Application of Data Science and Big Data Analytics in Underground Transportation Infrastructure

This research project applies data science, predictive analytics, and big data analytics to the construction, maintenance, and performance of the underground transportation infrastructure. The potential applications include: (a) data-driven prediction and automated decision-making, (b) predicting or detecting ground and geological conditions before or during the TBM operations, (c) predicting adverse events, and consequently, improved risk management, (d) optimal visualization of UTI data, and (e) proactive underground transportation infrastructure monitoring. The project is divided into three phases: Phase I, Large-Scale UTI Data Collection, Exploration, and Preprocessing, will entail Task I: Research, Information and Literature Search, Task II: Data Collecting and Exploring, and Task III: Data Preprocessing; - Phase II, Knowledge Extraction, Data Analytics, and Predictive Analytics, will entail Task IV: Feature/Knowledge Extraction, Task V: Feature Selection & Data Dimensionality Reduction, and Task VI: Data Analytics/Predictive Analytics; and Phase III, Data Visualization and Storage, will entail Task VII: Data Visualization and Task VIII: Data Storage, Archiving, and Accessibility.