Particulate matters are among the major air pollutants in Taiwan, with PM2.5 classified as a Group 1 carcinogen by the World Health Organization (WHO). The volume of particulate matters generated during construction projects is substantial. In many critical areas, such as major traffic routes, flight zones, and densely populated regions, construction activities often occur simultaneously. Consequently, the particulate matters produced by dust can easily lead to air pollution, compromise flight and driving safety, and even pose health risks. Therefore, this issue requires special attention and effective management. Historically, manual watering or sprinkler trucks were employed to mitigate dust-related particulate matter during construction. However, these methods often required significant manpower or resulted in additional diesel combustion emissions, while failing to provide immediate dust suppression. To address this challenge, we have implemented a system that utilizes air quality sensors and CCTV, integrated with artificial intelligence (AI) to recognize dust. This system triggers sprinkler equipment in the shortest time, effectively reducing the particulate matters generated by construction activity. The pilot system has deployed in two-year construction project in the Taoyuan International Airport in Taiwan which is expected to save 2,500 man-hours annually, conserving 60 tons of water daily, and reducing 102 tons of carbon emissions per year. It has been minimizing waste from 50,000 m2 of dust nets and cleanup costs. Additionally, the reusable equipment and materials support sustainable development goals and net-zero emissions throughout this project.