<![CDATA[The escalation of air pollution in urban environments and enclosed spaces, primarily driven by the accumulation of Carbon Monoxide (CO) and Carbon Dioxide (CO2), poses a latent threat to human health due to their colorless and odorless nature. This study aims to design and implement an Internet of Things (IoT)-based air quality early warning system prototype utilizing the ESP32 microcontroller as the core controller. The system architecture integrates an MQ-7 sensor to measure CO levels, an MQ-135 sensor to detect CO2 concentrations, and a DHT22 sensor to monitor ambient temperature and humidity in real-time. The research methodology employs an engineering experiment approach, encompassing hardware architecture design, software development, sensor calibration via average Analog to Digital Converter (ADC) values, and comprehensive system functional testing. Experimental results demonstrate that the device accurately classifies air quality into three distinct thresholds: Good (CO < 10 ppm, CO2 ≤800 ppm), Moderate (CO 10–25 ppm, CO2 801–1500 ppm), and Poor (CO 26 ppm, CO2 > 1500 ppm, or temperature 35ºC). Upon detecting hazardous air conditions, physical indicators including a red LED and a local buzzer are simultaneously activated. Concurrently, critical alerts are transmitted to the user's smartphone via the Blynk platform, exhibiting a response time ranging from 4 to 42 seconds, with an average of 17.7 seconds. The deployment of this early warning system successfully demonstrates the effectiveness of IoT technology integration in providing a highly responsive environmental protection mechanism.]]>
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