Dans ce travail de recherche, nous nous sommes intéressés à la conception et au développement d'un système iNformatIque COmmunautaire mobiLe et AdapTatif, appelé NICOLAT. Ce dernier vise à supporter une CoP dans laquelle l'apprentissage s'effectue via la résolution communautaire de problèmes en offrant des solutions qui permettent de limiter les facteurs qui peuvent aboutir à la démotivation des membres de la CoP.Pour expérimenter et valider les solutions que nous proposons à travers ce système, nous ciblons la CoP des enseignants usagers de la méthode pédagogique MAETIC, qui peuvent rencontrer, en classe, des problèmes dans l'usage de celle-ci.Ainsi, nos principales contributions se résument dans les points suivants : 1) La mise en place du noyau communautaire du système NICOLAT. Ce dernier est sous forme d'un réseau social supportant la résolution communautaire de problèmes, 2) La mise en place d'une couche de résolution de problèmes ayant pour objectif d'aider le membre à résoudre son problème par exploitation de l'historique des problèmes résolus dans le passé. Ceci pour minimiser le nombre de demandes d'aide répétitives. Le cycle du raisonnement RàPC (Raisonnement à Partir de Cas) a été utilisé pour guider ce processus, 3) La mise en place de deux couches d'adaptation permettant de supporter les interactions des membres dans les outils d'interaction qu'ils préfèrent ou avec lesquels ils sont familiarisés le plus. L'objectif visé par cette adaptation est, d'une part, de dépasser les problèmes de prise en main de nouveaux outils d'interaction. D'autre part, de permettre l'accès au système en cas de mobilité et minimiser ainsi le temps de réponse, 4) La mise en place d'une approche de sélection des membres qui peuvent contribuer positivement à résoudre un problème à qui faire aboutir la demande d'aide. L'objectif est de permettre à un membre cherchant à résoudre son problème de recevoir une réponse pertinente / In this research work, we focused on design and development of an adaptive and mobile community system, called NICOLAT (iNformatIque COmmunautaire mobiLe et AdapTatif). The latter aims to support a Community of Practice (CoP) in which learning is done through community problem solving by providing solutions that limit the factors that can lead to the demotivation of the CoP members.To experiment and validate the solutions we provide through this system, we target the CoP of teachers users of the MAETIC pedagogical method, who can meet, in classroom, problems in the use of it.Thus, our main contributions are summarized in the following points: 1) Establishment of community kernel of the NICOLAT system. The latter is as a social network supporting the community solving of problems, 2) Implementation of problems resolution layer that aims to help the member solve his problem through the exploitation of the history of problems solved in the past. This is to minimize the number of repetitive help requests. The cycle of the CBR (Case-Based Reasoning) was used to guide this process, 3) Establishment of an interactions adaptation layer to support the members' interactions in the interaction tools they prefer or with which they are most familiar. The purpose of this adaptation is, firstly, to exceed the problems of interaction tools manipulation. On the other hand, to enable access to the system in case of mobility and thereby minimize response time, 4) Establishment of a dynamic approach of selection of members who can contribute positively to solve a problem, to whom bring the help requests. The objective is to enable a member seeking to solve his problem to receive a relevant answer

Pervasive (ubiquitous) computing is a new paradigm where the computers are submerged into the background of the everyday life. One important aspect of pervasive systems is context-awareness. Context-aware systems are those that can adapt their behaviours according to the current context. Context-aware applications are being integrated into our everyday activity aspects such as: health care, smart homes and transportations. There exist a wide range of context-aware applications such as: mobile phones, learning systems, smart vehicles. Some context-aware systems are critical since the consequence of failing to identify a given context may be catastrophic. For example, an auto-pilot system is a critical context-aware system; it senses the humidity, clouds, wind speed and accordingly adjusts the altitude, throttle and other parameters. Being a critical context-aware system has to be provably correct. Policy-based approaches has been used in many applications but not in context-aware systems. In this research, we want to discover the anatomy (i.e. architecture, structure and operational behaviour) of policy-based management as applied to context-aware systems, and how policies are managed within such a dynamic system. We propose a novel computational model and its formalisation is presented using the Calculus of Context-aware Ambients (CCA). CCA has been proposed as a suitable mathematical notation to model mobile and context-aware systems. We decided to use CCA due to three reasons: (i) in CCA, mobility and context-awareness are primitive constructs and are treated as first-class citizens; (ii) properties of a system can be formally analysed; (iii) CCA specifications are executable, and thus, leading to rapid prototyping and early validation of the system properties. We, then show how policies can be expressed in CCA. For illustration, the specification of the event-condition-action (ECA) conceptual policy model is modelled in CCA in a natural fashion. We also propose a policy-based architecture for context-aware systems, showing its different components, and how they interact. Furthermore, we give the specification of the policy enforcement mechanism used in our proposed architecture in CCA. To evaluate our approach, a real-world case study of an infostation-based mobile learning (mLearning) system is chosen. This mLearning system is deployed across a university campus to enable mobile users to access mobile services (mServices) represented by course materials (lectures, tests and tutorials) and communication services (intelligent message notification and VoIP). Users can access the mServices through their mobile devices (Hand-set phones, PDAs and laptops) regardless of their device type or location within a university campus. We have specified the mLearning system in CCA (i.e. specification based on policies of the mServices), afterwards, the specification is simulated using the CCA interpreter tool. We have developed an animation tool specially designed for the mLearning system. The animation tool provides graphical representation of the CCA processes. In terms of safety and liveness, some important properties of the mLearning system have been validated as a proof of concept.

