Elsevier Company Digital Twins: Emerging Trends, Technologies, and Applications (Advances in Digital Twin Computing and Sensor Networks)

The concept of the digital twin, a virtual representation of a physical system, has gained significant attention due to advancements in Artificial Intelligence, Internet of Things, and data analytics. It plays a crucial role in enhancing efficiency, sustainability, and decision-making across industries, such as manufacturing, healthcare, and urban planning. The timeliness of this topic lies in the rapid digital transformation and the increasing complexity of systems requiring real-time, intelligent management to achieve competitive advantages and sustainability goals. Company Digital Twins explores virtual companies based on digital twin technologies. Digital twin computing not only reduces the gap between a real company and a virtual company, but generates new datasets, making the company digital twin a bridge between the real and virtual company. A company digital twin is also the mirror that reflects the real company into the virtual company. The structure of the book is comprised of 15 chapters that discuss the foundational concepts emerging trends, underlying technologies, practical applications; and future directions, and includes data security and privacy concerns, integration issues, and the scalability of digital twins across large companies. Sitting within the series, Advances in Digital Twin Computing and Sensor Networks, Company Digital Twins is essential reading for anyone who needs to benefit from the capabilities of digital twins within the organization. Discusses how companies use digital twins for real-time decision-making and strategic foresight Covers sectors embracing this technology, including manufacturing, healthcare, smart cities, agriculture, transportation, retail, etc Highlights trends in digital twin applications for improving efficiency, sustainability, and innovation in companies Explores technological components such as Internet of Things, Artificial Intelligence, big data analytics, blockchain, and cloud computing Examines challenges such as data security, integration complexity, and scalability, and offers insights into future developments