A Computação Pervasiva tem sido tema de diversos trabalhos nos últimos anos. Essa emergente área de pesquisa propõe uma visão de futuro onde serviços computacionais são oferecidos para os usuários através de inúmeros dispositivos espalhados pelo ambiente. Os serviços são disponibilizados, tanto através da infraestrutura existente dos computadores ligados fisicamente à rede quanto através de dispositivos móveis. Esse espalhamento da computação deve acontecer de maneira natural e imperceptível ao usuário. Dados pessoais, programas e arquivos de dados poderão ser acessados de qualquer lugar em qualquer momento. O poder de processamento será um recurso do ambiente, acessado quando necessário, da mesma forma que é hoje a eletricidade. O usuário não precisará ter ciência de qual máquina realiza o processamento necessário às suas aplicações, contanto que o resultado esperado seja obtido. Acredita-se que essa realidade será atingida através da aliança entre áreas de pesquisa como a Computação em Grade, Computação Móvel e a Computação Consciente do Contexto. A Computação Consciente do Contexto busca enriquecer a comunicação entre os seres humanos e os dispositivos computacionais, tornando sua atuação mais eficaz. As aplicações conscientes do contexto conseguem perceber as modificações que ocorrem no ambiente e adaptar seu comportamento ao novo estado. Esse processo pode ser dividido em três etapas: monitoramento, reconhecimento de contexto e adaptação. Na etapa de monitoramento são coletadas, através de sensores, informações sobre o ambiente. Essas informações, entretanto, são geralmente, de baixo nível de abstração e, portanto, dificilmente usadas diretamente por aplicações. A etapa de reconhecimento de contexto relaciona os dados obtidos do ambiente e transforma-os para que possam ser úteis às aplicações no processo de escolha do comportamento mais adequado à cada circunstância, habilitando a etapa de adaptação a efetivar a transformação do comportamento da aplicação de acordo com a nova situação do ambiente. Este trabalho propõe um servidor de contexto chamado MultiS que tem como objetivo a resolução dos problemas relativos à etapa de reconhecimento de contexto: a produção de dado de contexto baseado em informações de diversos sensores e a capacidade de reagir a modificações no ambiente. Também é proposta uma linguagem para composição de dados do contexto chamada CD-XML utilizada pelas aplicações para descrever ao servidor de contexto os dados aos quais elas são sensíveis. / The Pervasive Computing has been studied on several papers in the last years. This emergent research area presents a vision of future where computational services will be available through uncountable devices scattered across the environment. This service network will be exposed to the users by both traditional wired computers and mobile devices. This distribution of the computing is going to happen smoothly and transparently to the users. Personal data, computer programs, and data files will be available anywhere, anytime. The processing power will be an environment resource and will be accessed whenever needed, in the same way which is the electricity nowadays. The users will no longer need to worry about where their program is being executed, as long as he gets the needed result. The ISAM group believes that this new reality will be achieved through the alliance of research areas such as Grid Computing, Mobile Computing and Context-Aware Computing. The Context-Aware Computing aims to enrich the communication between human being and computer devices. Context-aware applications are capable of recognize the changes on the environment and adapt its own behavior to the new context state. This process can be divided in tree steps: monitoring, context recognition and adaptation. On the monitoring layer, environment information is collected from sensors. Those sensors, however, usually return only low level information, which is hardly used by the applications on its original form. The context recognition layer processes the data acquired from the context and transforms into information aimed to be useful to the adaptation process. With that information the adaptation system can identify the correct behavior for the application on each different context situation. This dissertation propose a context server named MultiS, which target is to solve the problems related to context recognition layer: the production of new context data based on the information of several sensors and the capability of react to changes on the environment. It also presents a new programming language for composition of contextual information, named CD-XML. This language is used by the context-aware applications to communicate to the context server describing which information the application is sensible to.

