Digital twins are digital representations of physical assets, systems, people, or processes. They help detect, prevent, predict, and optimize the physical environment using artificial intelligence (AI), real-time analytics, visualization, and simulation tools. Conceptually, digital twins have been around for decades; a forerunner was used in NASA’s Apollo 13 mission to the moon in 1970. While far from ubiquitous today, adoption is increasing across industries, although challenges around security and interoperability still need to be addressed.
The publisher forecasts that the global digital twins market will reach $154.3 billion by 2030, driven by advances in underlying technologies such as the Internet of Things (IoT), cloud, AI, and data analytics. The number of use cases for digital twins is increasing and includes remote asset monitoring, 3D design, and modeling of the effects of drugs on human patients.
Interoperability remains a key concern for digital twins. For widespread adoption of digital twins, it is important to ensure they can communicate effectively with each other. This requires standardizing data formats, communication protocols, and interfaces for seamless integration across different platforms, software, and hardware. Efforts are underway to address these challenges; however, achieving full interoperability requires collaboration among industry stakeholders, technology providers, and standardization bodies.
The publisher forecasts that the global digital twins market will reach $154.3 billion by 2030, driven by advances in underlying technologies such as the Internet of Things (IoT), cloud, AI, and data analytics. The number of use cases for digital twins is increasing and includes remote asset monitoring, 3D design, and modeling of the effects of drugs on human patients.
Interoperability remains a key concern for digital twins. For widespread adoption of digital twins, it is important to ensure they can communicate effectively with each other. This requires standardizing data formats, communication protocols, and interfaces for seamless integration across different platforms, software, and hardware. Efforts are underway to address these challenges; however, achieving full interoperability requires collaboration among industry stakeholders, technology providers, and standardization bodies.
Scope
- This report provides an overview of the digital twins theme.
- It identifies the key trends impacting growth of the theme over the next 12 to 24 months, split into three categories: technology trends, macroeconomic trends, and regulatory trends.
- It includes a comprehensive industry analysis, including use cases for digital twins across various industries, including manufacturing, power, oil and gas, healthcare, construction, automotive, aerospace and defense, government, and sports.
- The detailed value chain comprises six layers: a physical layer, a connectivity layer, a data layer, a platform layer, a delivery layer, and a services layer.
Reasons to Buy
- The range of potential use cases for digital twins is extensive. They range from design and architecture to engineering, smart cities, aerospace and defense, power, oil and gas, and, probably the most advanced, a digital twin of the human body. This report tells you everything you need to know about digital twins, including identifying the current leaders in some of the most important segments of the digital twins value chain.
Table of Contents
- Executive Summary
- Players
- Technology Briefing
- Trends
- Industry Analysis
- Signals
- Value Chain
- Companies
- Sector Scorecards
- Glossary
- Further Reading
- Thematic Research Methodology