Increasingly harmful air pollution harming humans and the environment. Although they give reliable data, they are costly and cannot be placed everywhere. The article deals with the recent works concerning Internet of Things (IoT) based air-quality monitoring system with a focus on sensors, calibration, power, and analysis of literature. Research shows cheap sensors can measure the value of the major pollutants but their reading drift over time. This means that calibration is a regular and necessary task. Power use can be reduced by sending data only when needed, using renewable energy, and applying low-power communication methods. Some studies also use models such as regression and LSTM to estimate pollution levels. Overall, these results indicate that IoT systems offer a realistic and economical approach for large-scale air-quality monitoring.