Trustworthiness and Quality of Context Information

Context-aware service platforms use context information to customize their services to the current users’ situation. Due to technical limitations in sensors and context reasoning algorithms, context information does not always represent accurately the reality, and Quality of Context (QoC) models have been proposed to quantify this inaccuracy. The problems we have identified with existing QoC models is that they do not follow a standard terminology and none of them clearly differentiate quality attributes related to instances of context information (e.g. accuracy and precision) from trustworthiness, which is a quality attribute related to the context information provider. In this paper we propose a QoC model and management architecture that supports the management of QoC trustworthiness and also contributes to the terminology alignment of existing QoC models.\ud In our QoC model, trustworthiness is a measurement of the reliability of a context information provider to provide context information about a specific entity according to a certain quality level. This trustworthiness value is used in our QoC management architecture to support context-aware service providers in the selection of trustworthy context\ud providers. As a proof of concept to demonstrate the feasibility of our work we show a prototype implementation of our QoC model and management architecture

Determining Trust Scope Attributes Using Goodness of Fit Test: A Survey

Indonesian, as one of the countries with high number of internet users has the potential to serve as the place with great information resources. However, these resources must be accompanied by the availability of dependable information. Information trustworthiness can be obtained by assessing the confidence level (trust) of the source of information. This can be determined by using trust scope attributes. Hence, in this study, we intended to establish the trust scope attributes by means of utilizing the ones contained in the User Profile provided by social media; in this case Facebook, Google+, Twitter, and Linkedin. We carried out the research by conducting four stages namely data collection, attributes grouping, attribute selection, and surveys. A survey was then distributed to 257 randomly selected respondents (divided into two clusters: civilians and military officers) to seek for their opinions in terms of what attributes were considered to be crucial in defining the believability of an information source. Chi-square Goodness of fit Test was conducted to compare observed data with data we would expect to obtain. The results of the research suggested that there was similar judgment in terms of dictating source of information trustworthiness chosen by the research participants with the attributes provided by trust scope category. In this research, both civilians and military officer clusters concurrently perceived that educational background was the most dependable attribute

CONTEXT MANAGEMENT: TOWARD ASSESSING QUALITY OF CONTEXT PARAMETERS IN A UBIQUITOUS AMBIENT ASSISTED LIVING ENVIRONMENT

This paper provides an approach to assessing Quality of Context (QoC) parameters in a ubiquitous Ambient Assisted Living (AAL) environment. Initially, the study presents a literature review on QoC, generating taxonomy. Then it introduces the context management architecture used. The proposal is verified with the Siafu simulator in an AAL scenario where the user’s health is monitored with information about blood pressure, heart rate and body temperature. Considering some parameters, the proposed QoC assessment allows verifying the extent to which the context information is up-to-date, valid, accurate, complete and significant. The implementation of this proposal might mean a big social impact and a technological innovation applied to AAL, at the disposal and support of a significant number of individuals such as elderly or sick people, and with a more precise technology

The impact of reviews on consumers’ consideration towards electric vehicles (EV)

The development of the Internet and technology led to increasingly more digital consumers, who are tired of being marketed to. Thus, many companies started adopting reviews as part of their marketing strategy to reach the target audience in social media. This trend is also present in the market of electric vehicle (EV). This dissertation was developed with the aim of understanding how EV consumers perceive social media online posts as endorsers of EV as a mobility product, through the lens of the Source Credibility Model. These objectives were addressed using a quantitative research method that adopted an experiment between subjects, comparing firm-created reviews (firmcreated content) with user-created reviews (user-generated content) . Previous literature was reviewed, and an online questionnaire was conducted, with 243 obtained valid answers. Moreover, the willingness to consider and willingness to buy an EV were considered as a variable in the analysis, being proposed because of trustworthiness communicated by the type of review. The results of this dissertation found that the difference between User-Generated Content and car brand reviews (firm-created content) is not statistically significant in the moment of influencing decision of considering or buying an EV as a mobility product. It was observed that there is a valid positive influence relationship of trustworthiness on the relationship between the types of review and the consideration of buying an EV. Lastly, with this model and this research, it was confirmed that there is a positive influence of the trustworthiness on willingness to buy and consideration to buy.A emergência da Internet e o desenvolvimento da tecnologia levou a um número crescente de consumidores digitais, cansados de serem comercializados. Assim, muitas empresas começaram a adotar o marketing de publicação em linha para chegar às pessoas nas redes sociais. Esta nova abordagem do marketing é também utilizada como uma ferramenta no marketing social para promover a mudança de comportamento, especialmente quanto ao processo de decisão de aquisição de um novo veículo elétrico (VE). Esta dissertação foi desenvolvida com o objetivo de compreender como os consumidores de VE veem os anúncios online nas redes sociais como endossantes de VE como um produto de mobilidade, partindo do Modelos de Credibilidade na Fonte. Estes objectivos foram abordados utilizando um método de investigação quantitativa que adoptou uma experiência entre sujeitos, comparando conteúdo criado por empresas, com conteúdo criado por utilizadores online. A literatura anterior foi revista e foi conduzido um questionário online, com 243 respostas bem-sucedidas. Além disso, a vontade de considerar foi incluída como uma variável na análise com influência direta na fiabilidade, dificilmente abordada na literatura. Os resultados constataram que a diferença entre o Conteúdo Gerado pelo Utilizador e o conteúdo de marcas de automóveis não é estatisticamente significativa, no momento de influenciar a decisão de considerar um VE como um produto de mobilidade. Observou-se que existe uma relação de influência positiva válida de confiança na relação entre os tipos de revisão e a consideração da compra. Finalmente, foi confirmado que existe uma influência positiva da fiablilidade na vontade de comprar