abstract: As people age, the desire to grow old independently and in place becomes larger and takes greater importance in their lives. Successful aging involves the physical, mental and social well-being of an individual. To enable successful aging of older adults, it is necessary for them to perform both activities of daily living (ADL) and instrumental activities of daily living (IADL). Embedded assessment has made it possible to assess an individual's functional ability in-place, however the success of any technology depends largely on the user than the technology itself. Previous researches in in-situ functional assessment systems have heavily focused on the technology rather than on the user. This dissertation takes a user-centric approach to this problem by trying to identify the design and technical challenges of deploying and using a functional assessment system in the real world. To investigate this line of research, a case study was conducted with 4 older adults in their homes, interviews were conducted with 8 caregivers and a controlled lab experiment was conducted with 8 young healthy adults at ASU, to test the sensors. This methodology provides a significant opportunity to advance the scientific field by expanding the present focus on IADL task performance to an integrated assessment of ADL and IADL task performance. Doing so would not only be more effective in identifying functional decline but could also provide a more comprehensive assessment of individuals' functional abilities with independence and also providing the caregivers with much needed respite. The controlled lab study tested the sensors embedded into daily objects and found them to be reliable, and efficient. Short term exploratory case studies with healthy older adults revealed the challenges associated with design and technical aspects of the current system, while inductive analysis performed on interviews with caregivers helped to generate central themes on which future functional assessment systems need to be designed and built. The key central themes were a) focus on design / user experience, b) consider user's characteristics, personality, behavior and functional ability, c) provide support for independence, and d) adapt to individual user's needs. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2015

A Computação Pervasiva tem sido tema de diversos trabalhos nos últimos anos. Essa emergente área de pesquisa propõe uma visão de futuro onde serviços computacionais são oferecidos para os usuários através de inúmeros dispositivos espalhados pelo ambiente. Os serviços são disponibilizados, tanto através da infraestrutura existente dos computadores ligados fisicamente à rede quanto através de dispositivos móveis. Esse espalhamento da computação deve acontecer de maneira natural e imperceptível ao usuário. Dados pessoais, programas e arquivos de dados poderão ser acessados de qualquer lugar em qualquer momento. O poder de processamento será um recurso do ambiente, acessado quando necessário, da mesma forma que é hoje a eletricidade. O usuário não precisará ter ciência de qual máquina realiza o processamento necessário às suas aplicações, contanto que o resultado esperado seja obtido. Acredita-se que essa realidade será atingida através da aliança entre áreas de pesquisa como a Computação em Grade, Computação Móvel e a Computação Consciente do Contexto. A Computação Consciente do Contexto busca enriquecer a comunicação entre os seres humanos e os dispositivos computacionais, tornando sua atuação mais eficaz. As aplicações conscientes do contexto conseguem perceber as modificações que ocorrem no ambiente e adaptar seu comportamento ao novo estado. Esse processo pode ser dividido em três etapas: monitoramento, reconhecimento de contexto e adaptação. Na etapa de monitoramento são coletadas, através de sensores, informações sobre o ambiente. Essas informações, entretanto, são geralmente, de baixo nível de abstração e, portanto, dificilmente usadas diretamente por aplicações. A etapa de reconhecimento de contexto relaciona os dados obtidos do ambiente e transforma-os para que possam ser úteis às aplicações no processo de escolha do comportamento mais adequado à cada circunstância, habilitando a etapa de adaptação a efetivar a transformação do comportamento da aplicação de acordo com a nova situação do ambiente. Este trabalho propõe um servidor de contexto chamado MultiS que tem como objetivo a resolução dos problemas relativos à etapa de reconhecimento de contexto: a produção de dado de contexto baseado em informações de diversos sensores e a capacidade de reagir a modificações no ambiente. Também é proposta uma linguagem para composição de dados do contexto chamada CD-XML utilizada pelas aplicações para descrever ao servidor de contexto os dados aos quais elas são sensíveis. / The Pervasive Computing has been studied on several papers in the last years. This emergent research area presents a vision of future where computational services will be available through uncountable devices scattered across the environment. This service network will be exposed to the users by both traditional wired computers and mobile devices. This distribution of the computing is going to happen smoothly and transparently to the users. Personal data, computer programs, and data files will be available anywhere, anytime. The processing power will be an environment resource and will be accessed whenever needed, in the same way which is the electricity nowadays. The users will no longer need to worry about where their program is being executed, as long as he gets the needed result. The ISAM group believes that this new reality will be achieved through the alliance of research areas such as Grid Computing, Mobile Computing and Context-Aware Computing. The Context-Aware Computing aims to enrich the communication between human being and computer devices. Context-aware applications are capable of recognize the changes on the environment and adapt its own behavior to the new context state. This process can be divided in tree steps: monitoring, context recognition and adaptation. On the monitoring layer, environment information is collected from sensors. Those sensors, however, usually return only low level information, which is hardly used by the applications on its original form. The context recognition layer processes the data acquired from the context and transforms into information aimed to be useful to the adaptation process. With that information the adaptation system can identify the correct behavior for the application on each different context situation. This dissertation propose a context server named MultiS, which target is to solve the problems related to context recognition layer: the production of new context data based on the information of several sensors and the capability of react to changes on the environment. It also presents a new programming language for composition of contextual information, named CD-XML. This language is used by the context-aware applications to communicate to the context server describing which information the application is sensible to.

