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This e-book contains a few chapters addressing various elements of task popularity, approximately in 3 major different types of issues. the 1st subject could be occupied with task modeling, illustration and reasoning utilizing mathematical types, wisdom illustration formalisms and AI strategies. the second one subject will pay attention to task attractiveness tools and algorithms. except conventional tools in keeping with information mining and computer studying, we're quite drawn to novel ways, akin to the ontology-based technique, that facilitate facts integration, sharing and automatic/automated processing. within the 3rd subject we intend to hide novel architectures and frameworks for task popularity, that are scalable and acceptable to giant scale dispensed dynamic environments. moreover, this subject also will contain the underpinning technological infrastructure, i.e. instruments and APIs, that helps function/capability sharing and reuse, and quick improvement and deployment of technological recommendations. The fourth class of subject could be devoted to consultant functions of job popularity in clever environments, which deal with the existence cycle of job reputation and their use for novel services of the end-user platforms with finished implementation, prototyping and evaluate. this can contain a variety of program situations, akin to shrewdpermanent houses, clever convention venues and cars.
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Extra resources for Activity Recognition in Pervasive Intelligent Environments
In the kitchen various sensors are attached to objects pertaining to ADLs. For example, contact sensors are attached to the entry door, containers of teabag, sugar, milk, coffee and chocolate, and a cup. The activation of a sensor indicates the occurrence of an action involving the object to which the sensor is attached. The event will be interpreted Activity Recognition: Approaches, Practices and Trends Fig. 3 19 A fragment of the SH context and ADL ontologies and mapped to a corresponding concept or property in the SH ontologies giving specific contextual information.
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