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- Special issue on advances in multimedia interaction and visualizationPublication . FRANCESE, Rita; Banissi, Ebad; Datia, Nuno; Risi, MicheleInformation Visualization is the field of study concerned with the development of methods for transforming abstract, complex data into visual representations in order to make that data more easily communicable and understandable. Technological advances enable information visualization in many areas, such as Visual Analytics, social media, geo-sociology, health, business, security and more. Interactivity and visualization increase the engagement with users, as they place them at the core of processes of access, dialogue, and relation with data providing visualization models for easy-to-use interactive systems. The use of interactive visualization in multimedia provides a powerful means for investigating, exploring, and imagining new communication modalities we will use in the near future. This special issue collected emerging contributions in the area of multimedia interaction and its applications for information visualization with different types of data. It includes a selection of the best papers presented at iV 2019, the 23rd International Conference on Information Visualizations. The conference took place in two different locations: 02–05 July 2019 in Paris (France) and 16–19 July 2019 in Adelaide, Australia. Participants included 70+ researchers from more than 23 countries.
- Plataforma FIWARE para monitorização de poluiçãoPublication . Pedroso, Ivo; Datia, Nuno; Cruz, NunoA poluição atmosférica afeta a saúde da população e é um factor de aumento da taxa de mortalidade. Entidades responsáveis pela gestão de grandes cidades procuram soluções que permitam monitorizar em tempo real os níveis de poluição em grandes áreas urbanas. No entanto, as soluções existentes para a monitorização de poluição são proprietárias ou não apresentam um grau de maturidade de integração, que facilite a expansão de uma rede de sensores com custos baixos de manutenção. Neste trabalho apresenta-se uma arquitectura da solução e uma implementação de referência, para uma plataforma distribuída de código aberto, que permita gerir uma rede de sensores. Esta plataforma permite acoplar e desacoplar, em tempo real, os sensores de poluição atmosférica, armazenar o histórico de medições registadas, agregar dados e disponibilizar um dashboard que permita posterior análise da informação armazenada. A arquitetura de solução é disponibilizada em contentores de execução virtual, recorrendo a diversos componentes do quadro de referência FIWARE e a componentes desenvolvidos à medida. O meio de comunicação usado na transmissão de dados entre os sensores e a plataforma, é uma rede baseada em LoRaWAN, a qual permite comunicações sem fios de longo alcance e de baixa potência. Foi assim selecionada a The Things Network (TTN), uma rede pública que implementa o protocolo LoRaWAN, que permite a comunicação entre sensores e a plataforma proposta. Foi selecionado o protocolo MQTT como forma de comunicação entre a plataforma proposta e a TTN. A plataforma proposta disponibiliza uma interface com o utilizador, implementada como um dashboard acessível a partir de um navegador, onde é possível observar a localização dos sensores registados sobre um mapa, a informação sobre seu estado operacional, bem como a informação sobre as medições observadas. Todos os componentes da plataforma são parametrizados através de um único ficheiro de configuração, que, através de um processo de automação, possibilita a instalação e execução da plataforma através de um único comando.
- Architecture for the 15-Minute CityPublication . Melo, Leonardo; Cruz, Nuno; Datia, NunoFinding a new home in a large city has increasingly become more complex, as people are concerned with not only the estate itself but also with its surroundings. The 15-Minute City concept, thinks of cities as a way to ensure that their residents within a 15-minute radius, can fulfill six essential functions: home, work, commerce, health care, education, and entertainment; which varies according to a chosen travel mode. To help people find properties that would fit them according to this concept, we have built an application that aims to provide an intuitive user interface that guides the user through the important decision of buying a house. To present relevant information to the user, we gathered information from three relevant sources, each with its unique challenges. The first source is estate data, extracted from the websites of local real estate agencies; second, city data, with points of interest relevant to the six essential functions mentioned previously; and at last, the user data provided by the user itself through our profile system which lets us understand his needs. System-wise, we built a reliable application following the microservices architecture guidelines, which future proofs our solution by segregating each part of the project and allowing it to scale easily, development and feature wise. The application scrapes, ingests, transforms and stores data regularly. The complete infrastructure is containerized using Docker and orchestrated by Kubernetes. With this application, we provided a scalable solution that allows users to select the best real estate taking into consideration the surrounding environment, tailored to their day-to-day needs, something that, as far as we know, is a novelty on real estate agency websites.
