By Alessandra De Paola (auth.), Salvatore Gaglio, Giuseppe Lo Re (eds.)
The identify of this ebook is a pun at the use of the preposition “onto” with the purpose of recalling “Ontology”, the time period ordinarily followed within the desktop technological know-how group to point the learn of the formal specification for organizing knowledge.
In the sphere of data engineering, Ontologies are used for modeling options and relationships on a few domain.
The yr 2013 celebrates the 20 th anniversary of the area vast net. the straightforward community of hypermedia has reworked the area of communications with huge, immense implications at the social relationships. in spite of the fact that, conventional world-wide-web is presently experiencing a hard evolution towards the web of items (IoT), this present day possible due to the mixing 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 goal, ontologies symbolize the main appropriate instrument to permit move and comprehension of data between machine functions, even these designed and built by means of unrelated humans in numerous places.
This publication proposes a set of contributions illustrating various purposes following those instructions and which are the results of genuine reviews constructed within the context of analysis projects.
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Additional resources for Advances onto the Internet of Things: How Ontologies Make the Internet of Things Meaningful
The first can assume the states in and out depending on users presence in the room. Variable OutdoorLight t +1 represents the external light at a subsequent time instant and can be high, medium, or low; it is used to better understand how much the light change in the room at a subsequent instant may be due to the external light status or to an user action. The variables LightTrend t and LightTrend t + 1 represent the evolution of light in two successive time instants, and can assume the states increasing, decreasing and stable.
The activity recognizer was used as constituent part of a profiler able to anticipate user activities and to monitor their daily routines. We also provided a formal representation of the concepts of our domain, describing all the entities going to make up our system. It is worth noting that the module for interacting with the user was not really implemented. This interaction was only simulated. We now intend to develop our user interface further. We are planning to conduct more tests to simulate the contemporary use of the recognizer and profiler, and also want to explore the effects of time granularity variation on the profiler.
The selection of the rules is delegated to a higher level planner whose task is that of finding the best rules for the correct operation of the entire system. A large variety of approaches for fuzzy rule generation is reported in the literature, ranging from the use of neural networks, to clustering techniques, and the use of evolutionary and heuristic search algorithms. The authors of  suggest using neural networks to learn fuzzy rules. A neural network simulates the behavior of the fuzzy rules inside the controller.