The versatility and dimension of smart phone applications is   increasing at magnificent rate and getting more and more advanced in a level that could solve complicated real time tasks. One of the important factors for such advancement has been the powerful sensors embedded on a Smartphone devices and sensory networks. Moreover, Context and Context-awareness would have remained a myth without the advent of sensors. The objective of this thesis has been to contribute to the research work carried out under the MediaSense project. Accordingly, the ultimate purpose of the thesis has been to evaluate and study the feasibility of the adaptive context view proposed in MediaSense Platform. In precise words, the thesis has done three core tasks. Firstly, the theoretical presentation of related works and the significance of the research question have been discussed through various social applications. Secondly, a proof-of-concept application has been developed to simulate what has been proposed in the research work. Finally, Android application has been designed and implemented in order to evaluate and study the techniques presented in a practical scenario. Moreover, in the android application known as SundsvallBIGBuddies, we have used the extensions designed for the existing MediaSense platform. The impact of using Android app relaying on a continuous stream of context data has been presented using graphs and tables.  In order to study the impact we used smart phone and tablets from Samsung.

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As computing devices become more pervasive and integrated with our lives, it becomes useful for these devices to understand the environment which surrounds them and the activities of their users, so that they may adapt themselves to suit the circumstances and best assist their users. To accomplish this, it is necessary that these devices have a model for expressing and sharing contextual data which characterizes the state of the surroundings, the devices and people in an environment, and the relationships between each. This thesis describes a framework for managing the exchange of contextual data between devices and sensors with information about their shared environment, with other devices whose goals are to adapt their behaviour to best suit the circumstances. This function supports the greater goal of implementing a pervasive computing environment. We identify three roles in context sharing: Context Providers which are sources of contextual data such as sensors; Context Consumers which are applications which use contextual data to adapt themselves; and Context Hosts which act as intermediaries facilitating the exchange of data and provide a proxy host for contextual data on behalf of Context Providers. This framework includes protocols to facilitate data exchange between each with considerations for the security and data privacy. This thesis also outlines an extensible model for defining and expressing contextual data and related meta data. The context model can be passed among the context sharing actors to communicate state and relationships between entities in the working environment. / Thesis (Master, Computing) -- Queen's University, 2012-09-07 11:42:42.117

Nous assistons à une époque où toute entreprise (ou organisme), dans le but d’augmenter son pou- voir décisionnel, est fortement intéressée par la collecte et l’analyse des données provenant de multiples sources hétérogènes et variées. Ces sources présentent également une autre spécificité à savoir la sensibilité au contexte. Cette situation nous met face à un enjeu scientifique crucial, du fait qu’elle réunit trois problématiques complémentaires : (i) la résolution de l’hétérogénéité qui peut exister entre les sources,(ii) la construction d’un système d’intégration décisionnel, et (iii) la prise en compte du contexte dans cette intégration. Afin de répondre à ces problématiques, nous nous intéressons dans cette thèse à la conception des applications contextuelles basées sur une ontologie de domaine, supposée existante. Pour ce faire, nous proposons d’abord un modèle de contexte qui intègre les dimensions principales identifiées dans la littérature. Une fois construit, il est lié au modèle de l’ontologie. Cette façon de procéder augmente la flexibilité dans la conception des applications avancées. Ensuite, nous proposons deux cas d’étude : (1) la contextualisation de sources de données sémantiques où nous étendons le système On- toBD/OntoQL afin qu’il prenne en compte le contexte, et (2) la conception d’un entrepôt de données contextuel où le modèle de contexte est projeté sur les différentes phases de conception du cycle de vie. Afin de valider notre proposition, nous présentons un prototype d’outil d’aide à la conception implémentant les différentes étapes de l’approche de conception proposée. / We are witnessing an era when any company is strongly interested in collecting and analyzing data from heterogeneous and varied sources. These sources also have another specificity, namely con- text awareness. Three complementary problems are identified: the resolution of the heterogeneity of the sources, (ii) the construction of a decisional integrating system, and (iii) taking into account the context in this integration. To solve these problems, we are interested in this thesis in the design of contextual applications based on a domain ontology.To do this, we first propose a context model that integrates the main dimensions identified in the literature. Once built, it is linked to the ontology model. This approach increases flexibility in the design of advanced applications. Then, we propose two case studies: (1) the contextualization of semantic data sources where we extend the OntoBD/OntoQL system to take the context into account, and (2) the design of a contextual data warehouse where the context model is projected on the different phases of the life cycle design. To validate our proposal, we present a tool implementing the different phases of the proposed design approach.