Quality of Context in Context-Aware Systems

Context-aware Systems (CASs) are becoming increasingly popular and can be found in the areas of wearable computing, mobile computing, robotics, adaptive and intelligent user interfaces. Sensors are the corner stone of context capturing however, sensed context data are commonly prone to imperfection due to the technical limitations of sensors, their availability, dysfunction, and highly dynamic nature of environment. Consequently, sensed context data might be imprecise, erroneous, conflicting, or simply missing. To limit the impact of context imperfection on the behavior of a context-aware system, a notion of Quality of Context (QoC) is used to measure quality of any information that is used as context information. Adaptation is performed only if the context data used in the decision-making has an appropriate quality level. This paper reports an analytical review for state of the art quality of context in context-aware systems and points to future research directions

WikiSensing: A collaborative sensor management system with trust assessment for big data

Big Data for sensor networks and collaborative systems have become ever more important in the digital economy and is a focal point of technological interest while posing many noteworthy challenges. This research addresses some of the challenges in the areas of online collaboration and Big Data for sensor networks. This research demonstrates WikiSensing (www.wikisensing.org), a high performance, heterogeneous, collaborative data cloud for managing and analysis of real-time sensor data. The system is based on the Big Data architecture with comprehensive functionalities for smart city sensor data integration and analysis. The system is fully functional and served as the main data management platform for the 2013 UPLondon Hackathon. This system is unique as it introduced a novel methodology that incorporates online collaboration with sensor data. While there are other platforms available for sensor data management WikiSensing is one of the first platforms that enable online collaboration by providing services to store and query dynamic sensor information without any restriction of the type and format of sensor data. An emerging challenge of collaborative sensor systems is modelling and assessing the trustworthiness of sensors and their measurements. This is with direct relevance to WikiSensing as an open collaborative sensor data management system. Thus if the trustworthiness of the sensor data can be accurately assessed, WikiSensing will be more than just a collaborative data management system for sensor but also a platform that provides information to the users on the validity of its data. Hence this research presents a new generic framework for capturing and analysing sensor trustworthiness considering the different forms of evidence available to the user. It uses an extensible set of metrics that can represent such evidence and use Bayesian analysis to develop a trust classification model. Based on this work there are several publications and others are at the final stage of submission. Further improvement is also planned to make the platform serve as a cloud service accessible to any online user to build up a community of collaborators for smart city research.Open Acces

Utilização de QoC para melhorar o cenário experimental de sensores biomédicos para suporte às aplicações móveis distribuídas

TCC(graduação) - Universidade Federal de Santa Catarina. Centro Tecnológico. Ciências da Computação.Atualmente sensores biomédicos estão sendo cada vez mais usados para coletar dados em determinados ambientes monitorados chamados de Ambient Assisted Living (AAL). Os dados desses ambientes, como por exemplo temperatura, pressão e umidade são coletados por sensores para que assim possa ser feito um monitoramento do ambiente à distância. A tendência de se coletar dados dessa maneira está aumentando, tendo em vista que é uma forma rápida e eficiente de monitorar ambientes a longa distância, podendo enviar os dados para um servidor pela rede. No entanto deve-se tomar o cuidado para que os dados transportados ao servidor estejam corretos e limpos, ou seja, sem informações inúteis, que não interessam em determinados contextos. Esse trabalho visa apresentar um estudo de uma abordagem de utilizar parâmetros de Qualidade de Contexto (QoC) nesses ambientes assistidos para configurar melhor os sensores daquele ambiente. Já que a inexistência de qualidade pode levar sistemas monitorados a agir de maneira inadequada, podendo oferecer riscos ao usuário dependendo da aplicação. A avaliação do QoC pode melhorar o sistema e ajudar a configurá-los, ou seja, em determinados lapsos de qualidade, uma ação específica pode ser tomada. Para validar o objetivo do trabalho, foi proposto um método de quantificar a qualidade de contexto e depois avaliá-la. Para a análise desse método foi utilizado um simulador de contexto, onde foi possível a criação de um cenário, bem como atuação de sensores biomédicos em uma pessoa que andava pelo cenário. Através deste simulador foi possível gerar tabelas com os resultados do QoC provindos das leituras do sensor e com isso foi feito uma avaliação desses resultados. A partir da avaliação feita, percebeu-se que é possível identificar não só a existência de um problema na qualidade dos dados, mas também qual é a possível fonte do problema que está causando essas falhas de qualidade

