Authors :
Lakshmi Nagaraju Kojja; Narasimhappadu Tamminaina; Akshitha Jangam
Volume/Issue :
Volume 10 - 2025, Issue 10 - October
Google Scholar :
https://tinyurl.com/37y8s4hh
Scribd :
https://tinyurl.com/2ubty3ds
DOI :
https://doi.org/10.38124/ijisrt/25oct882
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Abstract :
This paper introduces an innovative embedded IoT system designed for real-time acquisition and cloud-based
analysis of multi-dimensional bio-behavioral parameters. Integrating advanced sensors for physiological signals such as
heart rate, temperature, finger movement, EEG, and ECG with robust wireless communication (ESP8266, GSM, GPS), the
proposed platform provides comprehensive, continuous data to an AWS-powered cloud infrastructure. The system leverages
this interoperable data for advanced analytics, facilitating digital twinning of user health profiles to enable personalized
diagnostics, medication guidance, ergonomic product design, and behavioral insights. Uniquely, the platform incorporates
mental and physical status recognition such as detecting sense of urination and emotional states through embedded
intelligence, enabling new dimensions of preventive and participatory healthcare. This dynamic data pipeline supports not
only enhanced clinical care, but also applications in insurance claim validation, product development, and remote patient
management, enabled by resilient power backup and real-time alerting systems. The multidisciplinary design aims to bridge
the gap between medical monitoring, digital twin technology, and user-focused analytics, thus establishing a new paradigm
for integrated, actionable health management in both clinical and consumer contexts.
Keywords :
Digital Twin, Bio-Behavioral Analytics, AWS DynamoDB, Ergonomics, Insurance Analytics.
References :
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This paper introduces an innovative embedded IoT system designed for real-time acquisition and cloud-based
analysis of multi-dimensional bio-behavioral parameters. Integrating advanced sensors for physiological signals such as
heart rate, temperature, finger movement, EEG, and ECG with robust wireless communication (ESP8266, GSM, GPS), the
proposed platform provides comprehensive, continuous data to an AWS-powered cloud infrastructure. The system leverages
this interoperable data for advanced analytics, facilitating digital twinning of user health profiles to enable personalized
diagnostics, medication guidance, ergonomic product design, and behavioral insights. Uniquely, the platform incorporates
mental and physical status recognition such as detecting sense of urination and emotional states through embedded
intelligence, enabling new dimensions of preventive and participatory healthcare. This dynamic data pipeline supports not
only enhanced clinical care, but also applications in insurance claim validation, product development, and remote patient
management, enabled by resilient power backup and real-time alerting systems. The multidisciplinary design aims to bridge
the gap between medical monitoring, digital twin technology, and user-focused analytics, thus establishing a new paradigm
for integrated, actionable health management in both clinical and consumer contexts.
Keywords :
Digital Twin, Bio-Behavioral Analytics, AWS DynamoDB, Ergonomics, Insurance Analytics.