Hospital Emergency Queue Detection Using Inter-Vlan Routing

Abstract

Ultimately, this project aims to contribute to smart healthcare infrastructure in Kigali by providing a scalable, secure, and intelligent system that improves emergency department efficiency and saves lives through faster, more organized care delivery. This study focuses on developing a Hospital Emergency Queue Detection System to streamline patient flow using vlan routing, minimize delays, and enhance healthcare outcomes. Utilizing cutting-edge technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), and data analytics, the system monitors real-time patient queues, predicts wait times, and prioritizes treatment based on urgency. In modern healthcare systems, reducing patient waiting times in emergency departments is critical for enhancing service quality and saving lives. This project proposes a novel approach to Hospital Emergency Queue Detection using VLAN (Virtual Local Area Network) routing to optimize network traffic and accurately monitor patient flow in real time. By segmenting hospital network infrastructure into VLANs dedicated to specific zones—such as triage, diagnostics, treatment, and discharge—data traffic from medical devices, RFID patient tags, and real-time location systems can be efficiently routed and analyzed. This system integrates queue detection algorithms with VLAN-based data segregation to identify bottlenecks and abnormal delays in patient movement. The architecture improves data throughput, reduces latency in communications, and ensures critical patient data is prioritized. The use of VLAN routing allows for scalable and secure monitoring of multiple departments while maintaining performance and privacy. The implementation results in improved emergency department efficiency, quicker decision-making, and enhanced patient experience.