Many real-world applications that focus on addressing needs of a human, require
information about the activities being performed by the human in real-time. While advances
in pervasive computing have led to the development of wireless and non-intrusive sensors
that can capture the necessary activity information, current activity recognition approaches
have so far experimented on either a scripted or pre-segmented sequence of sensor events
related to activities. In this paper we propose and evaluate a sliding window based …