Human aware superorganisms

Abstract

Massive networks of wearable devices have recently become a key scenario for pattern recognition technologies. Applications range from implicit human-machine interactions, to autonomous monitoring of user habits and activities. This paper presents a framework providing developers with tools to orchestrate the continuous process of collecting and classifying data streams in aware-systems. It supports service oriented, reconfigurable components and provides a solid background to put at joint work specification-and data-driven approaches. It also provides an innovative meta-classification scheme allowing to implement applications by editing a simple state automata. Experimental results suggest that the approach could be integrated in a number of applications for: (i) improving energy efficiency, (ii) improving classification accuracy and (iii) improving software engineering of aware systems.