Context-Aware Adaptive Framework for e-Health Monitoring

TL;DR

This paper introduces a context-aware adaptive framework for e-health monitoring that optimizes resource usage while accurately tracking daily activities of dependent persons, enhancing efficiency and personalization.

Contribution

It presents a novel adaptive monitoring algorithm that considers user profile, activities, and their relationships to improve e-health service efficiency.

Findings

Significant reduction in network, energy, and processing usage.

Framework effectively adapts to individual contexts.

Enhanced accuracy in activity recognition.

Abstract

For improving e-health services, we propose a context-aware framework to monitor the activities of daily living of dependent persons. We define a strategy for generating long-term realistic scenarios and a framework containing an adaptive monitoring algorithm based on three approaches for optimizing resource usage. The used approaches provide a deep knowledge about the person's context by considering: the person's profile, the activities and the relationships between activities. We evaluate the performances of our framework and show its adaptability and significant reduction in network, energy and processing usage over a traditional monitoring implementation.