Automated Space Classification for Network Robots in Ubiquitous Environments. (16th August 2015)

• Record Type: Journal Article
• Authors: Choi, Jiwon; Cho, Seoungjae; Chu, Phuong; Vu, Hoang; Um, Kyhyun; Cho, Kyungeun
• Other Names: Chao Han-Chieh Academic Editor.
• Is Part Of: Journal of sensors. Volume 2015(2015)
• Publication Date: 2015-08-16
• Subjects: Detectors -- Periodicals; 681.205
• DOI: 10.1155/2015/954920
• Languages: English
• ISSNs: 1687-725X

Abstract

Abstract : Network robots provide services to users in smart spaces while being connected to ubiquitous instruments through wireless networks in ubiquitous environments. For more effective behavior planning of network robots, it is necessary to reduce the state space by recognizing a smart space as a set of spaces. This paper proposes a space classification algorithm based on automatic graph generation and naive Bayes classification. The proposed algorithm first filters spaces in order of priority using automatically generated graphs, thereby minimizing the number of tasks that need to be predefined by a human. The filtered spaces then induce the final space classification result using naive Bayes space classification. The results of experiments conducted using virtual agents in virtual environments indicate that the performance of the proposed algorithm is better than that of conventional naive Bayes space classification.