# Voxel-Based Digital Twin Framework for Earthwork Construction
## 1 Introduction
A scan-to-building information modeling (BIM) approach was utilized for bridge construction monitoring, leveraging laser scanning data and BIM models to enhance progress monitoring [16]. A framework was developed that uses vision data and IoT data to collect the progress and resource data for construction status assessment, visualization, and prediction [6]. These studies underscore the growing relevance and versatility of digital twins in improving the efficiency, accuracy, and visualization of the construction stage. Despite these advancements, existing digital twin approaches in construction face several limitations, particularly when applied to earthwork construction. For example, previous studies relied on static BIM or CAD models for virtual twin development to represent the as-plannedmodel while collecting data from physical objects [17]. These models do not reflect earthwork properties, which are based on inhomogeneous geotechnical characteristics, and support volumetric changes that occur during excavation and filling [18]. The modeling needed to develop a virtual twin for earthwork is fundamentally different. Structural components typically possess homogenous characteristics and can be represented as discrete, object-based elements within a BIM environment; however, earthwork elements such as terrain and soils are irregular and heterogeneous, characterized by uncertain properties that vary spatially and temporally [18]. Additionally, unlike structural components that are installed or constructed according to the static as-planned designs, earthwork is inherently operational, involving dynamic changes to the terrain in a volumetric manner due to the filling and excavation activities [19]. Capturing these dynamic characteristics of earthwork requires specialized geometric modeling that can represent its complexity in a spatially accurate and semantically rich manner, enabling the virtual twin to reflect realistic conditions and adapt to the evolving physical twin [20]. Apart from this, recently proposed vision-based methods for digital twin creation provide excellent capabilities to capture dynamic changes in the construction environment; however, the earthwork digital twin requires additional information, such as material properties, for semantically specific simulations and progress monitoring [21]. Moreover, they capture point-based information, such as point clouds, which are converted into surfaces and do not support volumetric reasoning, which is crucial for managing cut-and-fill operations [22]. Most importantly, integration between geometric and semantic twin sources (such as design information, construction dataset monitored from the physical twin, and geotechnical parameters) is typically ad hoc [23]. A holistic system that integrates the information in a unified platform with an update function, not only for the geometric information but also for the earthwork semantics, is needed and can contribute significantly. Voxel-based representation offers a robust solution to address the inherent challenges, making it highly suitable for the development of a realistic earthwork digital twin [24]. The advantages of the voxels in this context are as follows: (1) voxels are a volumetric unit created by discretizing the as-planned or as-built model into three-dimensional (3D) cells/cubes, capturing the realistic representations of earthwork characteristics. (2) Voxels are scalable and their size can be refined, allowing for the detailed representation of uncertain earthwork properties [25]. (3) Each voxel can integrate semantic information such as soil type, cohesion, strength, moisture content, unit cost, and excavation time, enabling detailed monitoring of earthwork conditions. This embedded semantic information not only supports material-specific simulation during model-equipment interaction but also allows for tracking which materials have been excavated or filled during construction.