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.
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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Ahmed, A., Suwa, H., Yasumoto, K. (2016). Zone-Based Living Activity Recognition Scheme Using Markov Logic Networks. In: Mandler, B., et al. Internet of Things. IoT Infrastructures. IoT360 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 169. Springer, Cham. https://doi.org/10.1007/978-3-319-47063-4_10
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DOI: https://doi.org/10.1007/978-3-319-47063-4_10
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