Abstract
In this paper, we propose a zone-based living activity recognition method. The proposed method introduces a new concept called activity zone which represents the location and the area of an activity that can be done by a user. By using this activity zone concept, the proposed scheme uses Markov Logic Network (MLN) which integrates a common sense knowledge (i.e. area of each activity) with a probabilistic model. The proposed scheme can utilize only a positioning sensor attached to a resident with/without power meters attached to appliances of a smart environment. We target 10 different living activities which cover most of our daily lives at a smart environment and construct activity recognition models. Through experiments using sensor data collected by four participants in our smart home, the proposed scheme achieved average F-measure of recognizing 10 target activities starting from 84.14% to 94.53% by using only positioning sensor data.