A Digital Twin is a virtual model of a process, product or service.
I propose to expand on the emerging Digital Twin capabilities for (example) industrial plant monitoring to create a virtual twin for “anything” that might add increasing value for a User.
A simple example:
- a User has a smart device (phone+) enabled with “basic” features that allow data capture – vibration, acceleration, temperature / thermal imaging etc.
- the User buys a washing machine and is encouraged to enable the “Twin Agent” from AI Marketplace
- over time, the smart device captures relevant data that impacts the User Experience (noise, power consumption…)
- the User is given feedback if and when required about the performance of their washing machine
- the data is shared with the manufacturer.
The above simple example implies much greater, longer term benefits:
- the commercial value of the correlation of mass product data to provide useful information for manufacturers etc.
- how are their products being used / misused in different markets…?
- a link into systems that optimize the product (for example, AI Generative Design)
- the most useful data captured in each context (e.g. vibration via smartphone) suggests product enhancements for IoT etc. in a virtuous cycle
- Machine intelligence (Product onboard AI?) further enhances the twin capability and fidelity
- there is a transition cycle per context:
- from passive (collect operational data)
- to active (analyze and optimize for efficiency, maintenance etc.)
- to proactive (upload new features, fixes and enhancements).