Comprehensive survey on air quality monitoring systems based on emerging computing and communication technologies
MSH Sassi, LC Fourati - Computer Networks, 2022 - Elsevier
In recent years, technologies related to indoor and outdoor air quality monitoring systems
have been growing rapidly, particularly computing and communication technologies …
have been growing rapidly, particularly computing and communication technologies …
AIRDELHI: fine-grained spatio-temporal particulate matter dataset from Delhi for ML based modeling
Air pollution poses serious health concerns in developing countries, such as India,
necessitating large-scale measurement for correlation analysis, policy recommendations …
necessitating large-scale measurement for correlation analysis, policy recommendations …
Machine learning for urban air quality analytics: A survey
The increasing air pollution poses an urgent global concern with far-reaching
consequences, such as premature mortality and reduced crop yield, which significantly …
consequences, such as premature mortality and reduced crop yield, which significantly …
[HTML][HTML] Deep learning on multi-view sequential data: a survey
Z Xie, Y Yang, Y Zhang, J Wang, S Du - Artificial Intelligence Review, 2023 - Springer
With the progress of human daily interaction activities and the development of industrial
society, a large amount of media data and sensor data become accessible. Humans collect …
society, a large amount of media data and sensor data become accessible. Humans collect …
Graph Neural Processes for Spatio-Temporal Extrapolation
We study the task of spatio-temporal extrapolation that generates data at target locations
from surrounding contexts in a graph. This task is crucial as sensors that collect data are …
from surrounding contexts in a graph. This task is crucial as sensors that collect data are …
Deep citywide multisource data fusion-based air quality estimation
L Chen, H Long, J Xu, B Wu, H Zhou… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
With the increasingly serious air pollution, people are paying more and more attention to air
quality. However, air quality information is not available for all regions, as the number of air …
quality. However, air quality information is not available for all regions, as the number of air …
Uncertainty disentanglement with non-stationary heteroscedastic Gaussian processes for active learning
Gaussian processes are Bayesian non-parametric models used in many areas. In this work,
we propose a Non-stationary Heteroscedastic Gaussian process model which can be …
we propose a Non-stationary Heteroscedastic Gaussian process model which can be …
DSGNN: A Dual-View Supergrid-Aware Graph Neural Network for Regional Air Quality Estimation
X Zhang, L Chen, X Tang, H Shi - arXiv preprint arXiv:2404.01975, 2024 - arxiv.org
Air quality estimation can provide air quality for target regions without air quality stations,
which is useful for the public. Existing air quality estimation methods divide the study area …
which is useful for the public. Existing air quality estimation methods divide the study area …
Challenges in Gaussian processes for non intrusive load monitoring
Non-intrusive load monitoring (NILM) or energy disaggregation aims to break down total
household energy consumption into constituent appliances. Prior work has shown that …
household energy consumption into constituent appliances. Prior work has shown that …
Gaussian Processes for Monitoring Air-Quality in Kampala
C Stoddart, L Shrack, R Sserunjogi… - arXiv preprint arXiv …, 2023 - arxiv.org
Monitoring air pollution is of vital importance to the overall health of the population.
Unfortunately, devices that can measure air quality can be expensive, and many cities in low …
Unfortunately, devices that can measure air quality can be expensive, and many cities in low …