IoT and Big Data Analytics: Under-Rail Maintenance Management at Vitória

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IoT and Big Data Analytics: Under-Rail Maintenance Management at Vitória – Minas Railway

Sobrinho, Osvaldo Gogliano / Mariani Bernucci, Liedi Ledi / Pizzigatti Correa, Pedro Luiz / Dos Santos Motta, Rosangela / Machicao, Jeaneth / Junqueira, Angelo Samuel / De Queiroz, Wellingthon Dias / De Mello E Silva, Thales Cesar Giriboni / Cassaro, Luciano / Oliveira, Luciano

Abstract

This paper describes a study using data collected by an instrumented ore car on Vitoria-Minas Railway, operated by Vale S. A. in Brazil. The study uses big data analysis over collected data by the instrumented car during its voyages. Railway geometry issues can cause undesirable movements on the wagons that can cause discomfort for passengers or instability for the cargo. In the worst scenario, derailments can occur. Several sensors installed on the instrumented car collect data about the wagon's velocity, acceleration, and movements each second. The volume of collected data is impressive since the railway has about 2,000 km of extension. That volume compels us to use big data analytics methods. As the result of the research, the team aims to establish some operational conditions, named severity indexes, which can indicate to the maintenance teams the necessity of intervention on the railway.

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Document information

Title :

IoT and Big Data Analytics: Under-Rail Maintenance Management at Vitória – Minas Railway

Contributors:

Sobrinho, Osvaldo Gogliano (author) / Mariani Bernucci, Liedi Ledi (author) / Pizzigatti Correa, Pedro Luiz (author) / Dos Santos Motta, Rosangela (author) / Machicao, Jeaneth (author) / Junqueira, Angelo Samuel (author) / De Queiroz, Wellingthon Dias (author) / De Mello E Silva, Thales Cesar Giriboni (author) / Cassaro, Luciano (author) / Oliveira, Luciano (author)

Published in:

2023 Symposium on Internet of Things (SIoT) ; 1-5

Publication date :

2023-10-25

Size :

1104552 byte

ISBN :

979-8-3503-2943-8

DOI :

https://doi.org/10.1109/SIoT60039.2023.10389944

Type of media :

Conference paper