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Digital Twins: where we are where we go – VI

A number of technologies are being used in the creation and operation of Digital Twins, including Cloud, Artificial Intelligence, IoT, Augmented and Virtual Reality, Blockchain. Image credit: Digital List

Technology challenges

A digital twin, as mentioned, is composed of a digital model, a digital shadow and a digital thread. Each of these has its own specific technology challenges associated. In addition, we shouldn’t forget that in the coming years a digital twin is bound to extend its capabilities on one hand (making use of technologies like artificial intelligence) and on the other hand it will become the component of a superorganisms, the symbiosis of the physical and the digital twin. Both bring along technology challenges.

Digital model

Depending on the application area there are different ways to create a digital model and this diversity is not helping the portability of models across different areas and sometimes within the same area. In most cases there are no standards, rather the modelling format is the consequence of the software supporting it (CAD). This is the result of a vertical growth, often driven by big companies imposing their processes and tools. There are areas, like the modelling of a city, where different components (like power infrastructures, the cadastral maps, telecom infrastructures…) are modelled in different, and incompatible ways. This increases the cost in creating interoperable applications spanning several components. It would be desirable to work out a bottom up approach to solve, manage this situation.

Another aspect is that the digital model can also be used by VR and AR applications connecting the digital with the physical part. Here again the existence of some interoperable models would boost the creation of applications.

Digital shadow

The shadowing requires a synchronization between the physical twin and its digital one. This in turns requires the physical twin to provide data mirroring its status at suitable, meaningful intervals, and a communication channel of some sort to transfer these data. Communications is becoming more and more pervasive (and affordable) and various communications paradigms are also becoming available (synchronous – low latency, synchronous with latency, asynchronous, direct, mediated…). There is already a broad spread in “shadowing”, from windmills turbine signalling their status to semi-autonomous cars reporting their status once a day. Depending on where the physical twin operates, different communications infrastructures are used. Robots in a factory plant are most likely to use WiFi type of connectivity, whilst those operating in public space may rely on radio cell networks. At home, a person’s digital twin may use a variety of ambient sensors (including smart mirrors and smart toilets) to harvest that person’s data.

Digital thread

All data received by the digital twin may be stored, keeping track of the evolution of the physical twin. The storing would take place in a cloud, most of the time. However, in the case of a person’s digital twin there are proposal to encapsulate these data in a person’s directly controlled device, like a smartphone. We are just starting and there is no defined architecture for digital thread data storage. Given the amazing progress in data storage medium for the next decade the storing of data does not seem to be critical, in terms of capacity. Privacy, availability and ownership control seem to dominate the discussion and steer solutions. This may change in a longer term. Additionally, as digital twin will move to stage 4 they will start to clone themselves and roam the cyberspace bringing along with them their data, so different architectures may be required. Synchronization of instances will also become a major issue. Blockchain technology may also play a role in providing a certified digital thread.

About Roberto Saracco

Roberto Saracco fell in love with technology and its implications long time ago. His background is in math and computer science. Until April 2017 he led the EIT Digital Italian Node and then was head of the Industrial Doctoral School of EIT Digital up to September 2018. Previously, up to December 2011 he was the Director of the Telecom Italia Future Centre in Venice, looking at the interplay of technology evolution, economics and society. At the turn of the century he led a World Bank-Infodev project to stimulate entrepreneurship in Latin America. He is a senior member of IEEE where he leads the Industry Advisory Board within the Future Directions Committee and co-chairs the Digital Reality Initiative. He teaches a Master course on Technology Forecasting and Market impact at the University of Trento. He has published over 100 papers in journals and magazines and 14 books.