Digital Twins: A glossary of common terms used in Digital twin

PropVR ...
Jan 11, 2023  . 4 min read

Digital Twin

A digital twin is a virtual representation of a real asset or system that can be used for study, simulation, and performance monitoring.

Digital Twin
Digital Twin

Internet of Things (IoT)

Internet of Things (IoT): A network of linked sensors, gateways, and devices that may gather and send data from a system or physical asset. The Internet of Things is essential to digital twin technology.


Devices that measure various attributes of the physical twin, such as temperature, position, and velocity. The data collected by sensors is used to create and update the digital twin.

Building Information Modelling (BIM)

A method of creating a digital representation of a building's physical and functional characteristics, that can be used to improve the building's design, construction, and operation.

Building Automation System (BAS)

The use of digital technologies to automatically control and monitor the building's HVAC, lighting, security, and other systems, which can be integrated with the digital twin to optimize the building's performance.

Virtual Commissioning

Before a physical asset is developed or deployed, the commissioning of a system or asset can be simulated using a digital twin. This process is known as virtual commissioning.

Remote Monitoring

The capability to track a physical asset's or system's performance in real-time using information from sensors and other linked devices.

Predictive Maintenance

In order to arrange maintenance before a problem happens, predictive maintenance uses data and analysis from a digital twin to forecast when a physical asset or system will need maintenance.

Asset Performance Management (APM)

The practice of tracking, evaluating, and improving the performance of physical assets or systems utilising information from digital twins and other sources.

Real-Time Data

Real-time data: Information that may be utilised to update the digital twin in real-time and is gathered and communicated from the physical asset or system in real-time.

Machine Learning

A branch of artificial intelligence that enables systems to learn from data, improve with practice and carry out tasks without explicit instructions. Digital twin technology can be combined with machine learning to enable advanced features like predictive maintenance.

Machine Learning is an important aspect of Digital Twin
Machine Learning is an important aspect of Digital Twin

Data Analytics

The collection and analysis of data from digital twins are used to improve physical twin performance and make data-driven decisions.

Cloud Computing

The practice of storing and processing data on remote servers that can be accessed over the internet. Cloud computing is often used for digital twin technology as it enables remote access and scalability.

Data Fusion

The process of combining data from multiple sources and sensors to provide a more complete and accurate representation of the physical asset or system.

Asset Digital Twin

A digital representation of a particular physical asset that offers capabilities for research, simulation, and monitoring.

Process Digital Twin

A digital twin that simulates, controls, and can be used to optimise a particular system or process.

Digital Thread

An approach that strives to incorporate digital twin technology into every stage of the creation and use of an asset or system, from design and development to deployment, use, and maintenance, and finally replacement or retirement.

Digital Twin Platform

A collection of technologies and services that are used to create, manage and analyze digital twins. A digital twin platform typically includes a simulation engine, a data management system, and a user interface

Digital Twin Platform
Digital Twin Platform


A form of a digital twin that is created after the physical twin has been built. It helps in monitoring, analyzing, and optimizing the physical twin.


A form of a digital twin that is created before the physical twin is built. It can be used to simulate, verify and optimize the design, before the physical system is built, resulting in potential savings of cost and time.


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