Designing High-Efficiency Health Monitoring Systems With Enhanced Sensor Network Optimization

Abstract

This study clarifies the advancement and enhancement of sophisticated sensor network-based health monitoring systems. In response to the growing need for precise health data in real-time, sophisticated devices capable of incessantly monitoring vital parameters have been developed. Modern sensor technologies, including biosensors, IoT devices, and wireless sensor networks, allow these systems to conduct data collecting and processing with little disruption. Optimization methods like as Particle Swarm Optimization (PSO), with machine learning algorithms and energy saving strategies, are used to improve the system's performance, dependability, and battery lifespan. The research emphasizes the creation of resilient and scalable systems applicable to many healthcare contexts, while examining data processing, communication protocols, network design, and sensor selection. Advanced sensor networks will be essential for future health monitoring, since studies demonstrate significant improvements in monitoring precision, system efficacy, and patient outcomes. The current technique is intended to provide a scalable and efficient solution. Furthermore, it would uphold privacy to provide a safe solution.