ABSTRACT
The rapid development of information technology in recent decades means that the digitalization world has experienced an explosion in the magnitude of data being captured and recorded in various industry fields. The most fundamental challenge for Big Data (BD) applications is to explore large volumes of data and extract useful information and develop techniques that automatically discover new, hidden, or unsuspected data from the large text collection. Although the advances in computer systems and internet technologies have witnessed the development of computing hardware following Moore’s law for several decades, the problems of handling large-scale data still exist when we are entering the age of BD. In addition, some existing and emerging concepts like cloud computing, data mining, machine learning, the internet of things, smart grids, and automation will continue to drive and even accelerate the growth of data. Storing, managing, and analyzing such a huge amount of data can’t be simply done by using traditional databases and techniques. Instead, it requires a new class of advanced technologies. Under such a circumstance, BD management has recently emerged to address this deficiency. The traditional tunneling industry is also experiencing an increase in data generation and storage. BD will change the way of gathering geological data, methods of rock classification, application of design analyses in the field of tunneling as well as tunnel construction and maintenance processes. BD, data mining had to be introduced with the most relevant techniques to analyze data related to tunneling operations. The concept of machine-generated data was also necessary for the further parts, as log files and reports from tunneling equipment are used in the data analyses. The paper briefly described the current situation of the tunneling industry, focusing on its challenges, and also mentioning some of its other unique attributes.
