Analysis of Toxic Gas Detection System Design with IoT-Based Gas Sensors - Maulana, M. Rizky; Satria, Beni; Aryza, Solly (Bahasa Indonesia, 2025)
Increasing industrial activities and urbanization have caused significant air pollution, including emissions of toxic gases such as hydrogen sulfide (H₂S) and ammonia (NH₃) which are harmful to human health and the environment. This study aims to design and implement an Internet of Things (IoT)-based toxic gas detection system using MQ-136 and MQ-137 sensors integrated with an ESP32 microcontroller. This system is designed to monitor toxic gas concentrations in real-time and send data to an IoT platform such as Blynk for visualization and notification. The research methods include system design, sensor integration with ESP32, data processing algorithm development, and system performance testing under various environmental conditions. The results show that the system is able to detect H₂S and NH₃ gases with good accuracy, provide automatic notification when gas concentrations exceed the threshold, and monitor air quality in real-time through the Blynk application. This system also shows high response speed and good stability during testing. Thus, this study provides an innovative solution for air quality monitoring in industrial and household environments, as well as supporting efforts to improve public safety and health.