Wireless IoT-Based Patient Monitoring in Operating Rooms: Integrating AI, Machine Learning, Cloud Computing, and Smart Manufacturing for Enhanced Healthcare Efficiency

Abstract

Modern operations rooms are turning more and more towards high-tech systems to enhance patient safety and efficiency in surgical procedures, but the old wired systems are cluttered, slow to set up, and offer no clinical mobility. The paper will introduce an IoT-based wireless OR monitoring system, which will eliminate cable-based-driven devices by using wearables, wireless networks, edge intelligence, and cloud analytics to achieve real-time monitoring with ease. The framework aids in the ongoing data gathering of physiological information, openness with clinical sites, and risk escalation alerting supported by artificial intelligence to enable surgical teams to react faster to physiological alterations. The system saves almost 20% of OR setup time quantitatively through the removal of cabling delays, and real-time streaming and anomaly detection enhance vital tracking and accuracy by more than 95%. Connectivity to 5G and edge computing reduces latency to facilitate quick decision making and cybersecurity, such as encryption and Zero-Trust controls, to secure sensitive medical records. Scalability of cross-department monitoring, postoperative analytics, and digital dashboards that improve situational awareness are ensured by cloud computing. On the whole, this paper has shown that convergence of IoT, AI, cloud, edge computing, and secure communication turns OR monitoring into an active, intelligent, and patient-centered ecosystem that could enhance the efficiency of workflow, clinical cognition, and surgical results.