The incorporation of digital technology in the mining industry has received many positive feedback in recent years. A good example is the utilisation of autonomous dump trucks in haulage operations. This application, however, does not come without shortfalls such as spilling due to overloading. When spilling occurs, dump trucks are more susceptible to a number of accidents including the reduction of brake performance, excessive exhaust gas emission, and the overall wearing of the body and engine. As a countermeasure, recently, several studies have been conducted regarding the development of loading volume measurement systems. One of such consists of measuring instruments directly mounted on dump trucks, as well as one based on volume measurement using laser scanning mounted orthogonally above the dump truck. These systems can however be complex and difficult to install on all heavy machinery and sites. Moreover, the systems can be expensive, time-consuming and are generally made for a single specialised purpose. This study therefore proposes an improvement to these systems via use of drones and digital twin technology for detecting dump truck overloading and spilling. The utilisation of drones is already prevalent in the mining industry looking to digitise the operations, and as such, the possible application of this technology would be smooth and cost-efficient loading and haulage operation. This system works by capturing several photographs using a drone from multiple points around the truck during loading. From these images, photogrammetry is used for constructing a 3D point cloud model of the dump truck plus load. By analysing this model, the shape and volume of the load are derived to extrapolate the loading status of the dump truck. Based on this technology, the proposed method has the potential to allow better load control for dump trucks, thereby increasing the overall productivity of a mine through system optimisation.