No abstract

Big cities have noticeable problems resulting from poor management of urban services. Monitoring a city gives some parameters to evaluate the performance of urban services, allowing to identify their flaws, and elaborate strategic plains to correct them. Smart cities architectures are intended to propose Information and Communication Technologies (ICTs) solutions to increase service efectiveness. Considering that to establish a ICT infrastructure to support a smart city architecture is very expensive, once you have got the data and you know what urban service you will attend to, you can use a city simulator to test how the architecture will behave when facing the city's problems. In this context we propose the Synaptic City architecture, together with a city simulator, with which we modeled a Brazilian city, Recife, Pernambuco, in order to discuss its main problems.

As Cidades Inteligentes estão emergindo frente às necessidades da nova sociedade da tecnologia e informação que surgiu neste século. Atualmente não existe um modelo de maturidade que possa medir o quão inteligente uma sociedade pode ser com base em indicadores sociais ou tecnológicos. Criar um modelo de maturidade pressupõe levantar requisitos, analisá-los e definir quais serão transformados em indicadores. Este trabalho visa apresentar o nível inicial de um Modelo de maturidade aplicado às cidades inteligentes.

The smart cities concept arises from the necessity of managing several problems caused by the unbridled population growth at urban centers. To make a city become "smart" it is needed to employ Information and Communication Technologies (ICT) to access, process and deliver information according to the urban context. This information can be employed to mitigate several urban issues, such as traffic jams, high natural resource consumption, epidemias, sustainability, waste management, low quality and life expectancy of citizens, among others. Thus, the increasing need to create architectures that are able to interact with the Internet of Things, i.e., several built-in devices, appliances, sensors and actuators embedded in each urban context. This work is a systematic review regarding proposals for such architectures. After selecting the relevant approaches, we have identified a set of issues that these approaches aim to solve and some architectural patterns employed.

Precision-Recall is one of the main metrics for evaluating content-based image retrieval techniques. However, it does not provide an ample perception of the properties of an image dataset immersed in a metric space. In this work, we describe an alternative metric named H-Metric, which is determined along a sequence of controlled modifications in the image dataset. The process is named homogenization and works by altering the homogeneity characteristics of the classes of the images. The result is a process that measures how hard it is to deal with a set of images in respect to content-based retrieval, offering support in the task of analyzing configurations of distance functions and of features extractors.