Computing is increasingly pervading the activities of our everyday lives: at work, at home, and out on the town. When designing these pervasive systems there is a need to better understand and incorporate the context of use and yet there are limited empirical investigations into what constitutes this context. The user’s physical and social situation is an important part of their context when operating in an urban environment and thus needs to be understood and included in the interaction design of context-aware pervasive computing. This thesis has combined ideas from human computer interaction (HCI) and architecture to investigate indexicality in interface design as an instrument for incorporating physical and social context of the built environment into context-aware pervasive computing. Indexicality in interface design is a new approach to designing HCI for pervasive computing that relies on knowledge of current context to implicitly communicate between system and user. It reduces the amount of information that needs to be explicitly displayed in the interface while maintaining the usefulness and understandability of the communication.

Thesis (Ph.D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2008. / Committee Chair: Abler, Randal T.; Committee Member: Copeland, John A.; Committee Member: Haas, Kevin; Committee Member: Moore II, Elliot; Committee Member: Owen III, Henry L.

Thesis (Ph.D.)--Computing, Georgia Institute of Technology, 2009. / Committee Chair: Abowd, Gregory; Committee Member: Edwards, Keith; Committee Member: Grinter, Rebecca; Committee Member: LaMarca, Anthony; Committee Member: Starner, Thad.

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.