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Processamento analítico de fluxos de dados de tráfego em tempo quase real

Authors: Pintor, Paulo Sérgio Oliveira;

Processamento analítico de fluxos de dados de tráfego em tempo quase real

Abstract

Nos dias de hoje, as tecnologias com as quais temos contacto geram dados sobre a sua utilização e sobre o utilizador, com uma velocidade e variedade sem precedentes. Cria-se assim a necessidade de gerir os fluxos de dados e de transformar estes dados em informação armazenada de forma estruturada, inferindo sobre a mesma e retirando conclusões. As áreas de aplicação são diversas e uma das vertentes que tem recebido maior atenção é o processamento de dados referentes ao tráfego automóvel obtidos usando dispositivos GPS, que se devidamente tratados permitem dar informação adicional aos utilizadores sobre o estado do trânsito, encontrar os caminhos mais rápidos ou até fazer previsões sobre o tráfego no futuro. O objetivo desta dissertação consiste em implementar um protótipo que consiga fazer o processamento de um fluxo de dados obtidos em tempo real e estruturá-los de forma a dar respostas sobre o estado do tráfego no momento e no futuro próximo. Para conseguir dar estas respostas, serão considerados não só os dados recebidos em tempo real como também informação adquirida anteriormente, de forma a ser possível fazer comparações e tirar conclusões. O protótipo está dividido em três módulos principais: o pré-processamento e a análise de dados históricos; o processamento de dados de tráfego em tempo quase real; e a apresentação de resultados. O protótipo foi sujeito a testes e os seus resultados sujeitos a avaliação de forma a verificar a validade das respostas devolvidas ao utilizador.

Nowadays, the technologies we handle generate data about their usage and the user, with an unprecedented rate and variety. This raises the need to manage all the data streams and to transform these data in information. This information is stored in a structured way allowing to infer about it and withdraw conclusions. There is a wide range of application areas, with the car traffic data processing receiving the most attention. These data are obtained from GPS devices and if properly processed, allow the user to have additional information about the traffic status, the faster way to a destination and even predictions on the future traffic status. This dissertation aims to implement a prototype able to process and structure the data streams in real-time, to ultimately present answers about the traffic status at the moment or even in a near future. These answers are obtained not only by the real-time information but also by previously acquired information. Having two sources of information allows to compare and withdraw statistical conclusions. The prototype is divided in three main modules: the pre-processing and analysis of historical data; the processing of traffic data in near real-time; and the results presentation. The prototype was subject to tests and their results subject to evaluation to verify the answers’ assertiveness.

Mestrado em Sistemas de Informação

Country
Portugal
Related Organizations
Keywords

Sistemas de informação, informação e previsão de tráfego, Apache Storm, Processamento de fluxos de dados, análise de dados em tempo quase real, Armazenamento de dados, Processamento de dados em tempo real

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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