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Sensors 2015, 15(11), 29056-29078; doi:10.3390/s151129056

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors

Centre of Industrial Electronics (CEI), Technical University of Madrid; Jose Gutierrez Abascal, 6, 28006 Madrid, Spain
These authors contributed equally to this work.
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Author to whom correspondence should be addressed.
Academic Editor: Felipe Jimenez
Received: 30 September 2015 / Revised: 2 November 2015 / Accepted: 5 November 2015 / Published: 17 November 2015
(This article belongs to the Special Issue Sensors in New Road Vehicles)

Abstract

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc. View Full-Text
Keywords: embedded intelligence; sensors; cooperative sensor networks; object identification; self-learning embedded intelligence; sensors; cooperative sensor networks; object identification; self-learning
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Villaverde, M.; Perez, D.; Moreno, F. Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors. Sensors 2015, 15, 29056-29078.

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