Modelling Groups of Humans: Towards Crowd Digital Twins

The term Digital Twin (DT) refers to an emerging concept and technology extending the value of physical assets through the services supported by a bidirectional connection with their digital counterparts. Since its very introduction, the DT concept has been applied to empower several kinds of physical assets across multiple domains, including Industry 4.0, infrastructures, autonomous vehicles, e-health, to name a few. The rise of socio-technical systems and cyber-physical-human systems, which feature humans as key system components, has led to the extension of the DT concept to humans themselves, bringing in the notion of "human digital twin", supporting human-system integration. However, in several contexts, humans are not just isolated entities, but rather form groups or crowds. The peculiar dynamics of such groups have to be carefully considered in various scenarios like emergency management or logistics scenarios. Motivated also by recent trends in social Internet of Things and collective computing, in this paper, we propose the notion of a "crowd digital twin", meant to support services considering the crowd and for the crowd itself. Supporting a bidirectional connection with a physical crowd, this notion is shown to present peculiar requirements, opportunities, and challenges, including low-latency synchronisation, environment-driven prediction, actuation, and validation of emergent behaviour.