Air quality monitoring of the urban environment remains critical to the wellbeing of people and the preservation of the physical environment. This paper outlines a new method of improving air quality monitoring in urban environments using artificial intelligence (AI) smart sensors connected by the Internet of Things (IoT). The proposed system will cover various air quality indicators—concentrations of gases and particles—by the Internet of Things-based sensor network that will gather real-time data. By serial communication of this data, it is forwarded to a machine learning (ML) model that has been trained on past air quality data and then classified with classification algorithms. The model then analyses the air quality using categories well understood by the model and presents back to the user’s feedback in terms of a “good,” “moderate” and “bad” air quality, coupled with the real-time air quality check. It is thus about using AI and IoT for monitoring air quality in a way that allows users to monitor the tendencies as time goes on to keep taking precautions regarding their health. The outcomes of our study indicate the efficiency of syncing both AI-ML and IoT approaches to air quality management in urban areas, providing an adaptive tool for both visualization and tracking.