A survey on context awareness

Liu, Wei; Li, Xue; Huang, Daoli

doi:10.1109/csss.2011.5972040

Cited by 40 publications

(13 citation statements)

References 5 publications

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“…An entity is a person, object or environment that is considered relevant to the interaction between an application and a user, including the user and the applications themselves". In their work, these authors illustrated the context based on what is relevant to the interaction between the user and the application [16].…”

Section: Context Awareness Approachmentioning

confidence: 99%

Dynamic composition components based on machine learning: architecture design and process

Zouani

Abdali

Zaouiat

2021

IJEECS

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<p>The dynamic composition of components is an emerging concept that aims to allow a new application to be constructed based on a user’s request. Three main ingredients must be used to achieve the dynamic composition of components: goal, scenario, and context-awareness. These three ingredients must be completed by artificial intelligence (AI) techniques that help process discovery and storage. This paper presents framework architecture for the dynamic composition of components that can extract expressed goals, deduce implicit ones using AI. The goal will be combined with pertinent contextual data, to compose the relevant components that meet the real requirements of the user. The core element of our proposed architecture is the composer component that (i) negotiate user goal, (ii) load the associated scenarios and choose the most suitable one based on user goal and profile, (iii) get binding information of scenario’s actions, (iv) compose the loaded actions, and (v) store the new component as a tree of actions enabled by contextual or process constraint. In our e-learning proven of concept, we consider five components: composer component, reader component, formatter component, matcher component, and executor component. These five components stipulate that a course is the combination of existing/scrapped chapters that have been adapted to a user profile in terms of language, level of difficulty, and prerequisite. The founding result shows that AI is not only an element that enhances system performance in terms of timing response but a crucial ingredient that guides the dynamic composition of components.</p><div style="display: none;"> </div>

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Section: Context Awareness Approachmentioning

confidence: 99%

Dynamic composition components based on machine learning: architecture design and process

Zouani

Abdali

Zaouiat

2021

IJEECS

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“…Abowd et al (1999) differentiated between primary and secondary context, in addition to conceptual and operational. Liu et al (2011) stated that context can be classified as user, physical or networking. Table 1 provides a summary of the different approaches adopted for categorizing context.…”

Section: Context Information Managementmentioning

confidence: 99%

Ontology-Based Context Modeling in Physical Asset Integrity Management

Al-Shdifat

Emmanouilidis

Khan

et al. 2020

Front. Comput. Sci.

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Asset management is concerned with the management practices, technologies and tools necessary to maximize the value delivered by physical engineering assets. IoT-generated data are increasingly considered as an asset and the data asset value needs to be maximized too. However, asset-generated data in practice are often collected in non-actionable form. Collected data may comprise a wide number of parameters, over long periods of time and be of significant scale. Yet they may fail to represent the range of possible scenarios of asset operation or the causal relationships between the monitored parameters, and so the size of the data collection, while adding to the complexity of the problem, does not necessarily allow direct data asset value exploitation. One way to handle data complexity is to introduce context information modeling and management, wherein data and service delivery are determined upon resolving the apparent context of a service or data request. The aim of the present paper is, therefore, 2-fold: to analyse current approaches to addressing IoT context information management, mapping how context-aware computing addresses key challenges and supports the delivery of monitoring solutions; and to develop a maintenance context ontology focused on failure analysis of mechanical components so as to drive monitoring services adaptation. The approach is demonstrated by applying the ontology on an industrially relevant physical gearbox test rig, designed to model complex misalignment cases met in manufacturing and aerospace applications.

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“…Moreover, context-aware technology has the capability to sense, detect, and grab the environment around users and get the dynamic changes to speculate their behavior [12]. …”

Section: Related Workmentioning

confidence: 99%

Intelligent Context-Aware and Adaptive Interface for Mobile LBS

Feng

Liu

2015

Computational Intelligence and Neuroscience

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Context-aware user interface plays an important role in many human-computer Interaction tasks of location based services. Although spatial models for context-aware systems have been studied extensively, how to locate specific spatial information for users is still not well resolved, which is important in the mobile environment where location based services users are impeded by device limitations. Better context-aware human-computer interaction models of mobile location based services are needed not just to predict performance outcomes, such as whether people will be able to find the information needed to complete a human-computer interaction task, but to understand human processes that interact in spatial query, which will in turn inform the detailed design of better user interfaces in mobile location based services. In this study, a context-aware adaptive model for mobile location based services interface is proposed, which contains three major sections: purpose, adjustment, and adaptation. Based on this model we try to describe the process of user operation and interface adaptation clearly through the dynamic interaction between users and the interface. Then we show how the model applies users' demands in a complicated environment and suggested the feasibility by the experimental results.

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A survey on context awareness

Cited by 40 publications

References 5 publications

Dynamic composition components based on machine learning: architecture design and process

Dynamic composition components based on machine learning: architecture design and process

Ontology-Based Context Modeling in Physical Asset Integrity Management

Intelligent Context-Aware and Adaptive Interface for Mobile LBS

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