Modeling Context Information in Pervasive Computing Systems

Henricksen, Karen; Indulska, Jadwiga; Rakotonirainy, Andry

doi:10.1007/3-540-45866-2_14

Cited by 469 publications

(313 citation statements)

References 10 publications

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“…As discussed by Henricksen et al (2002), context information is: incorrect if it does not reflect the true state of the world that it is modelling; inconsistent, for example, if it contains contradictory information; incomplete if certain aspects of the context are unknown. Here is one example of a problem: a situation in which the user is using the application in a certain place and moves to another floor or building; if there is no treatment of quality, the context of location and/or profile that displays their preferences for nearby places to visit will quickly become out of date and may impair its interaction with the application.…”

Section: Quality Of Contextmentioning

confidence: 99%

An adaptive environment based on Moodle with treating of quality of context

Nunes

Herpich

Voss

et al. 2015

IJKL

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Ubiquitous learning (U-Learning) environments collect context information relative to user's preferences and needs, but this information is typically very volatile. On this basis, the Quality of the Context aims at treating this information with the application of the quality parameters. This paper presents a ubiquitous virtual environment, in which three modules (U-SEA, SEDECA and QoC) were developed and integrated with Moodle, and describes the use of a Bootstrap theme to automatically adapt the interface on mobile devices. The results about the integrated modules showed that the UVLE QoC environment operated satisfactorily, based on the assessments made by the group of users who tested the modules and their operation.

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Section: Quality Of Contextmentioning

confidence: 99%

An adaptive environment based on Moodle with treating of quality of context

Nunes

Herpich

Voss

et al. 2015

IJKL

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“…Although we do not have a strong contribution here, we could not write about these requirements without mentioning the QoI aspect. The idea of the classifying associations by Henricksen et al [9] appears to be an important key towards QoI-based semantic reasoning and although they did not explicitly refer to the semantic web paradigm, the model proposed was obviously close to it and its semantic implementation would be straight forward. We also believe that the uncertainty aspect will not be tackled by the engine itself, rather that it is the way the engine is used and wrapped that can ever address this aspect.…”

Section: An Opening On Uncertainty and Quality Of Informationmentioning

confidence: 99%

Semantic Reasoning in Context-Aware Assistive Environments to Support Ageing with Dementia

Tiberghien

Mokhtari

Aloulou

et al. 2012

The Semantic Web – ISWC 2012

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Abstract. Robust solutions for ambient assisted living are numerous, yet predominantly specific in their scope of usability. In this paper, we describe the potential contribution of semantic web technologies to building more versatile solutions -a step towards adaptable context-aware engines and simplified deployments. Our conception and deployment work in hindsight, we highlight some implementation challenges and requirements for semantic web tools that would help to ease the development of context-aware services and thus generalize real-life deployment of semantically driven assistive technologies. We also compare available tools with regard to these requirements and validate our choices by providing some results from a real-life deployment.

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“…This issue has a significant impact when dealing with distributed applications, where the decision making structure and the application are not hosted on the same machine. In order to realize an effective stabilization, stabilization mechanisms should take into account the following characteristics of contextual information mentioned in [11]: (i) Inaccuracy-This property expresses the fact that contextual information give the measure of observed phenomena with some errors. (ii) Incoherence-This property denotes that informations collected from different sensors can be contradictory.…”

Section: Flexible Context-aware Architecturementioning

confidence: 99%

A flexible context stabilization approach for self-adaptive application

Nzekwa

Rouvoy

Seinturier

2010

2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)

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Abstract-Pervasive applications are characterized by variations in their context of execution. Their correct behavior requires continuous adaptations, accordingly to changes observed in their environment. Some of the existing approaches tackle this problem by adding stabilization mechanisms on the decision making layer. In most cases it remains costly for applications to trigger decision making procedures, specially when application changes frequency is potentially high. We believe that, to provide more flexible and efficient context-aware applications, stabilization issues should be addressed separately from decision making issues. In this paper, we present a flexible stabilization approach as an elegant solution to that problem.

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Modeling Context Information in Pervasive Computing Systems

Cited by 469 publications

References 10 publications

An adaptive environment based on Moodle with treating of quality of context

An adaptive environment based on Moodle with treating of quality of context

Semantic Reasoning in Context-Aware Assistive Environments to Support Ageing with Dementia

A flexible context stabilization approach for self-adaptive application

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