Driving Digital Twin adoption with LC/NC App development for IoT

In the age of a new normal, remote monitoring and control have become a necessity across the enterprise. The prominence of IoT extends beyond its traditional purpose of sense and integration, evolving to complete end-to-end Enterprise Digital applications that represent physical assets, processes, and environment as a replica in a virtual representation.

There is an exciting convergence of the physical and digital world, generating a solution concept called digital twins that consist of mixed reality and autonomous systems, coming together with other technologies to enable breakthrough innovations in the world of remote asset, process and environment monitoring.

A digital twin is a virtual model of a physical environment that can be buildings, energy distribution grids, warehouses factories… anything that's important to you.

The first thing you do once it's modelled is to bring that digital twin alive and synchronize it. When you synchronize it with the physical world, you're able to start applying software techniques to that model. One of the first things you can do is monitor this physical environment through the digital counterpart, as it provides operational insights into exactly what's happening at any given time in these environments.

The next thing that can be done is tracking its past. Once you've tracked its past, then start taking advantage of analytics to find insights into that history which unlocks something incredibly powerful which is the ability to predict. You can start to predict future states, for example, knowing in advance when equipment will need servicing or predicting occupancy needs before they happen.

Running a simulation enables you to make copies of the digital twin that are effectively the operational visibility of that physical environment and use them to find optimizations that are too complex and cannot be defined by monitoring the physical environment alone. You can do all that with the software copy of the digital twin, and then once the simulation is complete, then you can apply the insights gained on the copy of that digital twin back to the real digital twin and affect inputs into the physical environment. This enables you to start providing autonomous control and automate routines and mundane tasks. Over time, the physical environment becomes optimized because of these simulations and learnings.

Digital twins also enable interactions with digital replicas overlaid onto the physical environment. Obtaining rich metadata and insights about anything you're doing in the physical world from this digital copy enables the possibility to interact in a pure virtual space over distances and with colleagues. 

To build such applications that represent the digital version of a process, asset and environment, we need strong dynamic capabilities as the application will have to be modified constantly by learning through the data and accepting feedback from the physical version.