Internet of Things (IoT) Based Air Pollution Detector for Baby Rooms

Abstract

Indoor air pollution is a leading cause of respiratory illnesses in infants and children, potentially resulting in severe health outcomes, including death. Common sources include dust, cigarette smoke, cleaning chemicals, and hazardous gases such as carbon monoxide (CO) and nitrogen dioxide (NO₂), particularly in enclosed, air-conditioned (AC) environments. Due to the difficulty of detecting pollutants like fine particulate matter (PM2.5) and CO, an effective, real-time monitoring solution is crucial. This study aims to design and develop an Internet of Things (IoT)-based device capable of monitoring PM2.5, CO, temperature, and humidity, specifically in infant rooms. The system integrates an ESP32 microcontroller with DSM501a, MQ-7, and DHT22 sensors and features automated alerts via a Telegram bot when pollutant levels exceed predefined thresholds. The device was evaluated through a comparative 24/7 testing method over seven days against commercially available standard instruments. Results show a relative error of 25% for PM2.5, 30% for CO, and significantly lower errors for temperature (2%) and humidity (0%). Sensor data is processed and transmitted to the Thingspeak server for real-time graphical monitoring. The Telegram alert feature demonstrated an average response time of 1.84 seconds across 20 tests. The findings suggest that the proposed device offers a viable, accessible, and responsive solution for indoor pollutant detection, contributing to improved air quality monitoring and early warning systems to protect vulnerable populations, especially infants.