Quality of Context for VANETs: QoC Metrics for Connectivity in VANETs

Author(s):  
Margarete Sá ◽  
Sérgio Gorender
Keyword(s):  
Sensors ◽  
2017 ◽  
Vol 17 (12) ◽  
pp. 2853 ◽  
Author(s):  
Berto Gomes ◽  
Luiz Muniz ◽  
Francisco da Silva e Silva ◽  
Davi dos Santos ◽  
Rafael Lopes ◽  
...  

2020 ◽  
Author(s):  
Diandre de Paula ◽  
Daniel Saraiva ◽  
Romeiro Natália ◽  
Nuno Garcia ◽  
Valderi Leithardt

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


Author(s):  
José Bringel Filho ◽  
Nazim Agoulmine

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.


Author(s):  
Felipe Becker Nunes ◽  
Fabricio Herpich ◽  
Gleizer Bierhalz Voss ◽  
Roseclea Duarte Medina

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.


Author(s):  
Yingyi Bu ◽  
Tao Gu ◽  
Xianping Tao ◽  
Jun Li ◽  
Shaxun Chen ◽  
...  

2008 ◽  
Vol 3 (3) ◽  
Author(s):  
Kamran Sheikh ◽  
Maarten Wegdam ◽  
Marten Van Sinderen

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