Towards Time-Critical Healthcare Systems Leveraging IoT Data Transmission, Fog Resource Optimization, and Cloud Integration for Enhanced Remote Patient Monitoring

Abstract

Cloud computing, fog resource optimization, and IoT data transfer are all used in this effort to improve remote patient monitoring in healthcare systems that have a tight deadline. Low-latency communication, effective resource allocation, and scalable data storage are guaranteed by the system, which connects IoT devices with cloud and fog infrastructures. Rapid medical responses are made possible by this strategy, particularly in isolated locations. Prioritizing transmission time reduction and energy efficiency enables real-time data processing, which is essential for prompt decision-making and better healthcare delivery. The system's capacity to efficiently start required medical actions is demonstrated by its remarkable 96% alert accuracy in real-time patient monitoring. The study not only demonstrates how well IoT, fog, and cloud technologies can be integrated, but it also analyzes different system configurations to assess performance, illuminating how these technologies work in concert to provide dependable and effective remote healthcare monitoring. By guaranteeing that patients receive precise and timely care regardless of their location, this integrated solution significantly improves healthcare systems and promotes improved health outcomes and more effective healthcare delivery.