Large-Scale Sensor Network Analysis: Applications in Structural Health Monitoring

Large-Scale Sensor Network Analysis: Applications in Structural Health Monitoring

Joaquin Vanschoren (University of Leiden, The Netherlands), Ugo Vespier (University of Leiden, The Netherlands), Shengfa Miao (University of Leiden, The Netherlands), Marvin Meeng (University of Leiden, The Netherlands), Ricardo Cachucho (University of Leiden, The Netherlands) and Arno Knobbe (University of Leiden, The Netherlands)
Copyright: © 2014 |Pages: 34
DOI: 10.4018/978-1-4666-4699-5.ch013
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Abstract

Sensors are increasingly being used to monitor the world around us. They measure movements of structures such as bridges, windmills, and plane wings, human’s vital signs, atmospheric conditions, and fluctuations in power and water networks. In many cases, this results in large networks with different types of sensors, generating impressive amounts of data. As the volume and complexity of data increases, their effective use becomes more challenging, and novel solutions are needed both on a technical as well as a scientific level. Founded on several real-world applications, this chapter discusses the challenges involved in large-scale sensor data analysis and describes practical solutions to address them. Due to the sheer size of the data and the large amount of computation involved, these are clearly “Big Data” applications.
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1. Introduction

Sensors are increasingly being used to monitor the world around us. They measure movements of structures such as bridges, windmills and plane wings, vital signals of humans, atmospheric conditions, and fluctuations in power and water networks. In many cases, this results in large networks with different types of sensors, generating impressive amounts of data. In this chapter, we look at a specific case in considerable detail - a sensor network attached to a large highway bridge - and demonstrate what generic techniques may be required to analyze this data (Knobbe et al., 2010; Vespier et al., 2011).

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