Analysis and Design of an Object Tracking Service for Intelligent Environments

Authors:
Ignacio Recio;José M. Moya;Álvaro Araujo;Juan Carlos Vallejo;Pedro Malagón
Affiliations:
Dpto. Ingeniería Electrónica, ETSI de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain 28040;Dpto. Ingeniería Electrónica, ETSI de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain 28040;Dpto. Ingeniería Electrónica, ETSI de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain 28040;Dpto. Ingeniería Electrónica, ETSI de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain 28040;Dpto. Ingeniería Electrónica, ETSI de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain 28040
Venue:
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Year:
2009

Citing 1
Cited 0

A Bayesian Sampling Approach to In-Door Localization of Wireless Devices Using Received Signal Strength Indication

PERCOM '05 Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications

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Abstract

This paper describes the design and implementation of an object tracking service for indoor environments. First, the wireless indoor location estimation technology is overviewed presenting advantages and disadvantages. Second, the methodology of the study is presented. To estimate the position we use clues inserted by location clue injectors of the system. In our architecture one of these injectors is a ZigBee sensor network. As location algorithm we have developed a method combining statistical techniques (particle filter) and proximity sensing (nearest neighbour) to get better efficiency. The results obtained show that a good precision and reliability can be achieved with a low-cost solution.