Ontology-based context-aware middleware for smart spaces

Qin, Weijun; Shi, Yuanchun; Suo, Yue

doi:10.1016/s1007-0214(07)70179-7

Cited by 38 publications

(14 citation statements)

References 6 publications

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“…However, some authors consider the use of ontologies in context aware environments to be very sensitive to the size of the dataset and unreasonable to use for time-critical applications [8]. Similarly, in [3], the authors have reported a limitation in semantic processing, where the reasoner and rule engine would not be able to perform in realtime when applied to the full semantics model.…”

Section: Information and Communications Technologymentioning

confidence: 99%

“…As a result, an ontology-based semantic model has become prevalent in the area of context aware and Smart City technologies [1,12,14]. Nonetheless, semantic processing is not capable of managing such vast amounts of data, as are expected in the Smart City scenario, in realtime [1,2,3,8]. Furthermore, in [10], the call for application of Big Data technology in Smart Grid analytics is emphasized and, as suggested in [11], cloud delivery of energy management solutions is largely becoming an accepted approach.…”

Section: Introductionmentioning

confidence: 99%

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Big Data in Large Scale Intelligent Smart City Installations

Girtelschmid

Steinbauer

Kumar

et al. 2013

Proceedings of International Conference on Information Integration and Web-Based Applications &Amp; Services

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This paper highlights how the domain of Smart Cities is often modeled by ontologies to create applications and services that are highly flexible, (re)configurable, and inter-operable. However, ontology repositories and their accompanying reasoning and rule languages face the disadvantage of bad runtime behavior, especially if the models grow large in size. We propose an architecture that uses tools and methods from the domain of Big Data processing in conjunction with an ontology repository and a rule engine to overcome potential performance bottlenecks that will occur in this scenario.

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Section: Information and Communications Technologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Big Data in Large Scale Intelligent Smart City Installations

Girtelschmid

Steinbauer

Kumar

et al. 2013

Proceedings of International Conference on Information Integration and Web-Based Applications &Amp; Services

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“…A context aware framework must posses an underlying context management mechanism that manages retrieval and storage of context along with enabling context recognition, querying, filtering and composition mechanisms. CoBrA [10], CAMidO [11], Context Toolkit [12], Camps [13] are some of the earliest context management middlewares for context aware systems with emphasis on context management. Excluding Context Toolkit all the rest are ontology based and therefore support reasoning other than context management as well.…”

Section: The Challenge Of Context-aware Middlewarementioning

confidence: 99%

An artificial chemistry based framework for personal and social context aware smart spaces

Ikram

Baker

Knappmeyer

et al. 2011

2011 7th International Wireless Communications and Mobile Computing Conference

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Supporting context-aware services and applications that are delivered to a user as they move through a smart space is a challenge. The complexity of awareness and interaction requires an efficient interaction and adaptation model. Most research prototypes comprise of many models and extensive middleware which seems excessive for simple context-aware applications involving pervasive devices. Part of the problem is finding a conceptual abstraction which is compact and concise yet can exclusively model all the dynamism and expressivity required for such a system. In this paper we propose a context aware architecture based on a smart space context model and a middleware inspired by chemical reactions.

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“…Systems that can actually build this kind of additional knowledge will be in a better position to suggest and implement more appropriate adaptations [3]. The new generation of context-aware systems is using ontologies to build this additional knowledge [4], [5]. An ontology-based approach to model context provides the means to formalise concepts from acquired context and to specify relations and rules between those concepts.…”

Section: Ontologies In Context-aware Contentmentioning

confidence: 99%

Multicao: A semantic approach to context-aware adaptation decision taking

Barbosa

Andrade²

2009

2009 10th Workshop on Image Analysis for Multimedia Interactive Services

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The use of context is already a reality in different application fields. One such example is the Robotics field, where sensors are used to capture information about the surrounding environment, allowing the system to react to changes. But also in the multimedia communications field, some work has recently emerged to allow combining sensed context and use that combined information to decide how to adapt the content. This paper describes the MULTICAO ontology, which lies at the core of an Adaptation Decision Engine, providing it with a formal description of the surrounding environment in a similar way as humans would describe it. This way the system has higher chances to take adaptation decisions that best meet users' expectations.

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Ontology-based context-aware middleware for smart spaces

Cited by 38 publications

References 6 publications

Big Data in Large Scale Intelligent Smart City Installations

Big Data in Large Scale Intelligent Smart City Installations

An artificial chemistry based framework for personal and social context aware smart spaces

Multicao: A semantic approach to context-aware adaptation decision taking

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