Internet of Things Based Health Monitoring System Using Smart Glove
The current healthcare and emergency response systems face significant challenges in preventing fatalities and serious injuries among elderly individuals and those living alone due to falls, delayed emergency care, and insufficient continuous health monitoring. This research proposes the development and evaluation of a cost-effective smart hand glove designed to enhance the safety and health monitoring of these vulnerable populations. The smart hand glove is built using an Arduino Uno microcontroller, an ESP8266 Wi-Fi module, two MPU6050 sensors for fall detection and gesture recognition, and a MAX30100 sensor for heart rate and SpO2 monitoring. These components work together to detect falls, recognize specific hand gestures, and continuously monitor vital signs. Upon detecting a fall or receiving a gesture input, the system triggers automatic SMS and email alerts to designated contacts. Additionally, health monitoring data is transmitted to a secure, password-protected website accessible by healthcare providers. The smart hand glove demonstrated its potential in improving safety and health outcomes for elderly individuals and those living alone by enabling timely medical intervention and continuous health monitoring. This innovative solution addresses critical gaps in emergency response and healthcare for vulnerable populations, ensuring better safety and wellbeing.
Authors
- Anamul Bahar
- Mohiuddin Sharif (ORCID: https://orcid.org/0000-0002-5580-2823)
- Mohammad Faisal Ahmed (ORCID: https://orcid.org/0000-0002-5165-2880)
- Mohammad Woli Ullah (ORCID: https://orcid.org/0000-0002-1632-8778)
- Muhammad Ubaid Ullah Khan (ORCID: https://orcid.org/0000-0003-4447-2598)
- Nowshad Hasan
Institutions
- Chittagong University of Engineering & Technology (BD)
- University of London (GB)
- International Islamic University Chittagong (BD)
Publication Details
- Published
- 2024-11-29
- DOI
- https://doi.org/10.1109/raaicon64172.2024.10928501
- Citations
- 1
- Primary Topic
- IoT-based Smart Home Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.21