A Computação Pervasiva tem sido tema de diversos trabalhos nos últimos anos. Essa emergente área de pesquisa propõe uma visão de futuro onde serviços computacionais são oferecidos para os usuários através de inúmeros dispositivos espalhados pelo ambiente. Os serviços são disponibilizados, tanto através da infraestrutura existente dos computadores ligados fisicamente à rede quanto através de dispositivos móveis. Esse espalhamento da computação deve acontecer de maneira natural e imperceptível ao usuário. Dados pessoais, programas e arquivos de dados poderão ser acessados de qualquer lugar em qualquer momento. O poder de processamento será um recurso do ambiente, acessado quando necessário, da mesma forma que é hoje a eletricidade. O usuário não precisará ter ciência de qual máquina realiza o processamento necessário às suas aplicações, contanto que o resultado esperado seja obtido. Acredita-se que essa realidade será atingida através da aliança entre áreas de pesquisa como a Computação em Grade, Computação Móvel e a Computação Consciente do Contexto. A Computação Consciente do Contexto busca enriquecer a comunicação entre os seres humanos e os dispositivos computacionais, tornando sua atuação mais eficaz. As aplicações conscientes do contexto conseguem perceber as modificações que ocorrem no ambiente e adaptar seu comportamento ao novo estado. Esse processo pode ser dividido em três etapas: monitoramento, reconhecimento de contexto e adaptação. Na etapa de monitoramento são coletadas, através de sensores, informações sobre o ambiente. Essas informações, entretanto, são geralmente, de baixo nível de abstração e, portanto, dificilmente usadas diretamente por aplicações. A etapa de reconhecimento de contexto relaciona os dados obtidos do ambiente e transforma-os para que possam ser úteis às aplicações no processo de escolha do comportamento mais adequado à cada circunstância, habilitando a etapa de adaptação a efetivar a transformação do comportamento da aplicação de acordo com a nova situação do ambiente. Este trabalho propõe um servidor de contexto chamado MultiS que tem como objetivo a resolução dos problemas relativos à etapa de reconhecimento de contexto: a produção de dado de contexto baseado em informações de diversos sensores e a capacidade de reagir a modificações no ambiente. Também é proposta uma linguagem para composição de dados do contexto chamada CD-XML utilizada pelas aplicações para descrever ao servidor de contexto os dados aos quais elas são sensíveis. / The Pervasive Computing has been studied on several papers in the last years. This emergent research area presents a vision of future where computational services will be available through uncountable devices scattered across the environment. This service network will be exposed to the users by both traditional wired computers and mobile devices. This distribution of the computing is going to happen smoothly and transparently to the users. Personal data, computer programs, and data files will be available anywhere, anytime. The processing power will be an environment resource and will be accessed whenever needed, in the same way which is the electricity nowadays. The users will no longer need to worry about where their program is being executed, as long as he gets the needed result. The ISAM group believes that this new reality will be achieved through the alliance of research areas such as Grid Computing, Mobile Computing and Context-Aware Computing. The Context-Aware Computing aims to enrich the communication between human being and computer devices. Context-aware applications are capable of recognize the changes on the environment and adapt its own behavior to the new context state. This process can be divided in tree steps: monitoring, context recognition and adaptation. On the monitoring layer, environment information is collected from sensors. Those sensors, however, usually return only low level information, which is hardly used by the applications on its original form. The context recognition layer processes the data acquired from the context and transforms into information aimed to be useful to the adaptation process. With that information the adaptation system can identify the correct behavior for the application on each different context situation. This dissertation propose a context server named MultiS, which target is to solve the problems related to context recognition layer: the production of new context data based on the information of several sensors and the capability of react to changes on the environment. It also presents a new programming language for composition of contextual information, named CD-XML. This language is used by the context-aware applications to communicate to the context server describing which information the application is sensible to.

