Buga-Buenaventura route in Colombia.

TunelIA: anticipating risks to improve tunnel maintenance

We use artificial intelligence to reduce energy consumption in ventilation systems and assess the structural condition of tunnels.

Artificial intelligence enables us to develop infrastructure capable of understanding what is happening within it, anticipating potential risks, and helping us make better decisions.

With this vision in mind, we are developing TunelIA, an innovation project funded through the REDes call for proposals by Spain’s Ministry for the Ecological Transition and the Demographic Challenge. The project begins in October 2026 and runs until December 2027.

“With TunelIA, we want to take a step forward in how we look after our infrastructure, moving from observing what has already happened to anticipating what could happen,” says Antonio Ramírez, Innovation Director at Sacyr Concesiones.

TunelIA combines artificial intelligence, advanced sensors, predictive models, and digital twins across two complementary areas.
The first focuses on intelligent ventilation management and fire-related risks. The second applies artificial intelligence to tunnel structural maintenance.

 

Intelligent ventilation

 

Tunnels are complex infrastructure assets that incorporate a range of ventilation, lighting, safety, and control systems. Managing them effectively is particularly important in critical situations, such as accidents or fires, but also in day-to-day operations, when we need to maintain air quality while using energy efficiently.

To achieve this, we collect information from sensors and the SCADA system, which monitors and controls industrial processes remotely and in real time, together with data on traffic, weather, maintenance, and tunnel characteristics.

“One of TunelIA’s main objectives is to reduce electricity consumption from ventilation by up to 20%. The project will also be able to predict potential critical situations inside the tunnel, such as a fire, up to 48 hours in advance, and simulate these scenarios before they occur to determine the most effective response and minimize risks to infrastructure users,” explains Antonio Ramírez.

The AI models will analyze this information to optimize fan operation, predict how factors such as gas accumulation and smoke propagation will evolve, and support a more effective response to different scenarios.

This will enable us to combine energy efficiency, prevention, and safety in a single tool.

 

 

Improving tunnel maintenance


The project’s second area focuses on tunnel structural maintenance, using a platform equipped with LiDAR sensors and thermal and RGB cameras.
These technologies will enable us to automatically detect cracks, moisture, spalling, detachments, corrosion, efflorescence, and other defects.

The data will be integrated into a digital platform showing the location and severity of each defect, helping us prioritize interventions and carry out faster, more objective, and traceable inspections. This can reduce inspection costs compared with traditional methods.

We are working on this solution with Sener Mobility, which contributes its technological expertise and DITer device. DITer provides the basis for the further development of automated tunnel inspection. The solution will be validated under real-world conditions, with its results compared against those obtained using traditional methods.

If validation is successful, the solution could gradually be adapted to other types of underground infrastructure and deployed in other markets where we operate.

Sacyr has 66 kilometers of tunnels under concession. The Buga-Buenaventura route in Colombia, which includes 17 tunnels, will take part in the pilot.

 

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