Ontological framework of context-aware and reasoning middleware for smart homes with health and social services

Evchina, Yulia; Dvoryanchikova, A.; Lastra, José L. Martínez

doi:10.1109/icsmc.2012.6377857

Cited by 17 publications

(14 citation statements)

References 18 publications

(23 reference statements)

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“…Thus, the context model management in emergency scenarios should be considered for ensuring the provision of the right information at the right time and place. As it was pointed in Evchina et al (2012), ontologies play a crucial role in context-aware systems.…”

Section: Co-semiwa: a Semantic Middleware For Emergency Responsementioning

confidence: 99%

Coordinating emergency response by competent teams

Hasse¹,

Gauthier²,

Rolt³

et al. 2018

IJCSIS

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ICTs and social networks can contribute to the emergence of creating competent teams for emergency response. For example, during disasters such as Pakistan flood of 2010, Japan tsunami of 2011 and Thailand flood of 2011, On-Line Social Networks (OSNs) have served as a main technology for numerous people seeking to share information about their personal status, to request resources, or to report the status of their community. They can be used at least for three main functions: detecting emergencies, disseminating information, and managing emergencies. On the other hand, the combination of Internet and mobile technology generated smart devices with associated sensor technologies that are becoming crucial parts in delivering supports during disaster and emergency situation. However, such use of mobile devices usually requires a reliable support system from crowdsensing technologies and back-end intelligent systems. In this way, the mobile crowdsensing must be designed with focus on mechanisms to identify and localize survivors and first responders in an incident zone, as well as mechanisms for competence characterization provided by social networks to facilitate coordination for individuals as well as crowds. These main technologies, the crowdsensing and social networks combined with semantic web and ontologies can provide a complete emergency response system that is the purpose of the CO-SEMIWA platform. This platform permits an interaction among participants to create dynamically competent teams where all participants perform tasks and solve problems in a specific emergency context and situation.

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Section: Co-semiwa: a Semantic Middleware For Emergency Responsementioning

confidence: 99%

Coordinating emergency response by competent teams

Hasse¹,

Gauthier²,

Rolt³

et al. 2018

IJCSIS

View full text Add to dashboard Cite

show abstract

“…Some ontology-based solutions, concerned with the semantic representation of context and personalized service search and retrieval techniques, are described in [11,12]. There are also approaches to extend existing standards by adding/using context, such as KNX ISO [13].…”

Section: State Of the Artmentioning

confidence: 99%

Holistic Context-Sensitivity for Run-Time Optimization of Flexible Manufacturing Systems

Scholze

Barata

Stokić

2017

Sensors

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Highly flexible manufacturing systems require continuous run-time (self-) optimization of processes with respect to diverse parameters, e.g., efficiency, availability, energy consumption etc. A promising approach for achieving (self-) optimization in manufacturing systems is the usage of the context sensitivity approach based on data streaming from high amount of sensors and other data sources. Cyber-physical systems play an important role as sources of information to achieve context sensitivity. Cyber-physical systems can be seen as complex intelligent sensors providing data needed to identify the current context under which the manufacturing system is operating. In this paper, it is demonstrated how context sensitivity can be used to realize a holistic solution for (self-) optimization of discrete flexible manufacturing systems, by making use of cyber-physical systems integrated in manufacturing systems/processes. A generic approach for context sensitivity, based on self-learning algorithms, is proposed aiming at a various manufacturing systems. The new solution encompasses run-time context extractor and optimizer. Based on the self-learning module both context extraction and optimizer are continuously learning and improving their performance. The solution is following Service Oriented Architecture principles. The generic solution is developed and then applied to two very different manufacturing processes.

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“…For example, Evchina et al [9] apply domain ontologies in the control of automated systems installed into modern apartments. Tan et al [10] proposes a general context model for businesses that appears independent of any particular domain.…”

mentioning

confidence: 99%

Maintaining a Dynamic View of Semantic Web Services Representing Factory Automation Systems

Puttonen

Lobov

Lastra

2013

2013 IEEE 20th International Conference on Web Services

Self Cite

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Software agents controlling production devices must maintain an up-to-date view of the physical world state in order to efficiently reason and plan their actions. Especially in a factory automation system, the world state undergoes rapid evolution, and the world view must remain synchronized with the changes. This paper discusses two approaches to updating the world view based on event notifications sent by web services representing production devices in a manufacturing system. One of the approaches is based on separately specified update rules, and one automatically uses the semantic web service descriptions formulated in OWL-S. While this paper specifically focuses on the factory automation domain, the approaches presented are applicable to other domains as well.

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Ontological framework of context-aware and reasoning middleware for smart homes with health and social services

Cited by 17 publications

References 18 publications

Coordinating emergency response by competent teams

Coordinating emergency response by competent teams

Holistic Context-Sensitivity for Run-Time Optimization of Flexible Manufacturing Systems

Maintaining a Dynamic View of Semantic Web Services Representing Factory Automation Systems

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