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A System for Recommending Essential Visual Perception Information in Life Monitoring Using Air Pollution Data
Author(s) -
KAJIWARA YUSUKE,
UENO MASAYOSHI,
HASEGAWA TATSUHITO,
NAKAMURA MUNEHIRO,
KIMURA HARUHIKO
Publication year - 2016
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.11822
Subject(s) - identification (biology) , computer science , perception , activities of daily living , air pollution , information system , pollution , data mining , artificial intelligence , real time computing , human–computer interaction , engineering , psychology , chemistry , botany , organic chemistry , neuroscience , psychiatry , electrical engineering , biology , ecology
SUMMARY Life monitoring systems with air pollution data have been developed for solitary elderly people. However, the existing systems obtain unnecessary information that invades their privacy. In addition, since degrees of air pollution change in distinctive ways due to the effect of home environment and airflow conditions, it is difficult for people who have no expert knowledge to identify the activities of their daily living (ADL). To solve the problems above, this paper presents a system to select useful information that is required to identify ADL. Experimental results have shown that the proposed system achieves 77.3% identification accuracy. Besides, compared with the case when 10 users were asked to identify ADL without the proposed system, the identification accuracy has increased by 11.3% with the proposed system.