Implementing Digital Twins with IoT Capabilities

What is a digital twin?

A digital twin is the digital proxy of a physical asset or device that can help you successfully deploy and use an IoT application. Digital twin technology is often referred to as device virtualization,. There are several ways to implement the Digital Twin. On an IoT platform, a digital twin is a virtual representation of a physical asset, such as; a machine, a vehicle, or a device. It digitally represents the data, processes, states, and lifecycle of that asset. 

Implementing IoT with digital twin capabilities in a building, retail, workspace, machine plant, etc. enables some of the following benefits:

  •  Enhanced visibility: Continuously view the operations of the machines or devices, and the status of their systems
  • Accurate predictions: Retrieve the machine’s future state from the digital twin model via modeling
  • What-if analysis: Interact with the model to simulate unique machine conditions, and perform what-if analysis
  • Documentation and communication:  Use the digital twin model to understand and explain the behavior of one or a collection of machines.
  • Integration of disparate systems: Connect with back-end applications, such as manufacturing, procurement, warehousing, transportation, or logistics.

Pure Data Digital Twin (PDDT)

Describing the behavior of ‘things’ is always a matter of data. When it comes to data, the Digital Twin defines the following: 

  • Current operating condition of the ‘thing,’ ie. asset, space, building, etc. by tracking meaningful parameters that describe its behavior.
  • Meaningful Events occurring during the operation of the ‘thing,’ ie. a room that becomes occupied at a certain moment in time, or climatic conditions in spaces that at any moment underperform based on quality standards. Events are typically bound to time in that, the minute they emerge, they typically require a reaction.

As the system tracks this type of data over time, the historic behavior gets recorded, which is a valuable source for analytics and machine learning. As the ‘Parameters’ provide real-time information on behavior, the ‘Events’ provide the mechanism to connect the behavioral pattern to processes that will enable the necessary business responses to the ‘Events.’

By adding the IoT-performance attributes to an existing set of attributes, we can connect the current operating condition of an object to the object itself. For example, am area of space could be extended with a ‘Occupation’ attribute, defining the current room occupation status as occupied or empty.

With the maturity of IoT Platforms, such as Axonize,  it’s now possible to provide a systematic response to events as well, where interactions take place with Building Management Systems operating in the building. For instance, when an Event occurs indicating that CO2 levels exceed an acceptable boundary, the airflow in that space could be increased.

Defining & Implementing Pure Data Digital Twins

The requirements posed upon the Digital Twin define, in essence, the Parameters and Events it should provide.

  1. Using the PDDT specifications define a standard ‘template’ for the PDDT,  per asset-type, ie. spaces, floors, pumps, escalators, elevators, ventilators, HVAC, etc. as standard PDDT setup is defined, so it can be associated to the set of assets of that type.
    The template defines the Parameters next to the Events that need to be produced. Defining the PDDT is done on the Axonize IoT platform, using no-code  principles. 
  2. Select the actual sensors or connected devices to deploy and connect to the PDDT. As in the example of the space related PDDT, the selection of room sensor devices to apply will be different when requiring information on climatic conditions next to occupation.

We support devices certified on Microsoft Azure IoT by default, as supported though our technology partner network.

Contact us to learn more about our IoT implementation with Digital Twins.

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