Integrating IoT Sensors and Intelligent Automation for Real‑Time Vital Sign Monitoring and Emergency Response

Authors

  • Avanti Shivaji Pawar, Vishakha Kiran Jadhav

Keywords:

IoT, Intelligent Automation, Vital Sign Monitoring, Emergency Response, Smart Healthcare, Wearable Sensors, AI Healthcare, Edge Computing

Abstract

The rapid advancement of the Internet of Things (IoT), wearable sensors, artificial intelligence (AI), and intelligent automation has significantly transformed modern healthcare systems. Real-time vital sign monitoring using IoT-enabled devices provides continuous observation of physiological parameters such as heart rate, body temperature, blood oxygen saturation (SpO₂), respiratory rate, and blood pressure. Traditional healthcare monitoring systems often fail to provide immediate responses during emergencies due to delayed data transmission and lack of intelligent decision-making mechanisms. This research proposes an integrated IoT-based intelligent healthcare framework capable of continuous patient monitoring and automated emergency response. The proposed architecture combines wearable biosensors, cloud computing, edge intelligence, and automated alert systems to improve patient safety and reduce response time in critical situations. The study evaluates the effectiveness of the system through simulation-based analysis involving 100 virtual patients monitored over a 30-day observation period. Parameters such as data latency, emergency detection accuracy, response time, and system reliability were analyzed. Results indicate that the proposed system achieves 96.8% emergency detection accuracy with average response latency below 2.1 seconds. Intelligent automation reduced emergency response time by approximately 42% compared to conventional hospital monitoring methods. The integration of AI-based predictive analytics further improved anomaly detection efficiency and reduced false alarms. The study demonstrates the feasibility of IoT-driven healthcare systems for smart hospitals, elderly care, home healthcare, and remote patient monitoring applications.

Downloads

Download data is not yet available.

References

Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2016).“Internet of Things (IoT): A vision, architectural elements, and future directions.”Future Generation Computer Systems, 29(7), 1645–1660.

Alemdar, H., & Ersoy, C. (2016).“Wireless sensor networks for healthcare: A survey.”Computer Networks, 54(15), 2688–2710.

Gope, P., & Hwang, T. (2016).“BSN-Care: A secure IoT-based modern healthcare system using body sensor network.”IEEE Sensors Journal, 16(5), 1368–1376.

Patel, S., Park, H., Bonato, P., Chan, L., & Rodgers, M. (2017).“A review of wearable sensors and systems with application in rehabilitation.”Journal of NeuroEngineering and Rehabilitation, 9(1), 21–35.

Rahmani, A. M., et al. (2017). “Exploiting smart e-health gateways at the edge of healthcare Internet-of-Things.”Future Generation Computer Systems, 78, 641–658.

Islam, S. M. R., Kwak, D., Kabir, M. H., Hossain, M., & Kwak, K. S. (2017).“The Internet of Things for health care: A comprehensive survey.”IEEE Access, 3, 678–708.

Verma, P., Sood, S. K., & Kalra, S. (2017).“Cloud-centric IoT based disease diagnosis healthcare framework.”Journal of Parallel and Distributed Computing, 116, 27–38.

Singh, R. P., Javaid, M., Haleem, A., & Suman, R. (2018).“Internet of Things (IoT) applications to fight against COVID-19 pandemic.”Diabetes & Metabolic Syndrome, 14(4), 521–524.

Hassan, M. M., et al. (2018).“A cloud-based IoT framework for remote patient monitoring.”IEEE Journal of Biomedical and Health Informatics, 21(4), 1014–1024.

Ahmed, M. U., Bjorkman, M., & Causevic, A. (2018).“An overview on the Internet of Things for health monitoring systems.”International Journal of Computer Applications, 975, 8887.

Qi, J., Yang, P., Min, G., Amft, O., Dong, F., & Xu, L. (2018).“Advanced Internet of Things for personalised healthcare systems.”Computing, 100(11), 1149–1166.

Rodrigues, J. J. P. C., et al. (2018).“Enabling technologies for the Internet of Health Things.”IEEE Access, 6, 13129–13141.

Chen, M., Ma, Y., Song, J., Lai, C. F., & Hu, B. (2019).“Smart clothing: Connecting human with clouds and big data for sustainable health monitoring.”Mobile Networks and Applications, 21(5), 825–845.

Kumar, P., & Lee, H. J. (2019).“Security issues in healthcare applications using wireless medical sensor networks.”Sensors, 12(1), 55–91.

Ray, P. P. (2019).“A survey on Internet of Things architectures.”Journal of King Saud University – Computer and Information Sciences, 30(3), 291–319.

Iwendi, C., et al. (2020).“COVID-19 patient health prediction using boosted random forest algorithm.”Frontiers in Public Health, 8, 357.

Covi, E., Donati, E., Heidari, H., et al. (2020).“Adaptive extreme edge computing for wearable devices.”IEEE Transactions on Biomedical Circuits and Systems, 14(6), 1238–1250.

Liang, Q., Shenoy, P., & Irwin, D. (2020).“AI on the edge: Rethinking AI-based IoT applications using specialized edge architectures.”IEEE Internet Computing, 24(5), 12–22.

Greco, L., Percannella, G., Ritrovato, P., Vento, M., & Vigilante, V. (2020).“Trends in IoT based solutions for health care: Moving AI to the edge.”Pattern Recognition Letters, 135, 346–353.

Spicher, N., Klingenberg, A., Purrucker, V., & Deserno, T. M. (2020).“Edge computing in 5G cellular networks for real-time analysis of electrocardiography recorded with wearable textile sensors.”IEEE Access, 8, 209872–209881.

Downloads

Published

30.06.2021

How to Cite

Avanti Shivaji Pawar. (2021). Integrating IoT Sensors and Intelligent Automation for Real‑Time Vital Sign Monitoring and Emergency Response. International Journal of Intelligent Systems and Applications in Engineering, 9(4), 509–518. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/8247

Issue

Section

Research Article