- Browsing multidimensional visual entitiesPublication . Aniceto, Miguel; Moura Pires, João; Datia, Nuno; Afonso, Ana PaulaThe field of Information Visualization seeks to identify the general principles of visualization, and makes use of these principles to propose new forms of visualization for specific types of data. Included in these different data types, it was identified a data type which was not thoroughly explored. The notion of entities where each entity is composed by different attributes, and one of these attributes is composed by one picture which invokes a strong feeling of familiarity to the user. The information that we are attempting to visualize is the most basic type of data structure, a table, where the number of entities to visualize should be higher than we can humanely count, yet smaller than a few thousands. In the field of visualization we identified a niche where the main focus is the image, and despite that it has a vast number of applicable scenarios, it hadn't been properly explored. One of the major attempts at doing so, was by Microsoft Live Labs and it demonstrated limitations that will be addressed by our approach. In order to evaluate the proposed forms of visualization they will be applied and evaluated with the Deloitte Portugal organizational case-study.
- Temporal patterns of TV watching for Portuguese viewersPublication . Datia, Nuno; Moura-Pires, J.; Cardoso, A.; Pinheiro Pita, Helder JorgeAudiometer systems provide enormous amounts of detailed TV watching data. Several relevant and interdependent factors may influence TV viewers' behavior. In this work we focus on the time factor and derive Temporal Patterns of TV watching, based on panel data. Clustering base attributes are originated from 1440 binary minute-related attributes, capturing the TV watching status (watch/not watch). Since there are around 2500 panel viewers a data reduction procedure is first performed. K-Means algorithm is used to obtain daily clusters of viewers. Weekly patterns are then derived which rely on daily patterns. The obtained solutions are tested for consistency and stability. Temporal TV watching patterns provide new insights concerning Portuguese TV viewers' behavior.
- A primer on understanding Google Earth Engine APIsPublication . Reis, Rui S.; Datia, Nuno; Pós-de-Mina Pato, MatildeThis article introduces the rationale behind the usage of the Google Earth Engine, and the advantages it offers, as an alternative to handle large volumes of georeferenced data using the existing tools we know as Geographic Information Systems on premises. Google Earth Engine is an efficient development framework that presents itself in two basic flavors: one online integrated development environment which uses the browser JavaScript’s engine; and two APIs that can be deployed on either a Python or a NodeJS environment. After presenting a limited number of use cases, representative of the Google Earth Engine design patterns, and building a prototype class using both variants, we conclude that both platforms are merely proxy APIs to the Google Earth Engine and do not have any measurable performance difference. However, since they run on fundamentally diverse contexts — a JavaScript’s engine on an internet browser, that integrates seamlessly with Google Maps, and a Python environment — it is argued that their utility depends on the user requirements instead of being true alternatives.
- Visual analytics for spatiotemporal eventsPublication . Silva, Ricardo Almeida; Moura Pires, João; Datia, Nuno; Santos, Maribel Yasmina; Martins, Bruno; Birra, FernandoCrimes, forest fires, accidents, infectious diseases, or human interactions with mobile devices (e.g., tweets) are being logged as spatiotemporal events. For each event, its geographic location, time and related attributes are known with high levels of detail (LoDs). The LoD plays a crucial role when analyzing data, as it can highlight useful patterns or insights and enhance the user’ perception of phenomena. For this reason, modeling phenomena at different LoDs is needed to increase the analytical value of the data, as there is no exclusive LOD at which the data can be analyzed. Current practices work mainly on a single LoD of the phenomena, driven by the analysts’ perception, ignoring that identifying the suitable LoDs is a key issue for pointing relevant patterns. This article presents a Visual Analytics approach called VAST, that allows users to simultaneously inspect a phenomenon at different LoDs, helping them to see in what LoDs do interesting patterns emerge, or in what LoDs the perception of the phenomenon is different. In this way, the analysis of vast amounts of spatiotemporal events is assisted, guiding the user in this process. The use of several synthetic and real datasets supported the evaluation and validation of VAST, suggesting LoDs with different interesting spatiotemporal patterns and pointing the type of expected patterns.
