Title :
Evidence fusion for activity recognition using the Dempster-Shafer theory of evidence
Author :
Liao, Jing ; Bi, Yaxin ; Nugent, Chris
Author_Institution :
Comput. Sci. Res. Inst., Univ. of Ulster, Newtownabbey, UK
Abstract :
This paper explores a sensor fusion method within Smart Homes to be used to monitor human activities in addition to managing uncertainty in sensor based readings. A case study has shown that the Dempster-Shafer theory of evidence can incorporate the uncertainty derived from the sensor errors and the sensor context and infer the activity. The results from this work show that this method can detect a toileting activity within a Smart Home environment with an accuracy of 69.4%.
Keywords :
biomedical engineering; health care; inference mechanisms; intelligent sensors; sensor fusion; uncertainty handling; Dempster-Shafer evidence theory; activity recognition; evidence fusion; human activity monitoring; sensor context; sensor errors; sensor fusion method; smart homes; toileting activity; Bismuth; Computer science; Humans; Intelligent sensors; Mathematics; Monitoring; Neural networks; Sensor fusion; Smart homes; Uncertainty; activity recognition; reasoning under uncertainty; sensor fusion; smart homes;
Conference_Titel :
Information Technology and Applications in Biomedicine, 2009. ITAB 2009. 9th International Conference on
Conference_Location :
Larnaca
Print_ISBN :
978-1-4244-5379-5
Electronic_ISBN :
978-1-4244-5379-5
DOI :
10.1109/ITAB.2009.5394319
