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Publicação
Mapeamento de Comportamento de Comboios
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| 20.79 MB | Adobe PDF |
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Hoje em dia, a quantidade da dados produzidos diariamente é imensa, dados provenientes
de sensores, dispositivos móveis e até de pequenos aparelhos que tenham GPS.
Dados estes que em boa prática, com tratamento e análise, se traduzem em informação
valiosa.
Em companhias ferroviárias a análise de dados provenientes de sensores espalhados
por toda a estrutura dos comboios, sensores que geram milhares de dados diariamente,
têm diversas finalidades como gestão de trânsito, gestão de horários e manutenção baseada
em condições.
A manutenção baseada em condições analisa os dados provenientes dos sensores com
o intuito de entender em que situação os dispositivos se encontram, de modo a evitar
substituições desnecessárias como também evitar falhas devido à falta de substituição.
Esta dissertação visa desenvolver uma interface capaz de apresentar dados, (informações,
velocidades ou até mesmo erros) provenientes de comboios. Tenciona-se ainda que
estes dados sejam exibidos geograficamente em mapas.
Pretende-se que este sistema seja implementado em cloud devido à quantidade elevada
de dados a serem transmitidos e processados. Ambientes cloud são altamente escaláveis e
eficazes, tal que, garantem que o processamento dos dados não seja comprometido pela
sua quantidade e diversidade. O desenvolvimento desta interface é demonstrado passo a
passo e a mesma é avaliada e analisada.
É ainda objetivo que os dados a apresentar sejam de fácil leitura e interpretação sendo
necessário o processamento dos mesmos antes da sua utilização.
Nowadays, the amount of data produced daily is enormous, data acquired from sensors, mobile devices and even small devices equipped with GPS. That data, in good practice, with treatment and analysis, translates into valuable information. In railway companies, the analysis of data from sensors spread throughout the structure of trains, sensors that generate thousands of data points daily, has different purposes such as traffic management, timetable management and condition-based maintenance. Condition-based maintenance analyzes data from sensors to understand what status devices are in, to avoid unnecessary replacements as well as to prevent failures due to lack of replacements. In this dissertation it is intended to develop an interface capable of presenting data, being information, speeds or even errors from trains. It is also intended for this data to be displayed geographically on maps. Is intended for this system to be implemented in the cloud due to the high amount of data being transmitted and processed. Cloud environments are highly scalable and efficient, as they ensure that data processing is not compromised by its quantity or diversity. The development of this interface is not only demonstrated step by step but also evaluated and analyzed. It is also intended that the data to be presented is easy to read and interpreted, being necessary to process it before their usage.
Nowadays, the amount of data produced daily is enormous, data acquired from sensors, mobile devices and even small devices equipped with GPS. That data, in good practice, with treatment and analysis, translates into valuable information. In railway companies, the analysis of data from sensors spread throughout the structure of trains, sensors that generate thousands of data points daily, has different purposes such as traffic management, timetable management and condition-based maintenance. Condition-based maintenance analyzes data from sensors to understand what status devices are in, to avoid unnecessary replacements as well as to prevent failures due to lack of replacements. In this dissertation it is intended to develop an interface capable of presenting data, being information, speeds or even errors from trains. It is also intended for this data to be displayed geographically on maps. Is intended for this system to be implemented in the cloud due to the high amount of data being transmitted and processed. Cloud environments are highly scalable and efficient, as they ensure that data processing is not compromised by its quantity or diversity. The development of this interface is not only demonstrated step by step but also evaluated and analyzed. It is also intended that the data to be presented is easy to read and interpreted, being necessary to process it before their usage.
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Palavras-chave
Big data Cloud Google Cloud Platform Mapas Coordenadas Geográficas Manutenção Baseada na Condição