Design of an IoT-Based Air Quality System with Web Integration in a Palm Oil Mill Environment

This research aims to design and implement an Internet of Things (IoT)-based air quality monitoring system with real-time data integration to web applications in the PT Gemareksa Mekarsari palm oil mill environment. This system utilizes NodeMCU ESP32 as the main microcontroller connected with MQ-2 and MQ-135 sensors to detect CO, CH₄, and NH₃ gases. Data is sent in real-time to the ThingSpeak platform and displayed through a responsive web dashboard. Testing was conducted over two days at three different location points (open area, fruit processing, and factory office) with a total of 45 measurements. Results showed that the system was able to transmit data with a delivery accuracy rate of 86.67%, with most data received without delay.. The detected gas concentrations were within safe limits, although mild fluctuations occurred, especially in the fruit processing area. The system also showed stable performance in displaying data on mobile and desktop devices. Thus, this system can be an effective solution for automatic and real-time industrial air monitoring, and support efforts to mitigate health risks due to air pollution.