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Modern wearable devices provide new opportunities for the development of knowledge artifacts and decision support systems. In this paper we present a recent development of KAFKA, a knowledge engineering methodology based on knowledge artifact notion, that make it able to manage real-time data detected and analyzed by means of Inertial Measurement Units sensors, mounted on Android wearables. This improvement makes KAFKA suitable to deal with many domains where real-time data are necessary, in particular the health-care and rehabilitation ones.

Seniors are the fastest growing segment of populations not only in many parts of Europe, but also in Japan and the United States. ICT technologies are not very popular among many elderly and also are not designed around their cultural necessities and ergonomic needs. The risk is that in the very near future this growing segment will be digitally isolated, in a society that is more and more based on ICT as infrastructure for service, and communications. Easy Reach Project proposes an ergonomic application to break social isolation through social interaction to help the elderly to overcome barrier of the digital divide. This paper focuses its attention on the development of the technology and algorithms used as Human Computer Interface of the Easy Reach Project, that exploits inertial sensors to detect gestures. Many experimental algorithms for gesture recognition have been developed using inertial sensors in conjunction with other sensors or devices, or by themselves, but they have not been thoroughly tested in real situations, they are not devoted to adapt to the elderly and their way of executing gestures. The elderly are not used to modern interfaces and devices, and --- due to aging --- they can face problems in executing even very simple gestures. Our algorithm based on Pearson index and Hamming distance for gestures recognition has been tested both with young and elderly, and was shown to be resilient to changes in velocity and individual differences, still maintaining great accuracy of recognition 97.4% in user independent mode; 98.79% in user dependent mode. The algorithm has been adopted by the Easy Reach consortium 2009-2013 to pilot the human machine gesture-based interface.

This paper presents the EasyReach system, a tool that aims at getting the elderly and pre-digital divide population closer to new technologies by creating a simplified social enviroment that facilitates interaction, trying to allow them to (i) easily keep in contact with friends and relatives, (ii) share their lifetime expertise, and (iii) avoid isolation. The EasyReach tool creates for the elderly a special social TV channel accessed by means of their own TV set and a specialized remote control endowed with gesture recognition, video and audio capture capabilities. A hidden personal assistant reasons on user preferences in the background allowing better focalization on his/her social interests. © 2013 Springer-Verlag.

The high number of accidents in living areas, work environments, and ambient, in general, can benefit of prevention mechanisms able to identify the causes and the indications which precede accidents, and to put in place strategies to avoid risks whenever this is possible. To this aim, this paper presents a risk management architecture for monitoring movements within a smart ambient and managing possible risks. In particular, we present a methodology for movement analysis aimed at detecting and preventing risks. Results from experimentations are discussed.

We present a solution for social adaptive e-learning. In particular we want to individuate candidates acting as peer help in an e-learning academic course. Starting from a previous work in which adaptive learning functionalities were added to a traditional Learning Management System (LMS) [1], we found an interesting application of filtering techniques working together with fuzzy ontologies to individuate peer help, a fundamental step in constructing a true social environment in e-learning communities [2]. This way it is possible to use all the activities and functionalities offered by LMS improving their effectiveness with technologies based on socio-constructivism learning theory, such as: adaptive presentation, collaborative filtering, supporting peer help and peer tutoring.