Technologies for Ambient intelligence: from Smart Objects to Sensor Networks

Milosevic, Bojan (2013) Technologies for Ambient intelligence: from Smart Objects to Sensor Networks, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Ingegneria elettronica, informatica e delle telecomunicazioni, 25 Ciclo. DOI 10.6092/unibo/amsdottorato/5838.
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Abstract

n the last few years, the vision of our connected and intelligent information society has evolved to embrace novel technological and research trends. The diffusion of ubiquitous mobile connectivity and advanced handheld portable devices, amplified the importance of the Internet as the communication backbone for the fruition of services and data. The diffusion of mobile and pervasive computing devices, featuring advanced sensing technologies and processing capabilities, triggered the adoption of innovative interaction paradigms: touch responsive surfaces, tangible interfaces and gesture or voice recognition are finally entering our homes and workplaces. We are experiencing the proliferation of smart objects and sensor networks, embedded in our daily living and interconnected through the Internet. This ubiquitous network of always available interconnected devices is enabling new applications and services, ranging from enhancements to home and office environments, to remote healthcare assistance and the birth of a smart environment. This work will present some evolutions in the hardware and software development of embedded systems and sensor networks. Different hardware solutions will be introduced, ranging from smart objects for interaction to advanced inertial sensor nodes for motion tracking, focusing on system-level design. They will be accompanied by the study of innovative data processing algorithms developed and optimized to run on-board of the embedded devices. Gesture recognition, orientation estimation and data reconstruction techniques for sensor networks will be introduced and implemented, with the goal to maximize the tradeoff between performance and energy efficiency. Experimental results will provide an evaluation of the accuracy of the presented methods and validate the efficiency of the proposed embedded systems.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Milosevic, Bojan
Supervisore
Dottorato di ricerca
Scuola di dottorato
Scienze e ingegneria dell'informazione
Ciclo
25
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Ambient Intelligence, Wireless Sensor Network, Smart Objects, Gestre Recognition, Body Sensor Network
URN:NBN
DOI
10.6092/unibo/amsdottorato/5838
Data di discussione
23 Maggio 2013
URI

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