Iot-Based Fuzzy Logic Smoke And Gas Detectors For Intelligent Fire Detection System In Food Stall

Abstract

LPG (Liquefied Petroleum Gas), which is widely used in households and industries, has a risk of fire and explosion due to leakage. So, to prevent the risk of leaking LPG gas, it is necessary to take precautions and early detection of gas leaks. This research develops an intelligent fire detection system in food stall based on the Internet of Things (IoT) by utilizing Smoke and Gas sensors and applying fuzzy logic methods. The Internet of Things (IoT) acts as a link between the sensor devices and the data processing system, enabling the sending of notifications and emails to the kiosk owner when a dangerous concentration of gas or smoke is detected. Fuzzy logic methods are used to interpret sensor data and provide a deeper understanding of the severity of potential fires. The results show that the system utilizes sensor technology to detect the presence of smoke and gas that can indicate the presence of a fire. Then, the data obtained from the detectors will be sent to Blynk IoT for processing and analysis. This tool is only able to detect smoke and gas with a maximum distance of 35cm. By using fuzzy logic, the system can provide information about the safety level. For example, if the level of smoke or gas exceeds the specified limit, the system will provide appropriate warnings or precautions.