Recent advances in sensor technologies and the growing interest in context- aware applications, such as targeted advertising and location-based services, have led to a demand for understanding human behavior patterns from sensor data. People engage in routine behaviors. Automatic routine discovery goes beyond low-level activity recognition such as sitting or standing and analyzes human behaviors at a higher level (e.g., commuting to work). The goal of the research presented in this thesis is to automatically discover high-level semantic human routines from low-level sensor streams. One recent line of research is to mine human routines from sensor data using parametric topic models. The main shortcoming of parametric models is that they assume a fixed, pre-specified parameter regardless of the data. Choosing an appropriate parameter usually requires an inefficient trial-and-error model selection process. Furthermore, it is even more difficult to find optimal parameter values in advance for personalized applications. The research presented in this thesis offers a novel nonparametric framework for human routine discovery that can infer high-level routines without knowing the number of latent low-level activities beforehand. More specifically, the frame-work automatically finds the size of the low-level feature vocabulary from sensor feature vectors at the vocabulary extraction phase. At the routine discovery phase, the framework further automatically selects the appropriate number of latent low-level activities and discovers latent routines. Moreover, we propose a new generative graphical model to incorporate multimodal sensor streams for the human activity discovery task. The hypothesis and approaches presented in this thesis are evaluated on public datasets in two routine domains: two daily-activity datasets and a transportation mode dataset. Experimental results show that our nonparametric framework can automatically learn the appropriate model parameters from multimodal sensor data without any form of manual model selection procedure and can outperform traditional parametric approaches for human routine discovery tasks.

Context information brings new opportunities for efficient and effective applications and services on mobile devices. Many existing work exploit the context dependency of mobile usage for specific applications, and show significant, quantified, performance gains by utilizing context. In order to be practical, such works often pay careful attention to the energy and processing costs of context awareness while attempting to maintain reasonable accuracy. These works also have to deal with the challenges of multiple sources of context, which can lead to a sparse training data set. Even with the abundance of such work, quantifying context-dependency and the relationship between context-dependency and performance achievements remains an open problem, and solutions to manage the and challenges of context awareness remain ad-hoc. To this end, this dissertation methodologically quantifies and measures the context dependency of three principal types of mobile usage in a methodological, application agnostic yet practical manner. The three usages are the websites the user visits, the phone numbers they call, and the apps they use, either built-in or obtained by the user from the App Store . While this dissertation measures the context dependency of these three principal types of mobile usage, its methodology can be readily extended to other context-dependent mobile usage and system resources. This dissertation further presents SmartContext, a framework to systematically optimize the energy cost of context awareness by selecting among different context sources, while satisfying the system designer’s cost-accuracy tradeoffs. Finally, this thesis investigates the collective effect of social context on mobile usage, by separating and comparing LiveLab users based on their socioeconomic groups. The analysis and findings are based on usage and context traces collected in real-life settings from 24 iPhone users over a period of one year. This dissertation presents findings regarding the context dependency of three principal types of mobile usage; visited websites, phone calls, and app usage. The methodology and lessons presented here can be readily extended to other forms of context and context-dependent usage and resources. They guide the development of context aware systems, and highlight the challenges and expectations regarding the context dependency of mobile usage.

