title: Using the Dempster-Shafer theory of evidence with a revised lattice structure for activity recognition.
abstract: This paper explores a sensor fusion method applied within smart homes used for the purposes of monitoring human activities in addition to managing uncertainty in sensor-based readings. A three-layer lattice structure has been proposed, which can be used to combine the mass functions derived from sensors along with sensor context. The proposed model can be used to infer activities. Following evaluation of the proposed methodology it has been demonstrated that the Dempster-Shafer theory of evidence can incorporate the uncertainty derived from the sensor errors and the sensor context and subsequently infer the activity using the proposed lattice structure. The results from this study show that this method can detect a toileting activity within a smart home environment with an accuracy of 88.2%.
authors.affiliation: Computer Science Research Institute, School of Computing and Mathematics, University of Ulster, Jordanstown, UK. liao-j1@email.ulster.ac.uk
authors.forename: Jing
authors.initials: J
authors.lastname: Liao
authors.forename: Yaxin
authors.initials: Y
authors.lastname: Bi
authors.forename: Chris
authors.initials: C
authors.lastname: Nugent
mesh_terms: D000203:Activities of Daily Living / Q000145:classification*; D000465:Algorithms; D003195:Computer Communication Networks; D006699:Home Care Services; D006801:Humans; D008962:Models, Theoretical; D018670:Monitoring, Ambulatory / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D014038:Toilet Facilities