Russell KennettYelbatyr Byambayev2024-11-062024-11-062024-05-10https://gmitlibrary.net/handle/123456789/41This bachelor's work reviews the potential to simplify, analyze, and simulate Tire Pressure Monitoring Systems (TPMS) data for real-time monitoring and mapping of road surface conditions in underground mine haulage level transportation, Oyu Tolgoi LLC. The main goal is to create a system that uses TPMS data to identify and categorize different types of road surfaces and levels of roughness to provide real-time maps of the state of the roads. The proposed system can provide valuable information to underground haulage and road maintenance authorities to optimize transportation routes, reduce equipment maintenance costs, reduce employee discomfort and fatigue, and improve road safety. The suggested method gathers real-time tire pressure and temperature data using PressurePro TPMS sensors mounted in haulage vehicles. The data then identifies and classifies road surface types and roughness levels. The method uses NodeJS to create a web app, JavaScript to write code, and SQL to manage data stored in relational databases. The system creates real-time maps of road conditions that display the different levels of road roughness using color-coded visualizations. The proposed system has significant implications for the "Road Train," the underground transportation ore industry, and can contribute to developing more efficient, reduced vehicle damage, and safer transportation systems. The experimental data results from the "Road Train" models were analyzed.enThesis