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@article{178100,
        author = {E.Sasikala and Koppala Komala and Perimidi Sirisha and Dhara Kishore and Pigilam Sandhya and Pulla Yedukondalu},
        title = {AIR QUALITY MONITOR AND PREDICTION SYSTEM USING IOT AND MACHINE LEARNING ALGORITHMS},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {2170-2177},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178100},
        abstract = {The pollution level is increasing rapidly due to factors like industries, urbanization, increase in population, and vehicle use which can affect human health. IOT Based Air Pollution Monitoring System is used to monitor Air Quality over a web server using the Internet. It will trigger an alarm when the air quality goes down beyond a certain level, which means when there are sufficient amounts of harmful gases in the air like CO2, smoke, alcohol, NH3 and NOx. It will show the air quality in PPM on the show data and the webpage so that they can easily monitor air pollution. The system uses MQ135 and MQ6 sensors for monitoring Air Quality as it detects the most harmful gases and can measure their amount accurately. The system uses an Arduino UNO to connect to an IOT platform and provide information about contaminants to the staff. Based on a microcontroller, the system employs gas sensors, DHT11 temperature and humidity, a display, and a buzzer. Arduino UNO and MQ135 sensors are intended to use as monitoring data and alert systems for air pollution. In the present research, an air pollution prediction model is established with the help of machine learning models. Machine learning techniques such as Q-Learning applied to the dataset. It is simple and fast to alter it to fit our changing needs. Then, the target of this project is to apply the machine learning (Q-Learning) concept for the prediction and analysis of gas sensors' pollution levels so that we can analyze the pollution level due to the pollutant gases based on prediction analysis.},
        keywords = {Machine Learning, Accuracy, Classifier, Arduino UNO, Sensor, Q-Learning.},
        month = {May},
        }