<![CDATA[Indoor air quality is an important factor affecting human health and safety, especially in industrial and laboratory environments that are at risk of hazardous gas leaks. To overcome this problem, a system is needed that is able to monitor air quality in real time and detect gas leaks with a high level of accuracy. One of the artificial intelligence methods that can be used in air quality control systems is fuzzy logic, which is able to process sensor data with a high level of uncertainty and produce optimal decisions.This study aims to design and develop an air quality control system with fuzzy logic-based gas leak detection. This system uses various sensors, such as gas sensors (MQ-series), temperature sensors, and humidity sensors, whose data is processed using a fuzzy algorithm to determine the level of air quality and detect gas leaks automatically. If a gas leak or a decrease in air quality is detected below the set threshold, the system will activate a warning alarm and control ventilation to maintain safe air conditions.The test results show that the developed system is able to detect gas leaks with a high level of accuracy and provide a quick response to changes in indoor air conditions. The use of fuzzy logic allows the system to adjust actions based on the severity of the leak or air pollution, thereby increasing efficiency and reliability in air quality control. Thus, this system can be an effective solution in improving indoor safety and comfort, especially in environments that are vulnerable to gas leaks.]]>
