Digital Twins

What is a Digital Twin

A Digital Twin is a virtual representation of a physical object, system, or process that spans its lifecycle, is updated from real-time data, and uses simulation, machine learning, and reasoning to help decision-making. Digital Twins are used to optimise operations, predict outcomes, and improve performance by providing insights that are not possible with physical models alone. They are widely used in various industries, including manufacturing, healthcare, and smart cities, to enhance efficiency and innovation.

How do Digital Twins work

Digital Twins are created by combining data from various sources, such as sensors, IoT devices, and historical records, to build a model that represents the physical object or system. This model is then updated with real-time data to reflect the current state of the object or system. By using simulation, machine learning, and reasoning, Digital Twins can predict future outcomes, identify potential issues, and recommend actions to improve performance.

How esthesis CORE supports Digital Twins

esthesis CORE automatically maintains Digital Twins for all connected devices. Using a well-documented REST API, you can access the Digital Twin of any device and retrieve its current state, latest data, as well as send commands and query for replies:

The location of the REST API can be found in your esthesis CORE installation under the About section.