Design and Development of IoT-Based Alcohol, CO₂, H₂S, and PM2.5 Detection System for Air Quality Monitoring in Chemical Laboratories

Abstract

Air quality in a chemical laboratory is a crucial factor for occupational safety due to potential exposure to hazardous compounds such as alcohol vapor, CO₂, H₂S, and PM2.5 particles. This research aims to design, build, and test an Internet of Things (IoT)-based air quality detection system capable of monitoring these pollutants in real-time. The research method involved designing a system using MQ-3, MQ-135, MQ-136, and GP2Y1010AUF sensors integrated with a NodeMCU ESP32 microcontroller. Sensor calibration was performed using experimental methods to ensure the device's accuracy. The calibration results showed high validity with coefficients of determination (R²) for the MQ-3, MQ-135, and MQ-136 sensors of 0.9873, 0.9871, and 0.9127, respectively. The average measurement error of the system was below 5%. The system proved effective in providing early warnings and can be applied to enhance occupational safety and health in chemical laboratories through continuous and responsive air quality monitoring.