Nader Kesserwan

Healthcare systems are complex systems that need effective and efficient operations, optimizations, management, and control to offer reliable, high-quality, and cost-effective healthcare services. There are different approaches to improve the management of healthcare systems including utilizing the healthcare systems engineering principles. Healthcare systems engineering views a healthcare organization as a system and applies the engineering analysis and design principles to improve different aspects of healthcare services provided in that system. While this approach can provide many advantages for healthcare organizations, there are also many challenges hindering the ability of healthcare systems engineers from effectively accomplishing their mission. The initiation of the digital twin technology formed several potential methods for various industrial sectors to enhance their operations. Accordingly, they can help improve productivity, cost-effectiveness, reliability, quality, and flexibility. This paper studies how digital twins can be utilized for improving healthcare systems engineering processes and outcomes to enhance different aspects of healthcare systems. The paper discusses some of the challenges of healthcare systems engineering and how these challenges can be relaxed by utilizing digital twins. The paper also develops a conceptual framework to utilize digital twins for improving healthcare systems engineering processes and outcomes and discusses the prospects of such utilization on achieving the goals of healthcare systems engineering. In addition, the paper provides some discussions on the impact of this utilization and the future research and development projections of the employment of digital twins for healthcare systems engineering.

Smart cities rely heavily on collecting and using data. Smart systems are implemented and deployed to provide intelligent features that help improve efficiency and quality of life. This creates a huge repository of data representing many aspects of smart city operations. Many data-driven applications can take advantage of this data to further improve the “smartness” of a smart city. At the same time, smart city systems, being very large-scale distributed systems and highly integrated with the physical infrastructure and residents of the city, pose immense security challenges as well. So why don’t we take advantage of this data to improve security measures? In this paper we propose the use of data-driven security approaches to secure smart city systems. To illustrate the significance of this approach we first identify the different challenges for securing smart city systems given the unique characteristics of these systems. Then we discuss the benefits of using data-driven security. Furthermore, we categorize the different types of security applications (features) needed to help capitalize on the data needs and benefits. We also discuss the how these categories of applications can alleviate some of the challenges. In addition, we highlight possible future research directions to incorporate effective data-driven security in smart city systems.