SOCIONICAL

People

Martin Wirz

This project is supervised by Dr. Daniel Roggen and Prof. Gerhard Tröster

Complex Socio-Technical Systems in Ambient Intelligence

SOCIONICAL is an Information and Communication Technologies Project funded under European Seventh Framework Programme (FP7), aiming to develop Complexity Science based modelling, prediction and simulation methods for large scale socio-technical systems.

SOCIONICAL focuses on the specific example of Ambient Intelligence (AmI) based smart environments. A key component of such environments is the ability to monitor user actions and to adjust its configuration and functionality accordingly. 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. At the same time there is dynamic, heterogeneous human-human, human-technology, and technology-technology communication leading to ad-hoc coupling between components and different feedback loops. The project will study global properties and emergent phenomena that arise in AmI based socio-technical systems from such local feedback loops and their coupling on two concrete scenarios: transportation and emergency/disaster.

SOCIONICAL takes a parallel, multi facetted research approach. Thus, it will address analytical methods, complex networks based representations, and agent based models. The advances in modelling and prediction will be verified by large scale, distributed simulation driven by real life data.

Our Objective: Decentralized Sensing of Collective Behaviors in Human Groups

We investigate approaches for detecting collective behavior patterns using body-worn sensors in a decentralized, online manner.

Our key research directions include:

• The definition of suitable behavioral building blocks (behavioral primitives) to address scalability from large-scale collective behaviors to lab-sized settings.
• The comparative analysis of suitable technologies for crowd sensing, based on current cellphones technologies as well as next-generation wearable devices.
• Investigation of efficient algorithms for a decentralized interpretation of sensor data into behavioral primitives.
  

Publications

Soon to be added.

Other contributors

Links

SOCIONICAL Official Website