Spatial representation of public displays networks

Dissertação de mestrado integrado em Engenharia de ComunicaçõesEste trabalho faz parte do projeto Europeu Pd-Net e tem como objectivo identificar e abordar os desafios tecnológicos e de investigação relacionados com a criação de redes, em larga escala, de ecrãs públicos e sensores associados. O aparecimento das redes de larga escala de ecrãs públicos irá representar uma mudança significativa no modo como pensamos sobre a disseminação de informação em espaços públicos e criará uma nova área de investigação, as bases para um novo meio de comunicação e novas oportunidades de negócio. De igual modo, é esperada uma mudança nos espaços públicos para espaços inteligentes que podem ser ajustados para refletir as esperanças, aspirações e interesses dos ocupantes que utilizam o conteúdo e as aplicações criadas em qualquer parte da rede. Um dos pontos-chave da rede de ecrãs públicos é a possibilidade de endereçar a rede como um todo e focar nas relações espaciais entre os ecrãs.This work is part of Pd-Net, a European project that aims to explore the scientific challenges and new technologies required to enable the emergence of large scale networks of pervasive public displays and associated sensors that are open to applications and content from many sources. The emergence of such pervasive display networks would represent a radical transformation in the way we think about information dissemination in public spaces and will create a new research area, provide the foundations for a new communication medium and new business opportunities. In the same way, it is expected a change from public spaces – from today’s environments in which information is pushed to passers-by in the form of adverts – to spaces that can utilise ambient intelligence to be tailored to reflect the hopes, aspirations and interests of its occupants using content and applications created anywhere in a global network. One of the interesting features of pervasive displays networks is the possibility to address the network as a whole and to focus on the spatial relations between displays

Geographical places as a personalisation element: extracting profiles from human activities and services of visited places in mobility logs

Collecting personal mobility traces of individuals is currently applicable on a large scale due to the popularity of position-aware mobile phones. Statistical analysis of GPS data streams, collected with a mobile phone, can reveal several interesting measures such as the most frequently visited geographical places by some individual. Applying probabilistic models to such data sets can predict the next place to visit, and when. Several practical applications can utilise the results of such analysis. Current state of the art, however, is limited in terms of the qualitative analysis of personal mobility logs. Without explicit user-interactions, not much semantics can be inferred from a GPS log. This work proposes the utilisation of the common human activities and services provided at certain place types to extract semantically rich profiles from personal mobility logs. The resulting profiles include spatial, temporal and generic thematic description of a user. The work introduces several pre-processing methods for GPS data streams, collected with personal mobile devices, which improved the quality of the place extraction process from GPS logs. The thesis also introduces a method for extracting place semantics from multiple data sources. A textual corpus of functional descriptions of human activities and services associated with certain geographic place types is analysed to identify the frequent linguistic patterns used to describe such terms. The patterns found are then matched against multiple textual data sources of place semantics, to extract such terms, for a collection of place types. The results were evaluated in comparison to an equivalent expert ontology, as well as to semantics collected from the general public. Finally, the work proposes a model for the resulting profiles, the necessary algorithms to build and utilise such profiles, along with an encoding mark-up language. A simulated mobile application was developed to show the usability and for evaluation of the resulting profiles