Context-aware computing requires software that can adapt to changes in context. When contextual circumstances trigger multiple adaptations, software must also understand the relationships between these adaptations and react according to the rules governing these relationships. Adaptable software needs a means to establish and interpret these rules in order to avoid any undesirable and potentially catastrophic conflicts. This dissertation designs and implements the Adaptation Rules Management API (ArmAPI). ArmAPI has been demonstrated to work with a Context-Oriented Programming variation for Java called ContextJ* to execute conflict-free adaptations in two software applications. ArmAPI allows programmers to define relationship types between adaptations, and transfers these definitions to Prolog facts and rules. The Prolog engine, encapsulated within ArmAPI, then works with imperative algorithms to determine the appropriate adaptations to execute based on the current set of facts, rules, and contextual circumstances. Context represents all of the conditions for all of the entities known to an observing device. In any environment, context represents a large amount of data that can influence a multitude of conflicting adaptations. This research provides an incremental step towards overcoming the problem of adaptation conflict by constructing an API that considers the relationship types of inclusion, exclusion, ordering, conditional dependency, and independence. The API has been validated via two prototypes that provide typical scenarios.

This dissertation is composed of research studies that contribute to three research areas including social context-aware computing, internal context-aware computing, and human behavioral data mining. In social context-aware computing, four studies are conducted. First, mobile phone user calling behavioral patterns are characterized in forms of randomness level where relationships among them are then identified. Next, a study is conducted to investigate the relationship between the calling behavior and organizational groups. Third, a method is presented to quantitatively define mobile social closeness and social groups, which are then used to identify social group sizes and scaling ratio. Last, based on the mobile social grouping framework, the significant role of social ties in communication patterns is revealed. In internal context-aware computing, two studies are conducted where the notions of internal context are intention and situation. For intentional context, the goal is to sense the intention of the user in placing calls. A model is thus presented for predicting future calls envisaged as a call predicted list (CPL), which makes use of call history to build a probabilistic model of calling behavior. As an incoming call predictor, CPL is a list of numbers/contacts that are the most likely to be the callers within the next hour(s), which is useful for scheduling and daily planning. As an outgoing call predictor, CPL is generated as a list of numbers/contacts that are the most likely to be dialed when the user attempts to make an outgoing call (e.g., by flipping open or unlocking the phone). This feature helps save time from having to search through a lengthy phone book. For situational context, a model is presented for sensing the user's situation (e.g., in a library, driving a car, etc.) based on embedded sensors. The sensed context is then used to switch the phone into a suitable alert mode accordingly (e.g., vibrate mode while in a library, handsfree mode while driving, etc.). Inferring (social and internal) context introduces a challenging research problem in human behavioral data mining. Context is determined by the current state of mind (internal), relationship (social), and surroundings (physical). Thus, the current state of context is important and can be derived from the recent behavior and pattern. In data mining research area, therefore, two frameworks are developed for detecting recent patterns, where one is a model-driven approach and the other is a data-driven approach.

