This research presents an automated indoor air quality monitoring system using an intelligent Internet of Things (IoT) fuzzy-based approach. The system continuously monitors the temperature and quality of air in an indoor environment and employs fuzzy logic to assess the air quality and make informed decisions. The proposed system utilizes sensors, including a PM10 sensor and CO2 sensor, to gather real-time data on air quality parameters. The collected sensor data is processed using a fuzzy logic algorithm that determines the actual quality of the air and triggers appropriate actions to maintain optimal conditions. Raspberry Pi and Arduino systems are integrated to facilitate signal conversion, decision processing, and actuation of the ventilation fan. The fan's speed is dynamically adjusted based on the fuzzy logic output, ensuring efficient ventilation and air quality control. The research includes the implementation of the proposed system in a chemical laboratory setting to evaluate its performance. The experimental findings indicate that the proposed system provides a reliable and automated solution for indoor air quality monitoring. By leveraging the advantages of fuzzy logic and IoT technologies, the system enables efficient control and management of air quality in indoor environments. The remote monitoring and control capabilities offered by the system enhance convenience and flexibility in maintaining a healthy and comfortable indoor environment. Overall, this research contributes to the field of indoor air quality management by presenting a practical and intelligent system. The findings lay the groundwork for further advancements in air quality monitoring and control systems, with potential applications in various indoor settings such as offices, homes, and healthcare facilities.