A Deep-Learning-Based Visualization Tool for Air Pollution Forecasting

This article presents a comprehensive visualization tool that integrates real-time observation and sensing data with various forecasting models, including numerical and deep-learning approaches. The developed software framework efficiently manages data flow, configures forecasting models, and visual...

Full description

Saved in:
Bibliographic Details
Published inIEEE software Vol. 42; no. 2; pp. 47 - 56
Main Authors Nguyen, Huynh A. D., Le, Hoang T., Barthelemy, Xavier, Azzi, Merched, Duc, Hiep, Jiang, Ningbo, Riley, Matthew, Ha, Quang P.
Format Journal Article
LanguageEnglish
Published Los Alamitos IEEE 01.03.2025
IEEE Computer Society
Subjects
Air pollution
Atmospheric modeling
Data models
Data visualization
Deep learning
Forecasting
Monitoring
Numerical models
Predictive models
Real time
Real-time systems
Servers
Visualization
Weather forecasting
Online AccessGet full text

Cover

More Information
Summary:This article presents a comprehensive visualization tool that integrates real-time observation and sensing data with various forecasting models, including numerical and deep-learning approaches. The developed software framework efficiently manages data flow, configures forecasting models, and visualizes monitoring and prediction information.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0740-7459
1937-4194
DOI:10.1109/MS.2024.3496663