Exploiting context-aware environments, where sensors scattered in a environment update presence servers to indicate the environmental changes can be used to enable new services. Such systems have become feasible both in terms of technical di±culties and their cost. A current focus in this area of research is how a context-aware system should be designed so that it reduces both the cost and complexity of the infrastructure, but still provides the desired services. One of the key components of many context-aware systems is location sensing, because a user's location is one of the most used elements of information in context-aware services. In this paper, we address cost e®ective location services by utilizing measurements of WLAN signal strength. We derive from these measurements an estimate of a device's location, and make this location information available via a SIP Presence User Agent, thus making location information readily available to services that might wish to use this information - while hiding details of how this information is acquired from these services. / Genom att utnyttja kontextmedvetna miljöer, där sensorer i en miljö uppdaterar närvarande servrar med information omändringar i omgivningen, så kan man öppna upp vägar för nya tjänster. Sådana system har blivit utförbara bade när det gäller tekniska svarigheter och deras kostnader. Inom forskning som rör sådana här system ägnas mycket uppmärksamhetåt hur en kontextmedveten miljö borde designas för att minimera både kostnaden och komplexiteten av infrastrukturen, men fortfarande tillhandahålla den önskade tjänsten. En av huvudkomponenterna i många kontextmedvetna system är platsuppfattning, eftersom en användares position är en av de mest använda elementen av information i kontextmedvetna tjänster. I den här uppsatsen ägnar vi oss åt kostnadseffektiva platstjänster genom att mäta signalstyrkan av ett WLAN. Genom dessa mätningar uppskattar vi en enhets position och gör denna information tillgänglig via en SIP Presence User Agent, och gör på så vis platsinformationen tillgänglig för tjänster som kan vilja ha den { utan att avslöja detaljer om hur informationen har skaffats.

A identificação de características que sejam importantes sobre um dado estudante durante o processo de ensino-aprendizagem tem sido alvo de muitos estudos nos últimos tempos. Docentes, coordenadores e pedagogos têm defendido que cada indivíduo possui características particulares e importantes dentro do processo de desenvolvimento do conhecimento. A necessidade de adaptar as estratégias de ensino de acordo com as preferências do aprendiz é uma realidade dentro das salas de aula, sejam estas presenciais ou virtuais. Porém, isto não significa que numa sala de aula deva haver criação de um método para cada aluno, mas sim que se aponte qual a melhor forma de interação para cada um deles construindo grupos de aprendizes com características comuns. Trabalhando desta forma se torna possível identificar perfis de aprendizes dentro de um conjunto de estudantes, possibilitando que se possa trabalhar com conteúdos e ambientes de aprendizagem mais adequados aos aprendizes.O objetivo deste trabalho é apresentar a arquitetura de um sistema que possibilita a criação de cenários de aprendizagem baseados no perfil do aluno. O docente deve indicar as características que devem ser observadas durante as interações do aprendiz em um dado ambiente de aprendizagem eletrônica. Estas características serão modeladas como informações de contexto, permitindo que os pontos definidos como observáveis sejam organizados e modelados de forma a facilitar a monitoração das interações. A classificação do aluno em um determinando tipo de perfil de aprendizagem, previamente definido pelo docente, é realizado considerando-se as informações sobre o contexto da interação e os tipos de perfis de aprendizagem. Para que seja possível construir os cenários de aprendizagem considerando o perfil do aluno este trabalho propõe criar um relacionamento entre os tipos de perfis de aprendizagem e as estratégias de ensino através das categorias descritoras dos objetos de aprendizagem. / The identification of characteristics of a given student that are important during the teachinglearning process has been the focus of numerous studies in recent years. Teachers, coordinators and pedagogues have defended the notion that each individual presents particular and important characteristics in the developing knowledge process. The need to adapt teaching strategies to the student\'s preferences is a reality in classrooms, being physical or virtual classrooms. However, this does not mean that a method should be created for each student in a classroom, but that the best form of interaction for each of them be identified, building groups of learners with common characteristics. Working in this way makes it possible to identify learner profiles within a group of students, allowing one to work with learning contents and environments more suited to the learners. The objective of this work is to present the architecture of a system that allows for the creation of learning scenarios based on the studen profile. The teacher should point out the features which may be observed during the student interaction in a given e-elearning environment. These features are designed as context information, allowing defined observation points to be organized and modeled for facilitating the monitoring of interactions. The student classification in a given learning profile type, defined previously by the teacher, is realized considering information about the context of interaction and the learning profile types. For the learning environment to build the learning scenarios according to the student profile, this work proposes to create a relationship between the learning profile types and the teaching strategies through the description of learning objects categories.

