Designing a Cost-Effective IoT Air Quality Sensor for Real-Time Data Monitoring

This research presents the design and implementation of a cost-effective, IoT-based air quality monitoring system for real-time environmental assessment. The system integrates ZH03A and MQ-7 sensors to measure particulate matter (PM2.5 and PM10) and carbon monoxide (CO) levels, respectively, managed by an Arduino Uno microcontroller for data processing. The system displays measurements on a $20 \times 4$ LCD and transmits real-time data via a NodeMCU ESP8266 to the Thinger.io cloud platform. In addition, data is stored locally on a microSD card and visualized as air quality maps using GIS tools. The system’s performance was validated through comparative testing with BMKG’s operational instruments, including the Kimoto ACSA-14 and LGR CO-30r. Field testing across 50 locations in South Jakarta revealed average concentrations of PM2.5 ($60 \mu \mathrm{~g} / \mathrm{m}^{3}$), PM10 ($70 \mu \mathrm{~g} / \mathrm{m}^{3}$), and CO (6.55 ppm), classified as “unhealthy,” “moderate,” and “moderate” under the AQI. This system provides an affordable and scalable solution for monitoring urban air quality, offering stakeholders real-time insights and actionable data. It aims to enhance public awareness and support data-driven policy interventions for improved environmental management