Specific types of socio-technical systems targeted by the SOCIONICAL project are large human groups embedded in Ambient Intelligence (AmI) environments. The project will study how global phenomena emerge in such systems from local interactions on the example of two specific scenarios: transportation and emergency/disaster. A key component of AmI environments is the ability of the system to monitor and model user actions, user state, and the general situation in the environment. Based on such monitoring the system is supposed adjust its configuration to optimally suit the users' needs. It can proactively record/provide relevant information, facilitate communication between different users, and, in many cases, actually try to influence human behaviour. Thus, the system reacts to human behaviour while at the same influencing it. This creates a feedback loop and leads to a tight entanglement between the human and the technical system. In large ensembles of people, in which the digital artefacts can communicate in a dynamic, ad hoc fashion, such entanglement is not limited to individual interactions. Instead it drives global system properties and will likely lead to complex emergent phenomena. Such phenomena can neither be understood nor predicted by looking at the human or the technical system alone. Instead the socio-technical system must be considered as a whole and studied using methods from complex systems science.

From a Complexity Science based investigation AmI based environments are a particularly interesting type of socio-technical systems for two reasons:

• the technical components of the system are not just passive mediators of human interactions (e.g. like the in Internet in social networks) but are active, situation aware participants in the interaction. As described above, in addition to mediating interactions AmI systems directly react to human actions (based on activity monitoring) and attempt to influence human behaviour. This means that the local interactions determining the sought after global behaviour are rich, variable, and highly complex. 
• we expect the socio-technical system to display global, emergent behaviour on a wide range of time scales ranging from a very short dynamic behaviour (panic in a crowd in the emergency scenario) to the development of long term trends and habits (e.g. long term changes in traffic and driving patterns).

The specific scenarios of transportation and emergency/disaster have been picked for their richness of possible interactions, availability of real life data and social and economic relevance. Picking two complex scenarios to be investigated in parallel combined with a multifaceted, parallel approach to modelling (classical analytical models, symmetry techniques, socio physics techniques, and agent based models) is what makes the instrument of an Integrated Project rather than a STREP the appropriate instrument for SOCIONICAL.

As of today the study of human computer interaction in AmI environments has been mostly restricted to the investigation of individual users or small user groups. SOCIONICAL will develop methods and tools for modelling, simulation, and prediction for large scale, complex, AmI environment based socio technical systems. It will focus on going from an understanding of local interactions between humans and the ICT system to describing and predicting the evolution of global properties, self-organization, and large scale emergent phenomena.

SOCIONICAL starts by looking at three types of interactions among individual entities ("in the small"):

• the (possibly ICT enabled) interaction among humans,
• the interaction among humans and digital artefacts (ICT components/services, devices, gadgets, "smart things"...)
• the interaction among digital artefacts themselves (based on self-management capabilities, spontaneous and opportunistic interaction, etc.