Proposed Model for NEOM City Based on Internet of Things (IoT) and MLC at ED System

Smart cities are continually growing to promise better services and solve traditional urban problems. One of the most notable challenges in current city hospitals is the complex patient workflow process. NEOM is a $500 billion investment that was announced in October 2017 as part of Saudi Arabia's Vision 2030 initiative. It will be located on the Red Sea Coast, and it will use the latest technologies, including artificial intelligence, and the Internet of Things (IoT), to tackle some of the world's toughest healthcare problems. Sensors will collect all the data and create a digital twin, which will lead to personalized medicine where citizens, not hospitals, are at the center of the system and can be supported by the latest medical advances for better treatment. This study proposed a smart model for the emergency department (ED) system to improve the patient's workflow using Machine Learning Control (MLC), IoT, and a simulation tool as discrete-event simulation (DES). The DES was used to collect different data (such as queue length and average waiting time) that could be compared with the information absorbed by the IoT sensors. The ED system improved with a 55% reduction in the expected time patients spend in the system and a 39% increase in the expected number of patients discharged. The methodology applied will enhance not only healthcare management systems but also extend its benefits to other domains, such as workflow optimization in manufacturing, thereby contributing to an overall enhancement of the system's workflow.