Last Thursday I was on a call with fellows co-authors working on a Digital Twins book to be published end of 2021. The topic debated by these “experts” was: what is the correct definition for Digital Twin. The discussion that raged for over an hour just demonstrated the old adage that
there is no problem so simple that could not be mede impossibly complex provided a sufficient number of people are involved to discuss it
The best definition that I heard, at least for me, was that a Digital Twin is a “Digital” “Twin”!
However, the discussion clearly pointed out the growing latitude of the Digital Twin concept, as they arre being used in more and more fields in many different ways. This different fields of application and the diverse ways of (and reason for) using them twist them so that they can fit the specific need.
As a matter of fact, how could you expect the same definition of Digital Twin to apply to something as (potentially) small as an IoT in the same way it can apply to a city (like Singapore) or a continent. Indeed, the EU has launched the initiative Destination Earth that aims at creating a Digital Twin for Europe – a digital version of Europe. As shown in the graphic the idea is to leverage on the variety of data representing various aspects of Europe – digital model(s), consolidating them all into a data lake that is continually updated to mirror the status of “Europe” – digital shadow, keep track of changes – digital thread.
If you feel just a continent is a little thing consider the recent WEF article proposing the creation of a Digital Twin to mirror the whole planet climate. I guess it can’t get much bigger than that (although the universe is way way bigger, but there may be lesser motivation for creating its digital twin – for that a digital model is sufficient).
This Planet Digital Twin will be embedded with AI -reinforced learning- acting as a planet simulator operating in real time, receiving data from the planet wide network of climate sensors (including the millions used for weather forecast).
Notice that we have had for several years now digital models of many “things”. What is happening is the increasing capability to connect these models to the physical reality, in quasi real time, and the availability of software (AI) that can finely tune these models based on the data gathered from the field. We no longer have static models, rather we have digital twins. More than that: we can “use” these digital twins performing in the cyberspace actions that were required in the physical space and only at the very end pass on requests to the physical twin to execute some actions in the physical space.