Robust and Efficient Big Data Analytics Using Thermal Imaging and Machine Learning

This study presents a robust and computationally efficient framework for big data analytics using thermal imaging data of a ship's engine. The framework combines Robust Principal Component Analysis (RPCA) for data cleaning, Optimal Sensor Placement (OSP) for data compression, and Long Short-Term Memory (LSTM) networks for predictive modeling.