AI-Driven IoT Framework for Real-Time Air Quality Monitoring and Stress Correlation Analysis

R. Manikandan, Gobinath G., Gokul G., Boobalan D.

2025

Abstract

Burden, air pollution, and stress in homes, offices, and urban settings. This project strikes at the nexus between environmental monitoring and mental health, given that air pollution is a significant global challenge, it has far-reaching implications on physical and mental health. The negative effects of poor air quality on the respiratory and cardiovascular systems are by now well established, but the same cannot be said for the impact of its phytotoxicity on the psyche, especially in real-time, localized contexts. Here, we put forward an AI-driven IoT framework for real-time air quality monitoring and stress prediction, which provides users with actionable intelligence without requiring any manual input. The system is a combination of low-cost IoT sensors (PM2. 5, CO2) using an ESP32 microcontroller to acquire data from the environment in real time and transmit it to a backend hosted in the cloud for analysis. It uses a machine learning model trained on a dataset with information linking air pollution and metrics of stress to predict stress, based on current pollution levels. The anticipated stress levels, along with air quality data, are shown on a mobile app, which also provides recommendations tailored to the user (for instance, “Open windows,” “Avoid outdoor activities”) and issues alerts when air quality worsens or stress levels are expected to increase. Utilizing the advances in artificial intelligence according to Internet of Things this system provides a scalable solution for monitoring the both contributing towards smart health technologies and promote living in sustainable way.

Paper Citation

in Harvard Style

Manikandan R., G. G., G. G. and D. B. (2025). AI-Driven IoT Framework for Real-Time Air Quality Monitoring and Stress Correlation Analysis. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 87-92. DOI: 10.5220/0013892200004919

in Bibtex Style

@conference{icrdicct`2525,
author={R. Manikandan and Gobinath G. and Gokul G. and Boobalan D.},
title={AI-Driven IoT Framework for Real-Time Air Quality Monitoring and Stress Correlation Analysis},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={87-92},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013892200004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - AI-Driven IoT Framework for Real-Time Air Quality Monitoring and Stress Correlation Analysis
SN - 978-989-758-777-1
AU - Manikandan R.
AU - G. G.
AU - G. G.
AU - D. B.
PY - 2025
SP - 87
EP - 92
DO - 10.5220/0013892200004919
PB - SciTePress