Research Article
Zone-Based Living Activity Recognition Scheme Using Markov Logic Networks
@INPROCEEDINGS{10.1007/978-3-319-47063-4_10, author={Asaad Ahmed and Hirohiko Suwa and Keiichi Yasumoto}, title={Zone-Based Living Activity Recognition Scheme Using Markov Logic Networks}, proceedings={Internet of Things. IoT Infrastructures. Second International Summit, IoT 360° 2015, Rome, Italy, October 27-29, 2015. Revised Selected Papers, Part I}, proceedings_a={IOT360}, year={2017}, month={1}, keywords={Daily living activity recognition Markov Logic Networks Smart home Activity zone}, doi={10.1007/978-3-319-47063-4_10} }- Asaad Ahmed
Hirohiko Suwa
Keiichi Yasumoto
Year: 2017
Zone-Based Living Activity Recognition Scheme Using Markov Logic Networks
IOT360
Springer
DOI: 10.1007/978-3-319-47063-4_10
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.