Development of a low-cost IoT-based e-health monitoring system for diabetic patients

Abstract The global need for diabetic patient self-care is increasing. The current global epidemiology of diabetes calls for an improved healthcare management system, particularly in poorer countries, to minimize the burden of diabetes complications and mortality. The main objective of this study seeks to increase diabetic patients’ access to healthcare by utilizing internet of things-based smart self-care high-tech devices. The proposed model was integrated with a Blynk software and hosted in NodeMCU, allowing user to access diabetic health metric from the smartphones or interconnected devices. The e-monitoring system has an inbuilt feedback mechanism that provides online access to healthcare provider for immediate insulin therapy. Furthermore, patients suffering from acute diabetic metabolic issues may have difficulty visiting the hospital. Therefore, they can use the proposed model to track and monitor their blood glucose levels, as well as communicate remotely with their doctor, so improving their health while saving money and time. Also, diabetic patients can use this system to record their health condition on their phone, decreasing the need for doctor visits and clinical medical procedure. The proposed system has several advantages, including speedy internet access and remote monitoring from anywhere in the world. This research also helps to achieve the United Nations’ Sustainable Development Goals, which include good health and well-being, equitable healthcare access, and sustainable cities and communities.

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Publication Details

Journal
Journal of Electrical Systems and Information Technology
Published
2024-11-25
DOI
https://doi.org/10.1186/s43067-024-00178-6
Citations
8
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
5.66
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article

Development of a low-cost IoT-based e-health monitoring system for diabetic patients

Ayodeji Akinsoji Okubanjo, Odeyinka Olumide, Okandeji Alexander, Akinloye Benjamin et al.
8 citations
Journal of Electrical Systems and Information Technology
Artificial Intelligence in Healthcare
5.66
article

Development of a low-cost IoT-based e-health monitoring system for diabetic patients

Ayodeji Akinsoji Okubanjo, Odeyinka Olumide, Okandeji Alexander, Akinloye Benjamin, Oluyemi Oluwatoyin
article en
8 citations

Abstract

Abstract The global need for diabetic patient self-care is increasing. The current global epidemiology of diabetes calls for an improved healthcare management system, particularly in poorer countries, to minimize the burden of diabetes complications and mortality. The main objective of this study seeks to increase diabetic patients’ access to healthcare by utilizing internet of things-based smart self-care high-tech devices. The proposed model was integrated with a Blynk software and hosted in NodeMCU, allowing user to access diabetic health metric from the smartphones or interconnected devices. The e-monitoring system has an inbuilt feedback mechanism that provides online access to healthcare provider for immediate insulin therapy. Furthermore, patients suffering from acute diabetic metabolic issues may have difficulty visiting the hospital. Therefore, they can use the proposed model to track and monitor their blood glucose levels, as well as communicate remotely with their doctor, so improving their health while saving money and time. Also, diabetic patients can use this system to record their health condition on their phone, decreasing the need for doctor visits and clinical medical procedure. The proposed system has several advantages, including speedy internet access and remote monitoring from anywhere in the world. This research also helps to achieve the United Nations’ Sustainable Development Goals, which include good health and well-being, equitable healthcare access, and sustainable cities and communities.

Journal of Electrical Systems and Information TechnologyVol. 11(1)
University of Lagos (NG), Federal University of Petroleum Resource Effurun (NG), Olabisi Onabanjo University (NG)
Openalex Percentile: Top 4%
Artificial Intelligence in Healthcare
5.66
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