Master of Philosophy (Architecture) / Context-aware computing is a mobile computing paradigm in which applications can discover, use, and take advantage of contextual information, such as the location, tasks and preferences of the user, in order to adapt their behaviour in response to changing operating environments and user requirements. A problem that arises is the inability to respond to contextual information that cannot be classified into any known context. Many context-aware applications require all discovered contextual information to exactly match a type of context, otherwise the application will not react responsively. The ability to learn and recall contexts based on the contextual information discovered has not been very well addressed by previous context-aware applications and research. The aim of this thesis is to develop a component middleware technology for mobile computing devices for the discovery and capture of contextual information, using the situated reasoning concept of constructive memory. The research contribution of this thesis lies in developing a modified architecture for context-aware systems, using a constructive memory model as a way to learn and recall contexts from previous experiences and application interactions. Using a constructive memory model, previous experiences can be induced to construct potential contexts, given a small amount of learning and interaction. The learning process is able to map the many variations of contextual information currently discovered by the user with a predicted type of context based on what the application has stored and seen previously. It only requires a small amount of contextual information to predict a context, something common context-aware systems lack, as they require all information before a type of context is assigned. Additionally, some mechanism to reason about the contextual information being discovered from past application interactions will be beneficial to induce contexts for future experiences.

This thesis describes research on methods for Ubiquitous/Pervasive Computing to better suit users in an Intelligent Environment. The approach is to create and equip a computing environment, such as our Active Office, with technologies that can identify user needs and meet these need in a timely, efficient and unobtrusive manner.¶ The critical issues in the Intelligent Environment are how to enable transparent, distributed computing to allow continued operation across changing circumstances and how to exploit the changing environment so that it is aware of the context of user location, the collection of nearby people and objects, accessible devices and changes to those objects over time.¶ Since the Intelligent Environment is an environment with rapid and rich computing processing, the distributed context processing architecture (DiCPA) was developed to manage and respond to rapidly changing aggregation of sensor data. This architecture is a scalable distributed context processing architecture that provides: 1. continued operation across changing circumstances for users, 2. the collection of nearby people and objects, 3. accessible devices and 4. the changes to those objects over time in the environment. The DiCPA approach focuses on how the Intelligent Environment provides context information for user location, user mobility and the user activity model. Users are assumed mobile within the Intelligent Environment and can rapidly change their access to relevant information and the availability of communications and computational resources.¶ Context-Aware Computing is a new approach in software engineering for Intelligent Environment. It is an approach in the design and construction of a context-aware application that exploits rapid changes in access to relevant information and the availability of communication and computing resources in the mobile computing environment. The goal of Context-Aware Computing is to make user interaction with the computer easier in the smart environment where technology is spread throughout (pervasive), computers are everywhere at the same time (ubiquitous) and technology is embedded (ambient) in the environment. Context-aware applications need not be difficult, tedious or require the acquisition of new skills on the part of the user. They should be safe, easy, simple to use and should enable new functionality without the need to learn new technology. They should provide relevant information and a simple way for a user to manage.¶ The Intelligent Environment requires a context-aware application to improve its efficiency and to increase productivity and enjoyment for the user. The context awareness mechanism has four fundamental cores i.e. identity (who), activity (what), location (where) and timestamp (when). Based on DiCPA architecture, the model of user location (where), user mobility (where), user activity (what) and Intelligent Environment response (what) were developed. Prototypes were also developed to proof the Context-Aware Computing concept in the Intelligent Environment.¶ An Intelligent Environment uses the multi-disciplinary area of Context-Aware Computing, which combines technology, computer systems, models and reasoning, social aspects, and user support. A “good quality” project for Context-Aware Computing requires core content and provides iterative evaluation processes, which has two types of iteration: design and product iteration of the evaluation. The aim of the development of an evaluation program in Context-Aware Computing is to determine what to test, how to test and the appropriate metrics to use. This work presents the metrics for a good quality project in the Context-Aware Computing area, which is followed by the evaluation of the prototypes of this work.