Leveraging AI for Effective Air Pollution Reduction
Air pollution is a global challenge that poses significant risks to human health and the environment. Fortunately, advancements in artificial intelligence (AI) are revolutionizing the fight against air pollution. By leveraging data-driven insights and intelligent systems, AI offers effective strategies to monitor pollution levels, which in turn will help with developing more effective solutions.
AI-powered monitoring systems utilize satellite imagery, ground-based sensors, and weather models to accurately assess pollution levels. Research on AI applications in air pollution reduction has seen substantial growth, with a focus on high-precision prediction of fine particulate matter (PM2.5) and economical AI-based sensors. Notably, China and the United States have published a significant number of scientific papers on AI applications, with China leading in terms of quantity.1
Using AI can significantly reduce the time for air quality forecast. Traditionally, air quality prediction relied on numerical models with lengthy computation times, requiring hourly calculations. However, researchers in Korea have demonstrated that AI models can significantly reduce prediction time while achieving higher precision. Their AI model achieved an impressive 90% accuracy in air quality prediction, surpassing the 77% accuracy achieved by the Community Multi-scale Air Quality Model (CMAQ) for the same-day calculation.2
AI is transforming air pollution reduction by providing data-driven insights and intelligent solutions. Through AI-powered air quality monitoring, smart traffic management, and industrial optimization, we can effectively combat air pollution and foster healthier environments.
References:
2. How artificial intelligence can help save us from air pollution - EHN