- AA-Maps: attenuation and accumulation maps for spatio-temporal event visualisationPublication . Albino, Catarina; Moura Pires, João; Datia, Nuno; Silva, Ricardo Almeida; Santos, Maribel YasminaSome phenomena, such as crimes in a city, fires occurred in a country and road accidents can be interpreted as sets of spatio-temporal events. A spatio-temporal event is described by a geographic location, a time instant and other characterising attributes. The cartographic visualisation of spatio-temporal events remains unresolved, due to the challenges related with portraying multiple dimensions simultaneously: the spatial, the temporal and the semantic (zero or more dimensions) phenomenon's components. In this context, this article presents the Attenuation and Accumulation Maps (AA-Maps). The main idea of this visualisation analytic approach consists in showing in a map, the resulting effect of combining attenuation and accumulation, from a temporal reference of observation, given a spatio-temporal Level of Detail (LoD). Imagine the footprints of people crossing a garden in various directions. They leave different traces that summarize the cumulative effect of the footprints on the grass, which is attenuated as time goes by. AA-Maps support different combinations of attenuation and accumulation functions. In addition, this method also enables analysis with different Levels of Detail (LoD), both spatial and temporal. This allows distinct analytic perspectives of the phenomenon while promoting the search for the most suitable parametrization for its characteristics.
- A deep learning approach to identify not suitable for work imagesPublication . Bicho, Daniel; J. Ferreira, Artur; Datia, NunoWeb Archiving (WA) deals with the preservation of portions of the World Wide Web (WWW) allowing their availability for the future. Arquivo.pt is a WA initiative holding a huge amount of content, including image files. However, some of these images contain nudity and pornography, that can be offensive for the users, and thus being Not Suitable For Work (NSFW). This work proposes a solution to classify NSFW images found at Arquivo.pt, with deep neural network approaches. A large dataset of images is built using Arquivo.pt data and two pre-trained neural network models, namely ResNet and SqueezeNet, are evaluated and improved for the NSFW classification task, using the dataset. The evaluation of these models reported an accuracy of 93% and 72%, respectively. After a fine tuning stage, the accuracy of these models improved to 94% and 89%, respectively. The proposed solution is integrated into the Arquivo.pt Image Search System, available at https://arquivo.pt/images.jsp.
- Mobilidade urbana sustentável: plataforma inteligente de monitorizaçãoPublication . Vaz, João; Datia, Nuno; Pós-de-Mina Pato, MatildeO parque automóvel circulante em Portugal tem sofrido um crescimento constante, quer em número de veículos, quer na idade média dos veículos. Os congestionamentos de trânsito, com particular incidência nos centros urbanos, e.g. a cidade de Lisboa, resultam em impactos negativos na vida dos cidadãos, onde se incluem problemas de saúde, económicos, sociais e ambientais. Com recurso a diferentes formas de sensorização é possível estudar, compreender e prever fluxos de tráfego em zonas de interesse nos centros urbanos. A partir de modelos de aprendizagem automática, neste trabalho é possível criar e utilizar modelos preditivos de indicadores de tráfego, para diferentes momentos e pontos de interesse na cidade de Lisboa. Os resultados preliminares mostraram que, com o algoritmo XGBoost, é possível prever o tempo de atraso causado por um congestionamento com erros a variar, aproximadamente, entre os 2 e os 3 minutos, verificando-se ainda que a partir da fusão de dados de tráfego, de meteorologia e sociais estes são melhores. Estes modelos podem ser integrados com a plataforma de gestão integrada de Lisboa (PGIL) e contribuir para as tomadas de decisão relativas à mobilidade. São, assim, mais uma ferramenta que permite antecipar futuros congestionamentos e melhorar o planeamento e gestão urbana para que seja possível reduzir os congestionamentos e mitigar os seus consequentes impactos.