Automated Patient Data Monitoring System using IoT Enabled Wearable Device

The project introduces all inclusive system of real time monitoring and prediction of health safety levels of human beings. Sensors are provided in the wristband that sense body parameters such as body temperature, oxygen saturation levels, pulse rate, blood pressure. These collected data streams into a central server that stores and analyses the data. This will help predict health safety levels using various machine learning algorithms and XGBoost, Logistic Regression, K Nearest Neighbors, etc. It makes use of a database management system for the efficient organization and retrieval of data. The body parameter recordings are stored safely as a database for reference in the future. It uses a microcontroller Node MCU and Arduino Uno giving it real time predictions of how the case may look in the days ahead. Furthermore, using the Android application, gives preview prediction as well monitor health levels safety over some periods for both users and doctors. This holistic approach avails insight into causes or triggers of the abnormal health situation and allows a person suffering from the health problem to be in control

Publication Details

Published
2024-11-23
DOI
https://doi.org/10.59544/zodk6835/icrcct24p13
Primary Topic
Smart Systems and Machine Learning
Type
article
Field-Weighted Citation Impact
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article

Automated Patient Data Monitoring System using IoT Enabled Wearable Device

Smart Systems and Machine Learning
article

Automated Patient Data Monitoring System using IoT Enabled Wearable Device

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Abstract

The project introduces all inclusive system of real time monitoring and prediction of health safety levels of human beings. Sensors are provided in the wristband that sense body parameters such as body temperature, oxygen saturation levels, pulse rate, blood pressure. These collected data streams into a central server that stores and analyses the data. This will help predict health safety levels using various machine learning algorithms and XGBoost, Logistic Regression, K Nearest Neighbors, etc. It makes use of a database management system for the efficient organization and retrieval of data. The body parameter recordings are stored safely as a database for reference in the future. It uses a microcontroller Node MCU and Arduino Uno giving it real time predictions of how the case may look in the days ahead. Furthermore, using the Android application, gives preview prediction as well monitor health levels safety over some periods for both users and doctors. This holistic approach avails insight into causes or triggers of the abnormal health situation and allows a person suffering from the health problem to be in control

Good health and well-being
Openalex Percentile: Top 75%
Smart Systems and Machine Learning
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