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ZENODO
Article . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
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IoT - Based Real Time Patient Health Monitoring System Using Raspberry Pi And Cloud Integration

Authors: Dhanya sri S; Barath kanna G; Dr. R. Karthik;

IoT - Based Real Time Patient Health Monitoring System Using Raspberry Pi And Cloud Integration

Abstract

Continuous monitoring of patient health parameters is a critical requirement in modern healthcare systems, particularly for elderly patients, individuals with chronic conditions, and post-operative care scenarios. Traditional hospital-based monitoring systems are expensive, stationary, and impractical for home-based care environments. This project proposes an IoT-Based Real-Time Patient Health Monitoring System that uses a Raspberry Pi microcomputer interfaced with multiple biometric sensors to continuously collect and transmit vital health parameters including body temperature, heart rate, blood oxygen saturation level, and blood pressure readings. The collected data is transmitted wirelessly to a cloud platform where it is stored, processed, and made accessible through a web-based dashboard. Automated alert mechanisms notify healthcare providers and designated caregivers when recorded values fall outside predefined safe thresholds. The system is designed to be compact, affordable, and easy to operate without requiring technical expertise from patients or caregivers. Testing results confirm that the system achieves high sensor accuracy and reliable data transmission under real-world operating conditions. This research demonstrates how Internet of Things technology can be integrated with cloud computing to deliver an accessible and effective remote patient monitoring solution that reduces healthcare costs and improves patient outcomes.

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green