This project aims to automate the timber loading and unloading process using AI-based measurement systems. By developing machine learning models to accurately measure timber dimensions and weight in real-time, we seek to optimize operations and reduce manual labor. The models will be trained on custom datasets using images and sensor data. To achieve this, we require access to High-Performance Computing (HPC) resources to efficiently train and validate the AI models on large-scale data. HPC will accelerate model development and ensure accuracy, enabling us to create a reliable, real-time automation system that improves efficiency in the timber industry.