From "measuring" pollution to forecasting, AI control
Air pollution in large cities not only poses an emission reduction problem but also requires the ability to identify pollution sources, monitor developments and warn early to have appropriate response measures.
Dr. Le Duy Dung - Director of the Bachelor of Data Science Program, Master of Artificial Intelligence, VinUni University - said that data science, the Internet of Things (IoT), artificial intelligence (AI) and digital twins can create new tools for this problem. One of the research directions introduced by Mr. Dung is V-IndoorCARE - a research project applying technology to monitor and improve the quality of the environment in the home.
The starting point of the project is the fact that people spend most of their time in spaces such as houses, offices, schools or hospitals. The air quality here therefore directly affects health, concentration and labor productivity.
The solution is built in the direction of establishing an IoT sensor network to continuously record parameters such as PM2.5 fine dust, CO2, temperature, humidity. Notably, the sensor is not only placed inside but also outside the project" - Mr. Dung shared.
Connecting two data sources helps the system compare air quality inside and outside in real time. From that data, it can support making decisions when to close, open doors, take fresh air from outside or adjust ventilation systems.
Computer vision technology and AI can support building 3D models of the room. In that digital space, the system simulates the movement of air flow, thermal field, CO2 concentration or PM2.5 fine dust when usage conditions change. For example, when the number of people in a room increases, the system can simulate the change of CO2 and temperature, thereby supporting optimal operation of the HVAC air conditioning and ventilation system.
This is a noteworthy issue because according to Dr. Dung's presentation, the HVAC system can account for about 40-60% of the total energy consumption of the building. Intelligent control is therefore aimed at two goals at the same time: Ensuring the quality of the interior environment and using energy more efficiently.
Instead of just measuring pollution to know if a room is "good" or "bad", data combining AI and digital models opens up the ability to analyze - forecast - support decision-making and move towards automated control. This is also a direction for green buildings, when air quality, human health and energy efficiency are placed in the same problem.
UAVs, data from people participating in monitoring pollution sources
In urban scale, technology is also being used by management agencies to support the detection and control of polluting sources. Ms. Nguyen Hoang Anh - Deputy Head of the Environmental Quality Management Department, Department of Environment, Ministry of Agriculture and Environment - said that Hanoi and neighboring provinces often face periods of poor air quality at the end of the year.
From about October of the previous year to March of the following year is often called the "pollution season", in which the peak diễn biến usually falls around December. According to Ms. Anh, there are four basic source groups related to air pollution including transportation; industry; construction, including transportation of construction materials and other sources such as open burning activities, civil activities.
The management problem is therefore not just individual control of each chimney or vehicle. When the density of emissions sources is high and adverse meteorological conditions occur, pollutants can accumulate, causing air quality to decline.
In that context, data and technology can become the "extended arm" of management agencies. "Technology is also being used to support monitoring polluting behaviors and achieve good results," Ms. Anh said.
An example mentioned by the representative of the Department of Environment is the use of UAVs - unmanned aerial vehicles - to monitor combustion activities at many hotspots in Hanoi. Instead of completely relying on direct ground inspection forces, the device can support observing large areas and detecting activities that pose a risk of pollution.
In another direction, people themselves can also become "sensors" of the city. Through the iHanoi platform, people can reflect pollution behaviors for information to be received, serving inspection and handling. According to Ms. Anh, combining many tools not only supports detecting pollution sources but also contributes to changing community awareness. However, technology cannot replace emission control at source.
From a room equipped with sensors to a city supported by UAV surveillance and data reflected from the community, technology is creating new layers of information for the fight against pollution.
