By Alessandra De Paola (auth.), Salvatore Gaglio, Giuseppe Lo Re (eds.)
The name of this ebook is a pun at the use of the preposition “onto” with the purpose of recalling “Ontology”, the time period normally followed within the machine technological know-how group to point the examine of the formal specification for organizing knowledge.
In the sphere of data engineering, Ontologies are used for modeling thoughts and relationships on a few domain.
The 12 months 2013 celebrates the 20th anniversary of the realm broad net. the easy community of hypermedia has remodeled the realm of communications with huge, immense implications at the social relationships. notwithstanding, conventional world-wide-web is at present experiencing a not easy evolution towards the net of items (IoT), this day possible due to the combination of pervasive applied sciences able to sensing the environment.
The most vital contribution of IoT regards the potential of allowing extra effective machine-to-machine cooperation. To such objective, ontologies symbolize the main compatible device to permit move and comprehension of knowledge between laptop purposes, even these designed and constructed by means of unrelated humans in several places.
This publication proposes a suite of contributions illustrating various functions following those instructions and which are the results of genuine reviews constructed within the context of analysis projects.
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2, Issue number 2, May (2008) 6. : Sensor-based occupancy behavioral pattern recognition for energy and comfort management in intelligent buildings. In: Proceedings of Building Simulation ’2009, an IBPSA Conference. K. (2009) 7. : Saving, home energy, through a user profiling system based on wireless sensors. In: ACM Buildsys, : (in conjunction with SenSys 2009), Berkeley, CA. Nov. 3, (2009) 8. : A fuzzy embedded agent-based approach for realizing ambient intelligence in intelligent inhabited environments.
For this reason, HMMs have been successfully employed in activity recognition applications. We focus on activity recognition, because it represents an important functionality in designing an AmI system capable of reacting to context switches. We also design a profiler to predict future user actions in order to allow the system to respond according to the user’s requirements. The remainder of the chapter is organized as follows. Section 2 discusses related research, while Sect. 3 describes the design and implementation of our system, including the formal definition of the concepts of the domain under consideration.
We therefore compute a correlation matrix C(nv × nv) in order to highlight the relationships among the variables, where the i, j-th element of C is given by the correlation coefficient ci j between the i-th and the j-th variable, as given by: ci j = Corr (Xi , X j ) = σi j σi σ j 26 A. Augello and S. Gaglio In the previous formula, σi j represents the covariance between Xi and X j and σi and σ j respectively the standard deviation of Xi and X j . In this way it is possible extract sub-matrices, representing correlation patterns between the observations related to the presence of users in office rooms and values representative of specific environment variables.