Context-aware systems can dynamically adapt to user situations to provide smarter services. In general, context refers to the information that can be used to characterize these situations, and context models are deployed to specify contextual information described in context-aware systems. However, even though user context is highly dynamic, existing context models either focus on modeling static views of context or lack appropriate design abstractions to deal with dynamic aspects and interactions involving contextual elements such location, time, user roles, social relationships, and changing preferences. Moreover, virtual environments have not been modelled by most of the existing context models even though online interaction is very common and popular. This thesis presents a dynamic user-centric context model that can be used to model the aspects of context-aware systems that are subject to frequent change. Four case studies are proposed to illustrate the applicability of the approach taken by this thesis, and they are in the domains of mobile e-healthcare, mobile commerce, mobile tourism, and mobile augmented reality gaming. Benefits of the proposed model include avoiding the development of context-aware systems from scratch, enabling future use of model-driven approaches, and reducing implementation effort.

Context-aware systems can dynamically adapt to user situations to provide smarter services. In general, context refers to the information that can be used to characterize these situations, and context models are deployed to specify contextual information described in context-aware systems. However, even though user context is highly dynamic, existing context models either focus on modeling static views of context or lack appropriate design abstractions to deal with dynamic aspects and interactions involving contextual elements such location, time, user roles, social relationships, and changing preferences. Moreover, virtual environments have not been modelled by most of the existing context models even though online interaction is very common and popular. This thesis presents a dynamic user-centric context model that can be used to model the aspects of context-aware systems that are subject to frequent change. Four case studies are proposed to illustrate the applicability of the approach taken by this thesis, and they are in the domains of mobile e-healthcare, mobile commerce, mobile tourism, and mobile augmented reality gaming. Benefits of the proposed model include avoiding the development of context-aware systems from scratch, enabling future use of model-driven approaches, and reducing implementation effort.

The IoT concept has revolutionised the vision of the future Internet with the advent of standards such as 6LoWPAN making it feasible to extend the Internet into previously isolated environments, e.g., WSNs. The abstraction of resources as services, has opened these environments to a new plethora of potential applications. Moreover, the web service paradigm can be used to provide interoperability by offering a standard interface to interact with these services to enable WoT paradigm. However, these networks pose many challenges, in terms of limited resources, that make the adaptability of existing IP-based solutions infeasible. As traditional service discovery and selection solutions demand heavy communication and use bulky formats, which are unsuitable for these resource-constrained devices incorporating sleep cycles to save energy. Even a registry based approach exhibits burdensome traffic in maintaining the availability status of the devices. The feasible solution for service discovery and selection is instrumental to enable the wide application coverage of these networks in the future. This research project proposes, TRENDY, a new compact and adaptive registry-based SDP with context awareness for the IoT, with more emphasis given to constrained networks, e.g., 6LoWPAN It uses CoAP-based light-weight and RESTful web services to provide standard interoperable interfaces, which can be easily translated from HTTP. TRENDY's service selection mechanism collects and intelligently uses the context information to select appropriate services for user applications based on the available context information of users and services. In addition, TRENDY introduces an adaptive timer algorithm to minimise control overhead for status maintenance, which also reduces energy consumption. Its context-aware grouping technique divides the network at the application layer, by creating location-based groups. This grouping of nodes localises the control overhead and provides the base for service composition, localised aggregation and processing of data. Different grouping roles enable the resource-awareness by offering profiles with varied responsibilities, where high capability devices can implement powerful profiles to share the load of other low capability devices. Thus, it allows the productive usage of network resources. Furthermore, this research project proposes APPUB, an adaptive caching technique, that has the following benefits: it allows service hosts to share their load with the resource directory and also decreases the service invocation delay. The performance of TRENDY and its mechanisms is evaluated using an extensive number of experiments performed using emulated Tmote sky nodes in the COOJA environment. The analysis of the results validates the benefit of performance gain for all techniques. The service selection and APPUB mechanisms improve the service invocation delay considerably that, consequently, reduces the traffic in the network. The timer technique consistently achieved the lowest control overhead, which eventually decreased the energy consumption of the nodes to prolong the network lifetime. Moreover, the low traffic in dense networks decreases the service invocations delay, and makes the solution more scalable. The grouping mechanism localises the traffic, which increases the energy efficiency while improving the scalability. In summary, the experiments demonstrate the benefit of using TRENDY and its techniques in terms of increased energy efficiency and network lifetime, reduced control overhead, better scalability and optimised service invocation time.

