Interacting with a Digital Twin using Amazon Alexa

Abstract The Digital Twin is an evolving concept with many facets and applications in, for instance, engineering simulation, system control, and product-centric information management. This article focuses on the latter where literature uses the Product Avatar concept to refer to a product’s digital counterpart. Such an avatar used to have one or more graphical interfaces to support user interactions with information about a product item. Over the last few years, voice user interfaces became more mature, and companies, such as Amazon and Google, used them to create digital assistants that support their users during tasks or by taking them over directly. This paper focuses on the hypothesis that a company could use a voice-enabled digital assistant to interact with item-level information. Our study used product tracking and tracing, and quality control in the production as a realistic application case. The design of the assistant bases on the information needs outlined in the Electronic Product Code Information Services (EPCIS) standard. We implemented this design in a small-scale demonstrator on an Echo Show 5 smart speaker with an integrated touch display and an embedded Amazon Alexa assistant. This paper concludes that significant technological barriers, such as low transcription accuracy for object identifier information and the handling of factory noise, remain. A significant non-technological barrier is the mistrust regarding the closed voice assistant technologies from companies, such as Amazon and Google. An approach to address the latter barrier is to use open technologies, such as the privacy-focused assistant Mycroft or Mozilla’s transcription solution DeepSpeech. Further research and experiments with these technologies are useful to identify how they can support the interaction with Digital Twins.