DESIGN OPTIMIZATION AND PERFORMANCE EFFICIENCY OF EMBEDDED IOT HEALTHCARE DEVICES: AN ELECTRONICS ENGINEERING ANALYSIS FOR SCALABLE MEDICAL SYSTEMS

Abstract

The introduction of IoT Solutions to healthcare is quickly shifting the way we treat medically. Through IoT technologies, health systems have evolved into systems allowing for continuous monitoring of patients from anywhere in the world. Patients' data can be transmitted in real-time to their providers, resulting in improved clinical decision-making. This research evaluates the engineering aspect of IoT-enabled medical devices, specifically: the design of embedded systems; the architecture of sensors; the effectiveness of communications; and the performance at the edge of devices (i.e., optimization). Using a secondary-source analytical approach, this study will synthesize literature, technical frameworks and peer-reviewed journal articles to evaluate important engineering difficulties and limitations at the system level.

The paper discusses the integration of embedded electronics with biosensors. It discusses signal conditioning, low power circuit design, and hardware reliability. Its discussion includes evaluations of the wireless communication channels and the issues of latency and bandwidth with respect to real-time healthcare delivery. The role of edge; computing is critically analyzed as a support layer which increases the responsiveness of the system, reduces communication overhead, and allows for efficient data processing at the device level. Also discussed are security and privacy issues, as well as scalability challenges in the Indian healthcare environment.

There is a proposed an Edge-Assisted Embedded Optimization Framework which addresses the latency-security-power trade-off through local analytics, adaptive communication and performance control via feedback. The results of the study show that embedding optimised embedded design with edge computing creates higher efficiencies, greater reliability, and increased scalability for any internet based health systems. This study has provided invaluable information for creating cost effective, secure and high performance Medical Devices that can be utilized in a variety of healthcare infrastructure types.