Trustworthiness and Quality of Context Information

With the growth of ubiquitous computing, context-aware computing-based applications are increasingly emerging, and these applications demonstrate the impact that context has on the adaptation process. From the context, it will be possible to adapt the application according to the requirements and needs of its users. Therefore, the quality of the context information must be guaranteed so that the application does not have an incorrect or unexpected adaptation process. But like any given data, there is the possibility of inaccuracy and/or uncertainty and so Quality of Context (QoC) plays a key role in ensuring the quality of context information and optimizing the adaptation process. To guarantee the Quality of Context it is necessary to study a quality model to be created, which will have the important function of evaluating the context information. Thus, it is necessary to ensure that the parameters and quality indicators to be used and evaluated are the most appropriate for a given type of application. This paper aims to study a context quality model for the UbiPri middleware, defining its quality indicators to ensure its proper functioning in the process of adaptation in granting access to ubiquitous environments. Keywords: QoC, Model, Context-Aware, Data, Privacy

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Evaluation of Quality of Context Information in U-Health Smart Homes

Advances in Healthcare Information Systems and Administration - Telemedicine and E-Health Services, Policies, and Applications ◽

10.4018/978-1-4666-0888-7.ch008 ◽

2012 ◽

pp. 179-215 ◽

Cited By ~ 3

Author(s):

José Bringel Filho ◽

Nazim Agoulmine

Keyword(s):

Health Systems ◽

Smart Homes ◽

Well Being ◽

Context Information ◽

Context Aware ◽

Daily Lives ◽

Quality Of Context ◽

The Impact ◽

Health And Well Being

Ubiquitous Health (U-Health) smart homes are intelligent spaces capable of observing and correctly recognizing the activities and health statuses of their inhabitants (context) to provide the appropriate support to achieve an overall sense of health and well-being in their inhabitants’ daily lives. With the intrinsic heterogeneity and large number of sources of context information, aggregating and reasoning on low-quality raw sensed data may result in conflicting and erroneous evaluations of situations, affecting directly the reliability of the U-Health systems. In this environment, the evaluation and verification of Quality of Context (QoC) information plays a central role in improving the consistency and correctness of context-aware U-Health applications. Therefore, the objective of this chapter is to highlight the impact of QoC on the correct behavior of U-Health systems, and introduce and analyze the existing approaches of modeling, evaluating, and using QoC to improve its context-aware decision-making support.

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A Perspective about the Application of Quality of Context in U-Learning Environments

Advances in Game-Based Learning - Handbook of Research on 3-D Virtual Environments and Hypermedia for Ubiquitous Learning ◽

10.4018/978-1-5225-0125-1.ch017 ◽

2016 ◽

pp. 410-432 ◽

Cited By ~ 1

Author(s):

Felipe Becker Nunes ◽

Fabricio Herpich ◽

Gleizer Bierhalz Voss ◽

Roseclea Duarte Medina

Keyword(s):

Learning Environments ◽

Usability Testing ◽

Quality Parameters ◽

Context Information ◽

Advantages And Disadvantages ◽

Quality Of Context

U-Learning environments collects context information relative to user's preferences and needs, but this information is typically very volatile. For this reason, Quality of Context is aimed at treating this information by applying quality parameters. This chapter aims to help the reader understand how the quality of context information can be treated in U-Learning environments, which are the main theoretical bases, technologies that support them and what are the methods, advantages and disadvantages related to this approach. In addition, specific cases of development and application of technologies and strategies involving Quality of Context are presented to illustrate all the concepts described. The results of usability testing related to the SUS questionnaire showed that the developed environment described in the case of study operated satisfactorily, based on the assessments made by the group of users who tested the modules and their operation.

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Adaptive interaction support in ambient-aware environments based on quality of context information

Multimedia Tools and Applications ◽

10.1007/s11042-012-1008-1 ◽

2012 ◽

Vol 67 (2) ◽

pp. 409-432 ◽

Cited By ~ 11

Author(s):

M. Anwar Hossain ◽

Ali Asghar Nazari Shirehjini ◽

Abdullah S. Alghamdi ◽

Abdulmotaleb El Saddik

Keyword(s):

Context Information ◽

Quality Of Context ◽

Adaptive Interaction

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Quality of Context: models and applications for context-aware systems in pervasive environments

The Knowledge Engineering Review ◽

10.1017/s0269888914000034 ◽

2014 ◽

Vol 29 (2) ◽

pp. 154-170 ◽

Cited By ~ 32

Author(s):

Atif Manzoor ◽

Hong-Linh Truong ◽

Schahram Dustdar

Keyword(s):

Context Information ◽

Context Aware ◽

Actual Problem ◽

Problem Context ◽

Pervasive Environments ◽

Specific Measurement ◽

Lack Of Information ◽

Quality Of Context ◽

Context Models

AbstractLimitations of sensors and the situation of a specific measurement can affect the quality of context information that is implicitly collected in pervasive environments. The lack of information about Quality of Context (QoC) can result in degraded performance of context-aware systems in pervasive environments, without knowing the actual problem. Context-aware systems can take advantage of QoC if context producers also provide QoC metrics along with context information. In this paper, we analyze QoC and present our model for processing QoC metrics. We evaluate QoC metrics considering the capabilities of sensors, circumstances of specific measurement, requirements of context consumer, and the situation of the use of context information. We also illustrate how QoC metrics can facilitate in enhancing the effectiveness and efficiency of different tasks performed by a system to provide context information in pervasive environments.

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The Rhadamanthys Quality of Context Architecture

10.5753/sbcup.2017.3317 ◽

2017 ◽

Author(s):

Hélio Carlos Brauner Filho ◽

Claudio Fernando Resin Geyer

Keyword(s):

Internet Of Things ◽

Ranking And Selection ◽

Context Information ◽

User Requirements ◽

Individual Quality ◽

Quality Of Context ◽

Single Score

With the rising number of Internet of Things devices and context providers, the need for sorting and selecting them according to user requirements and to the quality of sensed information becomes prevalent. Thus, this paper presents the Rhadamanthys architecture, designed to fulfill this requirement using Quality of Context information for both ranking and selection. Individual Quality of Context criteria as defined in the literature are evaluated for each available provider and used in formulae to obtain a single score that enables ranking and allows selection.

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