Coffee Twin: An Interactive Digital Twin System Featuring Augmented Reality, Virtual Reality and Voice Interaction

The increasing digitalization of industrial environments has led to the emergence of new paradigms such as Digital Twins (DTs), which enable real-time connections between physical assets and their virtual counterparts. In this context, the Coffee Twin system was developed as a modular and controlled demonstrator to explore, present, and validate the integration of DT technology with Augmented Reality (AR), Virtual Reality (VR), and voice-based interaction. A coffee machine was selected as the case study due to its manageable complexity, low-risk operation, and potential to illustrate concepts that can later be extended to more complex industrial systems. The system architecture is centered on a Raspberry Pi, which supports local data acquisition from temperature and humidity sensors, mechanical actuation through a servo motor, and remote control via a smart switch. To interact with the system, three software applications were developed: a Web application, an AR application for contextual visualization and remote interaction, and a VR application that recreates the operation of the machine within an immersive 3D environment. Beyond the technical implementation, the prototype was evaluated in demonstration and user-testing sessions in which 80 participants, mostly secondary-school pupils and university students, completed a coffee-making task across the three applications and then answered a System Usability Scale (SUS) questionnaire. The analysis of the 80 valid responses yielded a mean SUS score of 69.2 (standard deviation 15.9; 95% confidence interval [65.7, 72.8]), which corresponds to acceptable, slightly above-average usability and indicates that combining real-time sensing, remote actuation, and multimodal interaction in a single low-cost platform is perceived as usable across a heterogeneous, predominantly non-expert audience. The main contribution of this work is therefore not a new Digital Twin algorithm, but an accessible, modular, and reproducible integration of Web, AR, VR, and voice interaction around a physical asset, supported by usability evidence. Overall, Coffee Twin shows how a low-cost and multimodal DT demonstrator can support the communication, experimentation, and early exploration of Industry 4.0 concepts in educational and pre-industrial settings.