Gestion de la qualité de contexte pour l'intelligence ambiante

L'informatique sensible au contexte vise à réduire la quantité d'informations explicites qu'un utilisateur doit fournir pour que le système accomplisse la tâche souhaitée. Ceci est particulièrement vrai dans le domaine récent de l'intelligence ambiante où les objets de la vie courante deviennent capables de déclencher une action ou un échange spontané d'informations, sans interaction avec l'utilisateur. Les progrès techniques en matière de réseaux de communication sans fil, d'équipements mobiles individuels, de capteurs et de logiciels embarqués, rendent aujourd'hui possibles des services aux usagers dépendants du contexte, mais les applications concrètes demeurent encore très limitées. Les travaux existants dans la littérature décomposent la gestion de contexte en quatre fonctionnalités: la collecte, l'interprétation, la détection de situations et l'utilisation pour l'adaptation. L'élément discriminant des solutions existantes est la qualité des informations abstraites obtenues par inférence et devant caractériser les situations de l'utilisateur. Les limites de ces solutions sont le manque de composition aisée des informations de contexte, le passage à l'échelle, tant en termes de quantité d'informations de contexte que de nombre d'applications clientes, l'absence de garantie sur la cohérence et la qualité des informations de contexte, et le manque de solutions intergicielles permettant de libérer le concepteur d'applications des aspects liés à la gestion de contexte. Nous nous intéressons dans cette thèse à la gestion de la qualité de contexte (QoC) dans un environnement ambiant. Les problématiques de gestion de la qualité de contexte sont multiples: choisir la méthode adéquate pour la gestion du contexte, extraire la qualité associée au contexte, interpréter et analyser la qualité de contexte pour les applications sensibles au contexte. Nous proposons de répondre à ces problématiques en intégrant la qualité de contexte au sein de la plateforme de gestion de contexte COSMOS (http://picoforge.lntevrv.fr/proiects/svn/cosmos) de l'équipe MARGE (http://www-inf.itsudparis.eu/MARGE) de Télécom SudParis. Afin d'effectuer cette intégration, nous avons conçu des éléments spécifiques à la qualité de contexte et avons mis en place une gestion fine et efficiente de cette qualité en limitant le surcoût associé. Nous proposons également un processus de conception basé sur l'ingénierie dirigée par les modèles afin de générer les éléments requis à la gestion de la qualité de contexte. Nous avons validé nos contributions à l'aide de deux applications fonctionnant sur téléphone mobile : une application de "vente flash" dans un centre commercial et une application de détection de localisation sur un campus. Les tests de performances que nous avons effectués permettent de comparer les résultats avec et sans la prise en compte de la QoC et montrent le faible coût de la gestion de la qualité par rapport aux améliorations apportées aux applications sensibles au contexteContext-aware computing aims to reduce the amount of explicit information required from a user for a system to perform a task. This is particularly true in the recent domain of ambient intelligence where everyday life objects are able to trigger an action or a spontaneous information exchange, without any interaction with the user. Technical advances in wireless communication, personal mobile devices, sensors and embedded software make context-aware services possible, but concrete applications are still very limited. The solutions proposed in the literature decompose context management into four functions: acquisition, interpretation, situation detection and application adaptation. The differentiating element in these proposals is the quality of the high-level context information obtained by inference and characterising the situation of the user. The limits of these solutions are the difficulty for composing context information scalability in terms of the quantity of context information and of the number of client applications, the absence of guarantee on the consistency of context information and the lack of middleware solutions able to free the designer of context-aware applications from the management of context data. In this thesis, we are interested in the management of the quality of context information (QoC) in an ambient environment. There are several key issues in QoC management: choosing the adequate method for context management, extracting the quality associated to the context, analysing and interpreting the quality of the context with regard to the requirements of context-aware applications. We propose to answer these questions by integrating QoC management into the COSMOS context management framework (http://picoforge.int-evry.fr/projects/svn/cosmos) developed by the MARGE team (http://www-inf.itsudparis.eu/MARGE) of Télécom SudParis.For this purpose, we have designed the necessary components dedicated to QoC management and we have implemented the mechanisms allowing a fine-grain manipulation of the QoC together with a limitation of the associated overhead. We also propose a design process based on model-driven engineering in order to automatically generate the elements responsible of QoC management. We validate our contributions through the development of two prototype applications running on mobile phones: a Flash sale offer application to be used in malls and a location detection application proposed to the students of a campus. The performance tests we have conducted allow to compare the results obtained with and without taking into account the QoC and show the low overhead associated to QoC manaqement with regard to the benefits brought to context-aware applications and servicesEVRY-INT (912282302) / SudocSudocFranceF