Pollution makes our environment endangered; the pollutants present in the air, such as N2O, S2O, CO, etc., affect living things and cause climatic changes in our environment. This leads to an increase in mortality rates and economic burdens. In order to address the above challenges, a new design of an IoT-powered air pollution monitoring system is introduced. This design utilizes an advanced sensor that monitors the harmful gases present in the air continuously. Furthermore, the proposed design incorporates a Kalman filter supported by an AI architecture that enhances the data accuracy and real-time processing by refining sensor data. The AI structure triggers the automatic response once it detects hazardous conditions; further, the automated response activates the instant alert and ventilation system that are placed in the proposed design. This increases safety and provides protection to the surroundings. The IoT system supports continuous data transmission from the sensor to the cloud; this enables seamless monitoring and time-to-time decision-making. Based on the predefined index, the proposed model predicts the air quality with three conditions: good, moderate, and danger. After air quality observation, the proposed system alerts the pollution control board for further action. The preliminary result obtained from the proposed model shows a significant improvement in the data accuracy and response time compared to conventional methods.