Ambient intelligence framework for context aware adaptive applications

Despite recent turbulence of the digital economy, the information society continues its progress. Information and communication technologies (ICT) are increasingly entering in all aspects of our life and in all sectors, opening a world of unprecedented scenarios where people interact with electronic devices embedded in environments that are sensitive and responsive to the presence of users. These context-aware environments combine ubiquitous information, communication, with enhanced personalization, natural interaction and intelligence. A critical issue, common in most of applications framed inside domotic systems or ambient intelligence, is the approach to automatically detect context from wearable or environmental sensor systems and to transform such information for achieving personalized and adaptive services. Most of the flexible and robust systems use probabilistic detection algorithms that require extensive libraries of training; in this work we experiment with a prototype framework based on intelligent agents skilled to capture user habits, identify requests, and apply the artefact-mediated activity through hybrid approaches, featuring adaptive fuzzy control strategy and biometric techniques.