TY - GEN
T1 - Performance Analysis of IoT-based Healthcare Monitoring System using Raspberry Pi
AU - Choubey, Chandan Kumar
AU - Thakur, Prabhat
AU - Hussain, Idris
AU - Deshalahre, Devendra
AU - Chavda, Lay
AU - Isha,
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Healthcare monitoring systems are now more crucial than ever since they assist in tracking crucial health data in real-time. In this paper, an IoT-based Raspberry Pi healthcare monitoring system is proposed. Several sensors built into the device take vital signs like heart rate, blood pressure, temperature, and oxygen saturation readings. The system is made to be user-friendly and reasonably priced to be available to various patients. The Raspberry Pi platform is the best option for this application because it is simple to customize and integrate with other technologies. The gathered data is shown on a web interface that only authorized individuals can access. By delivering real-time data that can assist in early health problem detection, the suggested system has the potential to enhance patient outcomes greatly. By automating the process of data gathering and processing, it can also lessen the strain on healthcare workers. Overall, this research underlines the advantages of adopting IoT systems and shows the potential of Raspberry Pi technology for healthcare monitoring.
AB - Healthcare monitoring systems are now more crucial than ever since they assist in tracking crucial health data in real-time. In this paper, an IoT-based Raspberry Pi healthcare monitoring system is proposed. Several sensors built into the device take vital signs like heart rate, blood pressure, temperature, and oxygen saturation readings. The system is made to be user-friendly and reasonably priced to be available to various patients. The Raspberry Pi platform is the best option for this application because it is simple to customize and integrate with other technologies. The gathered data is shown on a web interface that only authorized individuals can access. By delivering real-time data that can assist in early health problem detection, the suggested system has the potential to enhance patient outcomes greatly. By automating the process of data gathering and processing, it can also lessen the strain on healthcare workers. Overall, this research underlines the advantages of adopting IoT systems and shows the potential of Raspberry Pi technology for healthcare monitoring.
KW - Critical thresholds
KW - Life-threatening incidents mitigation
KW - Preventative care
KW - Regional assessment
KW - Remote operation
KW - Seamless monitoring
KW - Unified platform
UR - http://www.scopus.com/inward/record.url?scp=85196869443&partnerID=8YFLogxK
U2 - 10.1109/I2CT61223.2024.10543391
DO - 10.1109/I2CT61223.2024.10543391
M3 - Conference contribution
AN - SCOPUS:85196869443
T3 - 2024 IEEE 9th International Conference for Convergence in Technology, I2CT 2024
BT - 2024 IEEE 9th International Conference for Convergence in Technology, I2CT 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE International Conference for Convergence in Technology, I2CT 2024
Y2 - 5 April 2024 through 7 April 2024
ER -