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A Study on Self‐Organizing Map of Indoor Activity Sound for Detecting Abnormal Situation in Daily Life
Author(s) -
Tanaka Motoshi,
Takata Naru
Publication year - 2021
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.23321
Subject(s) - self organizing map , abnormality , microphone , sound (geography) , computer science , broadband , artificial intelligence , telecommunications , psychology , acoustics , cluster analysis , physics , sound pressure , social psychology
In order to develop a detection system of abnormal situations (such as accidents) for a person living alone, SOM (self‐organizing map) of only daily activity sound recorded with a broadband microphone, and detection of abnormal situation are investigated. The SOM was divided into three regions containing 98.9, 1.0, and 0.1% of the number of learned vectors, and transition of the vectors of simulated abnormality sound was observed. The result indicates the feasibility of use of the SOM for detecting abnormal situations. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.