A Stream Processing System for Multisource Heterogeneous Sensor Data

With the rapid development of the Internet of Things (IoT), a variety of sensor data are generated around everyone’s life. New research perspective regarding the streaming sensor data processing of the IoT has been raised as a hot research topic that is precisely the theme of this paper. Our study serves to provide guidance regarding the practical aspects of the IoT. Such guidance is rarely mentioned in the current research in which the focus has been more on theory and less on issues describing how to set up a practical system. In our study, we employ numerous open source projects to establish a distributed real time system to process streaming data of the IoT. Two urgent issues have been solved in our study that are (1) multisource heterogeneous sensor data integration and (2) processing streaming sensor data in real time manner with low latency. Furthermore, we set up a real time system to process streaming heterogeneous sensor data from multiple sources with low latency. Our tests are performed using field test data derived from environmental monitoring sensor data collected from indoor environment for system validation. The results show that our proposed system is valid and efficient for multisource heterogeneous sensor data integration and streaming data processing in real time manner

Constructing Execution and Life-Cycle Models for Smart City Services with Self-Aware IoT

International audienc

Smart Panking : uma aplicação para estacionamento em cidades inteligentes

The world is experiencing two major transformations: the number of people living in urban areas surpassing the number of people in rural areas and a technological revolution changing the lives of billions of people. With more people living in cities, the problems they face are intensified and the response to these problems increasingly involves the use of a lot of technology, from which emerges the concept of Smart City. In order to deal with one of the most critical problems of cities, urban mobility, this work seeks to understand its causes and what interventions could be undertaken. One of the most prominent problems that impacts the urban mobility is the high number of vehicles circulating in cities and one of the challenges is to manage this fleet of vehicles in order to reduce congestion, facilitating mobility and consequently reducing the amount of exhaust gases in the atmosphere. Since one of the causes of this problem is the time spent by drivers looking for parking spaces, one solution is to minimize it. For this purpose a Systematic Literature Review of primary studies that were inserted in this context was carried out and through a Product Research in the Market, followed by the application of a questionnaire to stakeholders, relevant characteristics were extracted for the development of a solution for this scenario. Therefore, the objective of this work was to create a tool that intelligently optimizes the process of supply and demand of parking spots, considering the growing number of vehicles and the limited space of cities as a contribution to the development of Smart Cities.O mundo está vivenciando duas grandes transformações: o número de pessoas vivendo em zonas urbanas ultrapassando o número de pessoas em zonas rurais e uma revolução tecnológica mudando a vida de bilhões de pessoas. Com mais pessoas vivendo nas cidades, os problemas que elas enfrentam são intensificados e a resposta a esses problemas envolve cada vez mais o emprego de muita tecnologia, de onde emerge o conceito de Cidade Inteligente. Com o intuito de lidar com um dos problemas mais crucias das cidades, a mobilidade urbana, este trabalho procurou levantar as suas causas e quais intervenções poderiam ser realizadas. Um dos problemas mais proeminentes que gera impacto na mobilidade urbana é o crescimento da quantidade de veículos circulando nas cidades e um dos desafios é gerenciar esta frota de veículos buscando diminuir o congestionamento, facilitando a mobilidade e consequentemente reduzindo a quantidade de gases expelidos na atmosfera. Uma vez que uma das causas deste problema é o tempo gasto pelos motoristas na procura por vagas para estacionar, uma solução é minimizar esta causa. Para este fim foi realizada uma Revisão Sistemática dos estudos primários que estão inseridos neste contexto e por meio de uma Pesquisa de Produtos no Mercado, seguido da aplicação de um questionário para stakeholders foram extraídas características relevantes para o desenvolvimento de uma solução para este cenário. Sendo assim o objetivo deste trabalho foi criar uma ferramenta que otimiza de forma inteligente o processo de oferta e procura de vagas de estacionamento, tendo em vista o número crescente de veículos e o espaço limitado das cidades como contribuição para o desenvolvimento das Cidades Inteligentes.São Cristóvã

Intelligence in 5G networks

Over the past decade, Artificial Intelligence (AI) has become an important part of our daily lives; however, its application to communication networks has been partial and unsystematic, with uncoordinated efforts that often conflict with each other. Providing a framework to integrate the existing studies and to actually build an intelligent network is a top research priority. In fact, one of the objectives of 5G is to manage all communications under a single overarching paradigm, and the staggering complexity of this task is beyond the scope of human-designed algorithms and control systems. This thesis presents an overview of all the necessary components to integrate intelligence in this complex environment, with a user-centric perspective: network optimization should always have the end goal of improving the experience of the user. Each step is described with the aid of one or more case studies, involving various network functions and elements. Starting from perception and prediction of the surrounding environment, the first core requirements of an intelligent system, this work gradually builds its way up to showing examples of fully autonomous network agents which learn from experience without any human intervention or pre-defined behavior, discussing the possible application of each aspect of intelligence in future networks