A novel IoT-aware wearable sensor device for healthcare data management framework using hybrid optimization algorithm

Area of Science:

• * Computer Science
• * Biomedical Engineering
• * Data Science

Background:

• * The Internet of Things (IoT) enhances patient care through connected technologies and clinicians, but managing sensor data in resource-limited IoT healthcare systems presents significant challenges.
• * Traditional data transmission networks face issues like limited battery life and resources, hindering efficient healthcare applications.
• * Continuous monitoring via sensor devices in IoT healthcare necessitates robust and energy-efficient data management strategies.

Purpose of the Study:

• * To develop an effective healthcare data management system using IoT-aided wearable sensor devices to overcome traditional model limitations.
• * To establish a cloud layer for robust communication, facilitating health data collection, transmission, and monitoring.
• * To implement an optimal resource allocation strategy for minimizing energy consumption during data transmission in IoT healthcare.

Main Methods:

• * Development of the Hybrid Tasmanian Devil Archery Algorithm (HTDAA), combining Tasmanian Devil Optimization (TDO) and Archery Algorithm (AA) for multi-objective constraint balance and convergence.
• * Formulation of an objective function based on normalized energy ratio, buffer memory ratio, and packet arrival data rate for effective resource allocation.
• * Integration of the HTDAA into an IoT setup for optimal channel resource allocation in health data transmission.

Main Results:

• * The HTDAA demonstrated a significant enhancement in packet arrival ratio: 5.6% over ESO, 31.7% over SLO, 3.3% over TDO, and 18.1% over AA.
• * Optimal resource allocation using HTDAA effectively reduces energy consumption in data transmission.
• * Simulations confirmed that the HTDAA-based system provides more robust and energy-efficient solutions compared to traditional models.

Conclusions:

• * The proposed HTDAA offers a superior approach to resource allocation in IoT healthcare data management.
• * The HTDAA-based system achieves significant improvements in energy efficiency and data transmission robustness.
• * This work presents a viable solution for addressing the data management challenges in IoT-enabled healthcare systems.