Ambient Intelligent applications involve the deployment of sensors and hardware devices into an intelligent environment surrounding people, meeting users’ requirements and anticipating their needs (Ambi- ent Intelligence-AmI). Biometrics plays a key role in surveillance and security applications. Fingerprint, iris and voice/speech traits can be acquired by contact, contact-less, and at-a-distance sensors embedded in the environment. Biometric traits transmission and delivery is very critical and it needs real-time transmission net- work with guaranteed performance and QoS. Wireless networks become suitable for AmI if they are able to satisfy real-time communication and security system requirements. In this paper an hierarchical network architecture, made up of several independent Wireless Automation Cells grouped in Automation Clusters, is presented. The performance evaluation of the proposed architecture, in terms of authentication accuracy and network scheduling efficiency, is also outlined.

A Real-Time Network Architecture for Biometric Data Delivery in Ambient Intelligence

ANDOLINA, Salvatore;
2013-01-01

Abstract

Ambient Intelligent applications involve the deployment of sensors and hardware devices into an intelligent environment surrounding people, meeting users’ requirements and anticipating their needs (Ambi- ent Intelligence-AmI). Biometrics plays a key role in surveillance and security applications. Fingerprint, iris and voice/speech traits can be acquired by contact, contact-less, and at-a-distance sensors embedded in the environment. Biometric traits transmission and delivery is very critical and it needs real-time transmission net- work with guaranteed performance and QoS. Wireless networks become suitable for AmI if they are able to satisfy real-time communication and security system requirements. In this paper an hierarchical network architecture, made up of several independent Wireless Automation Cells grouped in Automation Clusters, is presented. The performance evaluation of the proposed architecture, in terms of authentication accuracy and network scheduling efficiency, is also outlined.
2013
Ambient Intelligence
Efficient wireless sensor networks
Real-time scheduling
Biometric traits processing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1232728
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