The study describes the creation and testing of an Internet of Things hazardous gas detection system, which uses MQ-series sensors together with an ESP32 microcontroller. The system detects hazardous gases and provides real-time alerts through local and wireless mechanisms. Experimental analysis was conducted under controlled indoor conditions using LPG exposure, while evaluating their dynamic response and calibration characteristics together with their recovery behavior and repeatability. The results demonstrate that the sensor exhibits fast response, stable recovery, and consistent output under repeated trials, indicating reliable performance for indicative monitoring applications. The measurements do not meet certified reference standards because they lack calibration, while cross-sensitivity and environmental conditions introduce accuracy problems. The research study presents these limitations together with solutions, which will lead to better gas monitoring systems that meet higher accuracy standards and compliance with official regulations.
Deepak et al. (Sun,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: