Human – Data Analytics Interaction Through Voice Assistance in Electric Vehicle’s Battery Testing

Voice assistants, alternatively mentioned as conversational agents or Digital Intelligent Assistants (DIA), represent a new form of interaction between humans and machines, providing fast, intuitive, and potentially hands-free access to systems through voice-based interaction in order to increase the efficiency of certain activities. While the literature has mainly focused on general applications of voice assistants in diverse industries, their potential in manufacturing remains mostly underexplored. This is despite the manufacturing sector is a key driver for employment and plays a critical role in economic growth. Furthermore, enabling human workers to interact with data analytics insights through voice interfaces is key to realize a human-system symbiosis in an Industry 5.0 context. However, there is limited literature regarding the data analytics potential integrated into voice assistants and related implementations due to, among others, the challenges of translating analytical results into easy-to-understand information for humans. In this paper, we face these topical issues for DIA by presenting a voice assistant equipped with data analytics functionalities to support human-machine interaction in the manufacturing sector when there are data analytics insights that are communicated to the user. We demonstrate this with a concrete instantiation in Electric Vehicle’s (EV) battery testing use cases.