The Internet of Things (IoT) has transformed the way we interact with the world and one of its most impactful applications is in healthcare, particularly telemonitoring, which continuously tracks patients' vital signs and provides real-time insights. However, managing the immense volume of data requires advanced technologies, such as Artificial Intelligence (AI). Furthermore, AI can enable proactivity and early disease detection, which until now is the complete responsibility of the physician, therefore in reducing hospitalizations, improving patient outcomes and lowering costs. This is especially critical for conditions like Heart Failure and COVID-19, where rapid deterioration necessitates timely intervention. Similarly, IoT-powered monitoring is essential in industrial settings to ensure worker safety and well-being. Current stress monitoring methods rely on offline assessments, limiting real-time prevention, which can be introduced by AI-based tools. To address these challenges, this research integrates AI into telemonitoring for proactive care in both healthcare and industrial applications.

Exploiting Internet of Things and Artificial Intelligence Technologies for Proactive Patient-centered Healthcare and Work Safety: from Concept to Clinical Trial

OLIVELLI, MARTINA
2025

Abstract

The Internet of Things (IoT) has transformed the way we interact with the world and one of its most impactful applications is in healthcare, particularly telemonitoring, which continuously tracks patients' vital signs and provides real-time insights. However, managing the immense volume of data requires advanced technologies, such as Artificial Intelligence (AI). Furthermore, AI can enable proactivity and early disease detection, which until now is the complete responsibility of the physician, therefore in reducing hospitalizations, improving patient outcomes and lowering costs. This is especially critical for conditions like Heart Failure and COVID-19, where rapid deterioration necessitates timely intervention. Similarly, IoT-powered monitoring is essential in industrial settings to ensure worker safety and well-being. Current stress monitoring methods rely on offline assessments, limiting real-time prevention, which can be introduced by AI-based tools. To address these challenges, this research integrates AI into telemonitoring for proactive care in both healthcare and industrial applications.
30-mar-2025
Italiano
artificial intelligence
covid-19
expert system
heart failure
HF
industrial environment
monitoring plan update
proactive care
stress classification
stress detection
telemedicine
telemonitoring
WHF
Bechini, Alessio
Fanucci, Luca
Donati, Massimiliano
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/215681
Il codice NBN di questa tesi è URN:NBN:IT:UNIPI-215681