Title :
Location of a Person by Means of Sensors´ Network
Author :
Hnatiuc, M. ; Belconde, A. ; Kratz, F.
Author_Institution :
Constanta Maritime Univ., Constanta, Romania
Abstract :
The different algorithm of data classification and clustering to identify the subject on the room is introduced. The aim is to provide a learning approach for pattern classification of presence sensors data. The focus system is on its application to find the best method for identification the subject location using a specific category of data simulated. The main features of the system include: automatic rule generation, automatic ranges generation, learning and adaptability capability. Simulation values concerning a different cluster methods results are presented. The system successfully detected the location in X and Y axes and body temperature. Its response time in identification suggests the feasibility in real-time applications.
Keywords :
electrical engineering computing; learning (artificial intelligence); pattern classification; pattern clustering; temperature sensors; thermopiles; wireless sensor networks; automatic range generation; automatic rule generation; body temperature; data classification algorithm; data clustering algorithm; learning approach; pattern classification; simulation values; subject location identification; thermopile sensor; wireless sensor network; Adaptation model; Clustering algorithms; Fuzzy systems; Humans; Temperature sensors; classification; location; thermopile sensor;
Conference_Titel :
Advanced Technologies for Enhancing Quality of Life (AT-EQUAL), 2010
Conference_Location :
Iasi
Print_ISBN :
978-1-4244-8842-1
DOI :
10.1109/ATEQUAL.2010.11
