Guiyang launches AI-driven air quality forecasting platform

The Eco-Cloud (Phase II), an "integrated platform for atmospheric environment monitoring, management, and control", was launched by the Guiyang Environment and Air Quality Forecasting Center, entering its trial operation stage.

This platform employs a deep learning model combining long short-term memory (LSTM) networks and convolutional neural networks (CNN) to build an AI-based air quality forecasting system.

It utilizes the CNN model's feature extraction capabilities to analyze air quality's spatial distribution characteristics and the LSTM model's predictive capabilities to uncover temporal evolution trends.

The platform trains, mines, and captures big data connections by mining valuable data resources accumulated in recent years, such as air quality and meteorological data in Guiyang. It also uses refined spatial integration, temporal matching, and big data processing technologies.

The platform can provide the city's daily and hourly air quality forecasts for the next seven days. It can forecast the concentrations of six pollutants by region and station, enhancing the seamless integration of forecasting, early warning, and emergency management.

It offers a new, efficient way to achieve air quality forecasting services and comprehensive management. It provides effective technical means for scientific decision-making, comprehensive environmental management, and strengthening air pollution prevention and control.

Guiyang Environment and Air Quality Forecasting Center will promote the integrated application of AI and big data technologies to respond to the needs of ecological environment management and strive to provide technical support for air quality assurance during polluted weather.