IoT Based Smart Ventilation and Air Quality Monitoring System - Shubhangi Namdev Mule; Aditya Vijay Mundhe; Simran Ravi Muntode; Tushar Balasaheb Nagare; Shreya Shankar Nagpure; T. Bhaskar (Journal of Computer Based Parallel Programming, 2025)
With increasing concerns about indoor air quality monitoring and energy efficiency, the need for IoT-based smart ventilation systems that also enhance human comfort has become more pressing. This research introduces a low-cost, sensor-driven smart ventilation system that utilizes gas sensing (MQ2, MQ135), temperature and humidity monitoring (DHT11), motion detection (PIR), and obstacle detection (Ultrasonic Sensor) to maintain optimal indoor environmental conditions. The proposed system employs an IoT-enabled microcontroller to process multi-sensor data in real-time, enabling automated fan control via a motor driver based on pollutant levels, occupancy status, and ambient climate conditions. Leveraging platforms like Wokwi and Tinkercad for simulation and validation, the system is designed to detect harmful gases such as carbon monoxide and methane, as well as air pollutants like ammonia and benzene, while also dynamically adjusting ventilation in response to human presence and room airflow. Literature indicates that combining gas sensing with motion and environmental monitoring enhances the responsiveness and energy efficiency of smart homes and industrial setups. This project contributes to that domain by offering a scalable and affordable solution tailored for small-scale residential or commercial environments, aiming to improve air quality, reduce energy consumption, and enhance occupant safety. The integration of multiple sensor streams and real-time actuation demonstrates the system’s potential as a practical model for future intelligent ventilation frameworks.