FutureWare: Designing a Middleware for Anticipatory Mobile Computing

Ubiquitous computing is moving from context-awareness to context-prediction. In order to build truly anticipatory systems developers have to deal with many challenges, from multimodal sensing to modeling context from sensed data, and, when necessary, coordinating multiple predictive models across devices. Novel expressive programming interfaces and paradigms are needed for this new class of mobile and ubiquitous applications. In this paper we present FutureWare, a middleware for seamless development of mobile applications that rely on context prediction. FutureWare exposes an expressive API to lift the burden of mobile sensing, individual and group behavior modeling, and future context querying, from an application developer. We implement FutureWare as an Android library, and through a scenario-based testing and a demo app we show that it represents an efficient way of supporting anticipatory applications, reducing the necessary coding effort by two orders of magnitude

Publicidade personalizada e privacidade dos dados no Facebook: o caso de Portugal

The evolution of the technological world has allowed companies and consumers to be increasingly connected, especially due to social networks. Along with the development of social networks, personalised advertising has grown exponentially, becoming the most effective advertising strategy as it allows companies to interact with consumers in a customised way and offer products and services that are in accordance with their profiles. However, although personalised advertising offers benefits to both companies and consumers, in recent years the concern about data privacy has increased. Thus, this research aims to understand the gap existing between personalised advertising and data privacy concerns, since users want to receive ads with high predictive ability of their needs, however the collection and use of their data causes insecurity in relation to their privacy. As a way to achieve this objective, a mixed-methods approach was used by creating a questionnaire based on the existing literature. A total of 583 valid responses were collected and analysed using IBM SPSS Statistics version 28 software for quantitative data analysis and NVivo Software version 12 for qualitative data analysis The results allowed the support of three research hypotheses and the rejection of four hypotheses. The conclusions obtained indicate that personalised advertising causes data privacy concerns and through the thematic analysis performed to one of the qualitative questions it was possible to determine 17 situations in which respondents stated that this type of advertising threatened their privacy. Furthermore, the statistically significant result of the chi-square test suggests that consumers seek to protect their data on Facebook, not supporting the privacy paradox. Furthermore, this research suggests the existence of a relationship between personalised advertising and cyber-paranoia, as consumers believe they are constantly being ‘listened to’ through their mobile phone’s microphone and that their conversations are used for delivering personalised advertisements, while also believing that everything they do on the Internet is monitored and used for advertising purposes. Finally, since no literature was found on cyber-paranoia and personalised advertising, it can be considered that this study presents an innovative contribution. However, since this investigation is an exploratory study, there is a need for further literature on this subject.A evolução do mundo tecnológico permitiu que as empresas e os consumidores estivessem cada vez mais conectados, especialmente devido às redes sociais. A par do desenvolvimento das redes sociais, a publicidade personalizada cresceu exponencialmente, tornando-se na estratégia de publicidade mais eficaz pois permite às empresas interagir com os consumidores de uma forma customizada e oferecer produtos e serviços que estejam de acordo com os seus perfis. No entanto, apesar de a publicidade personalizada oferecer benefícios tanto para as empresas como para os consumidores, nos últimos anos verificou-se o aumento da preocupação com a privacidade dos dados. Assim, esta investigação tem como objetivo compreender a lacuna que existe entre a publicidade personalizada e a preocupação com a privacidade dos dados, pois os utilizadores querem receber anúncios com elevada capacidade de previsão das suas necessidades, no entanto a recolha e a utilização dos seus dados causa insegurança em relação à sua privacidade. Como forma a atingir este objetivo, foi utilizado um método de investigação misto através da criação de um questionário baseado na literatura existente. Um total de 583 respostas válidas foram recolhidas e analisadas utilizando o software IBM SPSS Statistics versão 28 para a análise dos dados quantitativos e o Software NVivo versão 12 para a análise dos dados qualitativos. Os resultados permitiram o suporte de três hipóteses de investigação e a rejeição de quatro hipóteses. As conclusões obtidas indicam que a publicidade personalizada causa preocupação com a privacidade dos dados, sendo que através da análise temática realizada a uma das perguntas qualitativas foi possível determinar 17 situações em que os inquiridos afirmaram que este tipo de publicidade ameaçava a sua privacidade. Além disso, o resultado estatisticamente significativo do teste qui-quadrado sugere que os consumidores têm comportamentos que visam proteger os seus dados no Facebook, não suportando o paradoxo da privacidade. Ademais, esta investigação sugere a existência de uma relação entre a publicidade personalizada e a ciberparanoia visto que os consumidores acreditam que estão constantemente a ser ‘ouvidos’ através do microfone do seu telemóvel e que as suas conversas são utilizadas para a criação de anúncios personalizados, considerando também que tudo o que fazem na Internet é monitorizado e usado para fins publicitários. Por fim, uma vez que não foi encontrada literatura sobre a publicidade personalizada e a ciberparanoia, pode-se considerar que este estudo apresenta um contributo inovador. Contudo, sendo esta investigação um estudo exploratório, é necessário haver mais literatura sobre este tema.Mestrado em Gestã

Virtual workplaces : when metaphors breakdown

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1998.Includes bibliographical references (leaves 79-81).Our model of work is shaped by the places we choose to work and the tools we choose to work with. As we introduce new technologies and build new environments our model is changing. Today's virtual workplaces are grounded in models of work that have been reformed from our experiences using current technology in physical workspace. However we are discovering opportunities and possibilities for work in collaborative, virtual environments that question physical models. Emerging patterns of distributed collaboration in persistent virtual environments are changing the way we work in time and space, recasting our notion of workplace. Virtual workplaces are interpreted and experienced through metaphors that describe a space of potential for work occurrences. Through the lens of metaphors, this research focuses on breakdowns between collaborative work and the environment in which work occurs. If what we understand and predict is based on what we already know, then by examining the breakdowns between design and use of collaborative environments we can illuminate the space of possibilities for collaborative work.by Thomas W.I. Gallemore.M.S

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201