AI and IoT-Based Smart Posture and Lung Function Monitoring System

DOI

10.2991/978-94-6239-654-8_62How to use a DOI?

Keywords

IoT; Artificial Intelligence; Smart Wearable; Posture Monitoring; Lung Function; Stress Detection

Abstract

Poor posture and stress-induced improper breathing are the usual causes of respiratory inefficiency among students and office workers with sedentary lifestyles. Conventional monitoring approaches tend to be bulky, single-parameter, and unsuitable for continuous self-assessment, resulting in undetected reductions in lung efficiency due to muscle fatigue and stress-related variations. In the light of the above-explained limitations, this work proposes an AI- and IoT-enabled intelligent wearable system to track continuously the posture angle, breathing rate, lung efficiency, muscle activity, and cognitive stress of a person in real time. In this proposed system, an ESP32 microcontroller is integrated with a number of physiological sensors are IMU for detecting posture angles, an airflow sensor for analysis of breathing and lung efficiency, an EMG sensor for evaluating muscle activity, and a MAX30102 module for estimation of stress based on HRV. ESP32 will perform data acquisition, signal preprocessing, and AI-based classification, while IoT connectivity will send the processed data to the web-based dashboard where all the parameters shall be presented live. Indeed, experimental observations confirm that the system can detect posture deviations with an accuracy of ± 2°, evaluate breathing rate and lung efficiency with over 90% correlation to manual measurements, and track stress variations reliably using heart rate variability. The dashboard provides for continuous real-time visualization of all parameters being monitored, whereby users are in a position to instantly observe physiological changes even during daily activities. The proposed wearable system is compact, non-invasive, and precise for real-time posture and respiratory tracking. Suitable applications may include rehabilitation, occupational ergonomics, and preventive respiratory care, potentially enabling long- lasting well-being through continuous physiological assessment.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - T. Sowmya Shree
AU  - S. Mangai
AU  - S. D. Myvizhi
AU  - K. Nithya
AU  - S. Vijaya Srinivas
AU  - E. Yamuna Shri
PY  - 2026
DA  - 2026/04/24
TI  - AI and IoT-Based Smart Posture and Lung Function Monitoring System
BT  - Proceedings of the Global Conference on Sustainable Energy Systems, Smart Electronics and Intelligent Computing (GCSESEIC 2025)
PB  - Atlantis Press
SP  - 793
EP  - 802
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6239-654-8_62
DO  - 10.2991/978-94-6239-654-8_62
ID  - Shree2026
ER  -