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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.
- 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.
- 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.
- A performance measurement platform for C-ITS over 5GPublication . Serrador, António; Mendes, Carlos; Datia, Nuno; Cota, Nuno; Cruz, Nuno; Beire, Ana R.This paper aims to present a new performance measurement tool dedicated to mobile cellular networks, focussed on the new C-ITS applications and challenges. Called ISEL QoS-Network Performance Evaluation (IQ-NPE), developed under the European Union 5G-MOBIX project, it is a measurement performance tool that is able to extract a wide range of performance parameters at different levels: radio, network layers and application. This is a step further when comparing with classical tools, based on mobile terminals, because C-ITS applications take advantage of cellular modems using Multiple Input Multiple Output (MIMO) advanced systems, due to available space offered by vehicles. IQ-NPE is designed to test classical alongside with the new C-ITS applications (ITS-G5 based) performance running at the Multi-access/Mobile Edge Computing (MEC) node in the new 5G architecture. All the collected data can be exported, as integrated performance data, to further be analysed using business intelligence tools. Thus, this paper presents the IQ-NPE general architecture, its main components, probes (units composed by hardware and software subsystems), together with configuration input and output examples.