The dream of weaving technology into our everyday fabric of life is recently being made possible by advances in ubiquitous computing and sensor technologies. Countless sensors of various sizes have made their way into everyday commercial applications. Many projects aim to explore new ways to utilize these new technologies to aid and interact with the general population. Context-aware systems use available context information to assist users automatically, without explicit user input. By inferring user intent and configuring the system proactively for each user, context-aware systems are an integral part of achieving user-friendly ubiquitous computing environments. <br /><br /> A common issue with building a distributed context-aware system is the need to develop a supporting infrastructure providing features such as storage, distributed messaging, and security, before the real work on processing context information can be done. This thesis proposes a coordination framework that provides an effective common foundation for context-aware systems. The separation between the context-processing logic component and the underlying supporting foundation allows researchers to focus their energy at the context-processing part of the system, instead of spending their time re-inventing the supporting infrastructure. <br /><br /> As part of an ongoing project, Impress, the framework uses the open standard, Jabber, as its communication protocol. The Publish-Subscribe (pubsub) extension to Jabber provides interesting features that match those needed by a context-aware system. The main contribution of this thesis is the design and implementation of a coordination framework, called the Impress Context Store, that provides an effective common foundation for context-aware systems. The separation between the context-processing logic and the underlying supporting foundation allows researchers to focus their energy at the context-processing part of the system, instead of spending their time re-inventing the supporting infrastructure.

The dream of weaving technology into our everyday fabric of life is recently being made possible by advances in ubiquitous computing and sensor technologies. Countless sensors of various sizes have made their way into everyday commercial applications. Many projects aim to explore new ways to utilize these new technologies to aid and interact with the general population. Context-aware systems use available context information to assist users automatically, without explicit user input. By inferring user intent and configuring the system proactively for each user, context-aware systems are an integral part of achieving user-friendly ubiquitous computing environments. <br /><br /> A common issue with building a distributed context-aware system is the need to develop a supporting infrastructure providing features such as storage, distributed messaging, and security, before the real work on processing context information can be done. This thesis proposes a coordination framework that provides an effective common foundation for context-aware systems. The separation between the context-processing logic component and the underlying supporting foundation allows researchers to focus their energy at the context-processing part of the system, instead of spending their time re-inventing the supporting infrastructure. <br /><br /> As part of an ongoing project, Impress, the framework uses the open standard, Jabber, as its communication protocol. The Publish-Subscribe (pubsub) extension to Jabber provides interesting features that match those needed by a context-aware system. The main contribution of this thesis is the design and implementation of a coordination framework, called the Impress Context Store, that provides an effective common foundation for context-aware systems. The separation between the context-processing logic and the underlying supporting foundation allows researchers to focus their energy at the context-processing part of the system, instead of spending their time re-inventing the supporting infrastructure.

Submitted by Fabricia Fialho Reginato (fabriciar) on 2015-07-31T00:41:21Z No. of bitstreams: 1 PauloButtenbender.pdf: 8406961 bytes, checksum: b941b0205ef79f65fae52d594c271fe6 (MD5) / Made available in DSpace on 2015-07-31T00:41:21Z (GMT). No. of bitstreams: 1 PauloButtenbender.pdf: 8406961 bytes, checksum: b941b0205ef79f65fae52d594c271fe6 (MD5) Previous issue date: 2013 / Nenhuma / A internet das coisas tem por objetivo utilizar a infraestrutura existente da internet para conectar sistemas, pessoas e objetos, permitindo um monitoramento e interação contínua. Essa visão está diretamente relacionada aos trabalhos já existentes na área de computação pervasiva. Uma característica comum aos trabalhos de computação pervasiva é que as suas respectivas plataformas são fechadas e exclusivas a um trabalho ou uma instituição e, portanto a aplicação dos conceitos de computação pervasiva exige dos autores uma construção do software de uma forma específica para o domínio de conhecimento onde será aplicado, o que acarreta em pouca ou nenhuma forma de compartilhamento das informações obtidas. Este trabalho tem como objetivo prover uma plataforma para melhorar a comunicação entre ambientes inteligentes e pessoas, utilizando dispositivos móveis como meio de interação e possibilitando a exposição de contextos pela internet para dispositivos inteligentes externos ao ambiente inteligente utilizando a infraestrutura existente de computação na nuvem e a capacidade de compartilhamento de conhecimento através de ontologias. / The main objective of the internet of things is to use the existing internet infrastructure to connect systems, people and objects, allowing constant interaction and monitoring. This vision is directly related to existing research within pervasive computing. A common characteristic among pervasive computing research papers is that usually their respective platforms are closed and build exclusively to a specific objective or for a given institution, and therefore applying pervasive computing concepts usually demand from the authors to develop the software constrained to the knowledge domain where pervasive computing is going to be applied, which incur in few or none ways of sharing information with other projects. The objective of this research is to provide a common platform to enhance the communication between intelligent environments and people, using mobile devices as a way of interaction, allowing user contexts to be exposed in the Internet to intelligent devices which are not contained within the intelligent environment where the user is actually located by using existing cloud computing infrastructure and web standards ontology to share knowledge.