A Survey on Digital Twins: Enabling Technologies, Use Cases, Application, Open Issues and More

Abstract

Digital Twins, sophisticated digital replicas of physical entities, have been gaining significant attention, especially after NASA's endorsement, and are poised to revolutionize numerous fields such as medicine and construction. These advanced models offer dynamic, real-time simulations, leveraging enabling technologies like Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), Cloud Computing, and Big Data Analytics to enhance their functionality and applicability. In the medical field, Digital Twins facilitate personalized treatment plans and predictive maintenance of medical equipment by simulating human organs with precision. In construction, they enable efficient building design and urban planning, optimizing resource use and reducing costs through predictive maintenance. Startups are innovatively employing Digital Twins in various sectors, from smart cities—where they optimize traffic flow, energy consumption, and waste management—to industrial machinery, ensuring predictive maintenance and minimizing downtime. This survey delves into the diverse use cases, market potential, and challenges of Digital Twins, such as data security and interoperability, while emphasizing their transformative impact on industries. The future prospects are promising, with continuous advancements in AI, ML, IoT, and Cloud Computing driving further expansion and application of Digital Twin technologies