Location of a Person by Means of Sensors´ Network

Author

Hnatiuc, M. ; Belconde, A. ; Kratz, F.

Author_Institution

Constanta Maritime Univ., Constanta, Romania

fYear

2010

fDate

15-19 July 2010

Firstpage

18

Lastpage

22

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Technologies for Enhancing Quality of Life (AT-EQUAL), 2010

Conference_Location

Iasi

Print_ISBN

978-1-4244-8842-1

Type

conf

DOI

10.1109/ATEQUAL.2010.11

Filename

5663580