This research aims to develop an indoor air quality monitoring device that includes particulate matter (PM1, PM2.5, PM10), carbon monoxide (CO), and carbon dioxide (CO2) based on the Internet of Things (IoT). The device is designed to detect particle and gas concentrations accurately and in real-time, thereby helping users improve indoor air quality. The research method involves developing the device design using particulate matter sensors PMS5003, gas sensors MQ-7 and MH-Z19, temperature and humidity sensors DHT11, and ESP8266 microcontroller to process data. The data from sensor measurements are displayed visually using graphs on the ThingSpeak dashboard. The results show that the developed monitoring device can detect particle and gas concentrations with measurement deviation percentages of 16.34% (PM2.5), 7.71% (PM10), 24.90% (CO2), 3.40% (temperature), and 5.67% (humidity). Meanwhile, for CO gas measurement, further calibration of the used sensor is required
                        
                        
                        
                        
                            
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