control
and personal air pollution exposure assessment. Urban air quality maps are traditionally …
and personal air pollution exposure assessment. Urban air quality maps are traditionally …
[HTML][HTML] Application of machine learning and multi-dimensional perception in urban spatial quality evaluation: A case study of Shanghai underground pedestrian street
T Yao, Y Xu, L Sun, P Liao, J Wang - Land, 2024 - mdpi.com
The exploitation of urban subsurface space in urban inventory planning is closely connected
to the quality of urban environments. Currently, the construction of underground pedestrian …
to the quality of urban environments. Currently, the construction of underground pedestrian …
ASTGC: Attention-based spatio-temporal fusion graph convolution model for fine-grained air quality analysis
Y Zhao, S Fan, K Xia, Y Jia, L Wang, W Yang - Air Quality, Atmosphere & …, 2023 - Springer
The deployment of air quality monitoring stations is limited in number and unevenly
distributed, resulting in a limited number of collected samples, so fine-grained analysis of air …
distributed, resulting in a limited number of collected samples, so fine-grained analysis of air …
Air quality sensor networks for evidence-based policy making: best practices for actionable insights
J Hofman, J Peters, C Stroobants, E Elst, B Baeyens… - Atmosphere, 2022 - mdpi.com
(1) Background: This work evaluated the usability of commercial “low-cost” air quality sensor
systems to substantiate evidence-based policy making.(2) Methods: Two commercially …
systems to substantiate evidence-based policy making.(2) Methods: Two commercially …
Towards Time-Series Key Points Detection Through Self-supervised Learning and Probability Compensation
M Yuan, X Bi, X Huang, W Zhang, L Hu… - … on Database Systems …, 2023 - Springer
Key points detection is crucial for signal analysis by marking the identification points of
specific events. Deep learning methods have been introduced into key points detection …
specific events. Deep learning methods have been introduced into key points detection …
Spatiotemporal air quality inference of low-cost sensor data; application on a cycling monitoring network
Air quality monitoring in heterogeneous cities is challenging as a high resolution in both
space and time is required to accurately assess population exposure. As regulatory …
space and time is required to accurately assess population exposure. As regulatory …