Design Remote Monitoring System for Patients at Real-Time based on Internet of Things (IoT)

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Author(s)

Satar Habib Mnaathr 1,*

1. Department of Biomedical Engineering, Collage of Engineering, University of Thi-Qar, Thi-Qar 64001, Iraq

* Corresponding author.

DOI: https://doi.org/10.5815/ijem.2023.05.01

Received: 20 Jul. 2023 / Revised: 13 Aug. 2023 / Accepted: 10 Sep. 2023 / Published: 8 Oct. 2023

Index Terms

Internet of Things, Health Monitoring, ESP32 microcontroller, GPS location, Blynk IoT cloud platform

Abstract

The remote real-time patient monitoring system is a healthcare solution that uses ESP32 microcontroller and Blynk IoT cloud platform to monitor the vital signs of patients, including temperature, oxygen saturation, and heartbeat. The system also monitors the environmental factors surrounding the patient, such as temperature and humidity, and determines the GPS location of the patient. Additionally, the system includes an alarm device that alerts healthcare providers in case of emergency. In this paper we design system aims to provide continuous care and monitoring for patients, whether they are in hospitals, at home, or outside. By using Blynk IoT cloud platform, the system aims to reduce the percentage of medical errors and deaths by providing real-time monitoring of the patient's vital signs and environmental conditions, allowing healthcare providers to respond to emergencies quickly and efficiently. The IoT-based patient monitoring system consists of sensors that collect data on the patient's vital signs and environmental factors. The collected data is transmitted wirelessly to the Blynk IoT cloud platform, where it is processed and analyzed. Healthcare providers can access the data through the Blynk mobile app and receive alerts in case of any abnormalities or emergencies.

Cite This Paper

Satar Habib Mnaathr, "Design Remote Monitoring System for Patients at Real-Time based on Internet of Things (IoT)", International Journal of Engineering and Manufacturing (IJEM), Vol.13, No.5, pp. 1-10, 2023. DOI:10.5815/ijem.2023.05.01

Reference

[1]Bhuiyan, M. N., Billah, M. M., Bhuiyan, F., Bhuiyan, M. A. R., Hasan, N., Rahman, M. M., ... & Niu, M. (2022). Design and implementation of a feasible model for the IoT based ubiquitous healthcare monitoring system for rural and urban areas. IEEE Access, 10, 91984-91997.
[2]Abdulmalek, S., Nasir, A., Jabbar, W. A., Almuhaya, M. A., Bairagi, A. K., Khan, M. A. M., & Kee, S. H. (2022, October). IoT-based healthcare-monitoring system towards improving quality of life: A review. In Healthcare (Vol. 10, No. 10, p. 1993). MDPI.
[3]Chopade, S. S., Gupta, H. P., & Dutta, T. (2023). Survey on Sensors and Smart Devices for IoT Enabled Intelligent Healthcare System. Wireless Personal Communications, 1-39.
[4]Chu, K. H., Tung, H. H., Clinciu, D. L., Hsu, H. I., Wu, Y. C., Hsu, C. I., ... & Pan, S. J. (2022). A preliminary study on self-healing and self-health management in older adults: Perspectives from healthcare professionals and older adults in Taiwan. Gerontology and Geriatric Medicine, 8, 23337214221077788.
[5]White, J. J. (2023). Developing a Diagnostic Approach to Multi-Dimensional Poverty (Doctoral dissertation, University of Toronto (Canada)).
[6]Janakiraman, R., Park, E., M. Demirezen, E., & Kumar, S. (2023). The effects of health information exchange access on healthcare quality and efficiency: An empirical investigation. Management Science, 69(2), 791-811.
[7]Jha, A., Athanerey, A., & Kumar, A. (2022). Role and challenges of internet of things and informatics in Healthcare research. Health and Technology, 12(4), 701-712.
[8]Azadi, A., & García-Peñalvo, F. J. (2023, January). Synergistic Effect of Medical Information Systems Integration: To What Extent Will It Affect the Accuracy Level in the Reports and Decision-Making Systems?. In Informatics (Vol. 10, No. 1, p. 12). MDPI.
[9]Harper, A. (2022). Nursing Leadership Perceptions of Clinical Pathways After Transitioning to an Electronic Health Record in the Acute Care Setting (Doctoral dissertation, Université d'Ottawa/University of Ottawa).
[10]Elbagoury, B. M., Vladareanu, L., Vlădăreanu, V., Salem, A. B., Travediu, A. M., & Roushdy, M. I. (2023). A Hybrid Stacked CNN and Residual Feedback GMDH-LSTM Deep Learning Model for Stroke Prediction Applied on Mobile AI Smart Hospital Platform. Sensors, 23(7), 3500.
[11]Menon, S. P., Shukla, P. K., Sethi, P., Alasiry, A., Marzougui, M., Alouane, M. T. H., & Khan, A. A. (2023). An intelligent diabetic patient tracking system based on machine learning for E-health applications. Sensors, 23(6), 3004.
[12]Alanazi, F., Gay, V., & Alturki, R. (2022). Poor Compliance of Diabetic Patients with AI-Enabled E-Health Self-Care Management in Saudi Arabia. Information, 13(11), 509.
[13]Serikul, P., Nakpong, N., & Nakjuatong, N. (2018, November). Smart farm monitoring via the Blynk IoT platform: case study: humidity monitoring and data recording. In 2018 16th International conference on ICT and knowledge engineering (ICT&KE) (pp. 1-6). IEEE.
[14]Mnaathr, S. H. (2021, February). Design and Simulation Networking Operating Model for Virtual Network System (VNS). In 2021 7th International Engineering Conference “Research & Innovation amid Global Pandemic.
[15]Saidi, A., Hadj Kacem, M., Tounsi, I., & Hadj Kacem, A. (2022, June). Adopting the Internet of Things Technology to Remotely Monitor COVID-19 Patients. In International Conference on Smart Homes and Health Telematics (pp. 166-180). Cham: Springer International Publishing.