Smart health monitoring: an interactive Raspberry Pi-based system for managing diabetes and hypertension in children

The rising prevalence of diabetes and hypertension among children calls for innovative solutions to enhance health management. This study introduces a novel pediatric health monitoring system integrating real-time data acquisition, automated alerts, voice-assisted interventions, and gamified educational elements to engage young users. The system demonstrated a rapid response time of 1.8 seconds to abnormal readings, a socket latency of 2.6 seconds, and achieved an accuracy of 98.7% in detecting critical health anomalies, ensuring timely interventions and reliable monitoring. By combining automated real-time monitoring with a gamified experience, the system empowers caregivers to act swiftly, enhances user engagement, and improves health outcomes for children. This work lays the groundwork for advancements in telemedicine, personalized healthcare, and child-centric digital health solutions.

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Publication Details

Journal
Journal of Cloud Computing Advances Systems and Applications
Published
2025-11-25
DOI
https://doi.org/10.1186/s13677-025-00796-z
Primary Topic
Mobile Health and mHealth Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart health monitoring: an interactive Raspberry Pi-based system for managing diabetes and hypertension in children

Ruppikha Sree Shankar, D. Cenitta, Krishnaraj Chadaga, R. Vijaya Kumar Reddy et al.
Journal of Cloud Computing Advances Systems and Applications
Mobile Health and mHealth Applications
article

Smart health monitoring: an interactive Raspberry Pi-based system for managing diabetes and hypertension in children

Ruppikha Sree Shankar, D. Cenitta, Krishnaraj Chadaga, R. Vijaya Kumar Reddy, Tanuja Shailesh
article en

Abstract

The rising prevalence of diabetes and hypertension among children calls for innovative solutions to enhance health management. This study introduces a novel pediatric health monitoring system integrating real-time data acquisition, automated alerts, voice-assisted interventions, and gamified educational elements to engage young users. The system demonstrated a rapid response time of 1.8 seconds to abnormal readings, a socket latency of 2.6 seconds, and achieved an accuracy of 98.7% in detecting critical health anomalies, ensuring timely interventions and reliable monitoring. By combining automated real-time monitoring with a gamified experience, the system empowers caregivers to act swiftly, enhances user engagement, and improves health outcomes for children. This work lays the groundwork for advancements in telemedicine, personalized healthcare, and child-centric digital health solutions.

Journal of Cloud Computing Advances Systems and ApplicationsVol. 14(1)
Manipal Academy of Higher Education (IN)
Openalex Percentile: Top 47%
Mobile Health and mHealth Applications
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Smart health monitoring: an interactive Raspberry Pi-based system for managing diabetes and hypertension in children — Ruppikha Sree Shankar, D. Cenitta, et al. · Journal of Cloud Computing Advances Systems and Applications (2025) | TGRS Research Map | TGRS