10/03/2026
Sensors, data, and virtual models are transforming the way underground infrastructure is conceived and managed. Digital twins facilitate anticipating risks, optimizing decisions, and improving security in environments where the margin of error is minimal.
An invisible but essential network sprawls beneath our cities. It’s formed by tunnels, technical lanes, and hydraulic conduits that support mobility, supply, and economic development. Managing these facilities, hidden from view and subjected to especially complex conditions, has historically been a major technical challenge. Today, convergence between underground engineering and digital technologies opens the door to a new way of understanding, designing, and operating these systems. We explore how digital twins are capable of redefining each phase of the life cycle of underground infrastructures.
What is a digital twin in the context of infrastructure?
A digital twin can be understood as a dynamic virtual replica of a physical object, permanently synchronized with its real counterpart through continuous data flows from sensors, control systems, and management platforms.
Unlike conventional BIM models, which usually offer predominantly static three-dimensional representations, a digital twin integrates structural, operational, and temporal information. This combination means that, beyond describing the state of the asset, we can also understand, simulate, and anticipate future behavior with great confidence.
The scientific literature on underground spaces emphasizes that there isn’t a single type of digital twin, but rather different levels of maturity. These range from descriptive models—focused on reflecting the current state—to predictive and prescriptive twins, capable of recommending optimal action plans through simulations, machine learning, and observational methods typical of geotechnical engineering. This layered view is particularly valuable when assets are underground, where the uncertainty of the terrain and interaction with the built environment are critical factors.
Planning before excavation
Planning tunnels and other underground infrastructure has so far been based on two-dimensional plans, one-off geotechnical studies, and static assumptions about the behavior of the terrain. Digital twins represent a break from this approach by offering an integrated platform where high-resolution geospatial data, terrain characterization models, associated risk analyses, and simulations of alternative routes converge.
These digital environments allow us to evaluate hypothetical scenarios before starting a given project, anticipate interference with existing services, and analyze the terrain’s response to different excavation strategies.
European research also highlights that the interoperability of data and the use of open standards are essential elements in facilitating the reusability and scalability of these models, especially in public projects and complex urban networks.
Construction: monitoring and process control
During the construction phase, the execution of this type of project presents challenges associated with geological uncertainty, coordination of multiple disciplines, and the need to manage risks in real time. In this context, digital twins act as a control system that connects information from the construction site with the design.
Technologies like laser scanning, photogrammetry, or mobile mapping allow for continuous updating of the virtual representation, generating an accurate picture of excavation progress. This integration facilitates the early detection of deviations from the intended design, verification of the executed quality, and smoother communication among the different agents involved. The result is a greater capacity to react to incidents, avoiding excessive costs and delays.
A significant example is the development of digital gems applied to the Granada metropolitan rail network. In this case, the combination of point clouds, Building Information Modeling (BIM) methodology, and collaborative platforms has allowed for the digitalization of the construction process, and laid the groundwork for more efficient management of the asset during its subsequent operation phase.
Advanced maintenance
Once in operation, these underground facilities require high levels of reliability and safety. However, traditional maintenance, based on regular inspections, doesn’t always reflect the real state of the infrastructure. Digital twins introduce a paradigm shift by enabling predictive maintenance strategies supported by continuous monitoring.
IoT sensors, control systems, and simulation tools allow for the identification of anomalous patterns, estimation of the evolution of structural deterioration, and planning of interventions before critical failures occur. In road tunnels, these capabilities also extend to traffic management, ventilation, lighting, and energy consumption.
Recent initiatives in northern Spain, developed in collaboration with technology centers, show how the adoption of these solutions can reduce energy consumption and improve operational safety through dynamic management of tunnel systems. This is complemented by projects like M Twins4US, aimed at maintaining buried networks through machine learning techniques and simulated models that predict the useful life of assets.
Digital twins in underground mining
The reach of digital twins isn’t limited to urban environments. In the mining sector, and especially in underground mining, this technology is taking on an increasingly strategic role, as evidenced with the Quellaveco mine, in Peru, conceived from its design as a highly digitalized operation.
Digital twins are used to simulate mining processes, optimize production planning, and anticipate the behavior of critical variables related to safety and operational efficiency. Integrated with advanced control centers and supported by predictive analytics systems, allow for testing decisions in a virtual environment before applying them in the real world, reducing risks and improving the sustainability of operations.
Benefits of digital twins and related challenges
Despite their potential, the widespread implementation of digital twins in underground infrastructure faces significant hurdles. Among the main challenges are the integration of heterogeneous data from multiple sources, the initial costs associated with deploying sensors and digital platforms, and the need to strengthen cybersecurity in highly connected systems. On top of these technical challenges come other organizational and institutional challenges, such as the adoption of adequate regulatory frameworks and training for the entities responsible for managing these complex systems.
However, despite these obstacles, the social and economic benefits are becoming increasingly evident. The ability to anticipate failures, optimize maintenance, and reduce service disruptions translates into greater safety for users, a more efficient use of public resources, and a reduced environmental footprint.
The promise of this technology goes beyond replicating a physical structure: it means we can understand and manage what goes on beneath the ground with unprecedented precision, marking a decisive step in the evolution of infrastructure engineering in the 21st century.