This paper's main objective is to consolidate the knowledge on context in the realm of intelligent systems, systems that are aware of their context and can adapt their behavior accordingly. We provide an overview and analysis of 36 context models that are heterogeneous and scattered throughout multiple fields of research. In our analysis, we identify five shared context categories: social context, location, time, physical context, and user context. In addition, we compare the context models with the context elements considered in the discourse on intelligent systems and find that the models do not properly represent the identified set of 3,741 unique context elements. As a result, we propose a consolidation of the findings from the 36 context models and the 3,741 unique context elements. The analysis reveals that there is a long tail of context categories that are considered only sporadically in context models. However, particularly these context elements in the long tail may be necessary for improving intelligent systems' context awareness.

Stepping into the 21st century, we see more and more evidence of the growing trend towards the amalgamation of cyberspace and the physical world. This trend emerged as computing technologies moved o_ desktops and migrated into aspects of our lives through their ubiquitous presence in the physical world. As these technologies become enmeshed in our daily routines, they begin to `disappear' from our awareness and cease to be thought of as technologies and simply become tools of everyday use. Yet even as they disappear, these technologies afford a new way for us to interact with the environments of everyday life and with the ordinary objects within these environments. The furthering of this vision will require, in many cases, the tools and applications to possess greater levels of autonomy and an awareness of the user's context. As a result, the applications gradually depend more and more for their behaviour on the information (context information) that is relevant to user interactions. However, it is difficult to develop new context-aware applications that take into account the ever-increasing amount of context information. This is because: the context information sources vary not only in their types, but also in their availability in different environments; the developers have to spend significant programming efforts in gathering, pre-processing and managing the context information when designing and developing the new applications; and, the information sources can fail from time to time, resulting in operational disruptions or service degradation. To make such context information easily and widely available for to new context-aware applications, there is a need to provide information provisioning and management at the infrastructure level. This thesis explores the issues and challenges associated with the development of an autonomic middleware system that addresses the problems discussed earlier, with a particular focus on supporting fault-tolerant context information provisioning for multiple applications, providing the support of opportunistic use of the context sources (the sensors) and, maximising overall the system's interoperability for the open, dynamic computing environments (Ubiquitous computing, for example). The research presented in this thesis makes several key contributions. First, it introduces a novel standards-based approach to model heterogeneous information sources and data preprocessing components. Second, it details the design of a standards-based approach for supporting the dynamic composition of context information sources and pre-processing components. This approach plays an important role in supporting fault-tolerant information provisioning from the sensors and the opportunistic use of these sensors. More specifically, it enables any given piece of high-level context information, as required by applications, to be derived via multiple different pre-processing models, resulting in a higher degree of reliability. Third, it describes the design and development of an autonomic context management system (ACoMS), which harnesses the first two contributions above. Finally, the thesis shows how this autonomic context management system can support context-aware routing in wireless mesh networks. These contributions are evaluated through two corresponding case studies. The first is a practical firefighting scenario with three prototypical applications that validate the design and development of ACoMS. The second is an adaptive wireless mesh surveillance camera system that validates the concept of adopting ACoMS as a cross-layer information plane to ease the prototyping and development of new adaptive protocols and systems, and illustrates the needs of adaptive controls at the sensing layer to optimise resource usage.

A growing number of initiatives in recent studies have continued to pursue improvements in e-business through the use of Business Process Management (BPM) methods and tools. However there are still some limitations that need to be addressed. While BPM has been beneficial in healthcare, there are issues around context. These involve a clear need for approaches that facilitate the understanding of context when implementing healthcare processes. This thesis introduces a BPM framework and its supporting methodology for representing and modeling context for information systems design. Scenario compositions are developed as a mechanism for linking descriptive workflow information and graphical models representing many viewpoints involved in the system development and use processes. Design patterns are used as a common information platform to bridge different context representation formats. By combining scenarios and design patterns representing context, chains of relations between context, their triggering factors, and their influences on user actions can explicitly be described and modeled.

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