Telefónica is significantly boosting energy optimization in its data centers by incorporating digital twins powered by AI and advanced analytics. This new layer of intelligence allows for a detailed understanding of what is happening inside the technical rooms and enables much more precise control over climate control and installed capacity.
The initiative, led by Telefónica Germany in collaboration with EkkoSense , relies on a combination of IoT sensors, real-time 3D models, and continuous analysis algorithms. The objective is clear: to reduce energy consumption in data centers , improve network resilience, and advance the Telefónica Group's automation roadmap, both in Spain and across Europe.
A 3D digital twin at the service of efficiency
The project is part of the Autonomous Network Journey (ANJ) , Telefónica's global program aimed at moving networks towards increasingly autonomous models and smart networks . In this context, the digital twin of data centers becomes a key element for automating thermal and capacity management without jeopardizing service continuity.
The solution develops a real-time, three-dimensional model of the data center , powered by a network of IoT sensors that measure temperature, airflow, load, and other critical parameters. Thanks to this view, technical teams can see at a glance how the environment behaves, detect hotspots, and make data-driven decisions, not just based on past experience or estimates.
Beyond visualization, the system integrates advanced analytics and predictive capabilities that suggest adjustments to climate control and IT load distribution. This allows for fine-tuning cooling usage, reducing inefficiencies, and improving Power Usage Effectiveness (PUE) , a key indicator in any data center sustainability and cost control strategy.
Another key advantage is the ability to model and simulate failure scenarios . The digital twin allows for virtual testing of what would happen in the event of a specific incident (for example, the failure of an air conditioning unit or a sudden load increase) and the design of preventative action plans to minimize risks before they materialize.
The deployment is also notable for its speed: new sites can be integrated in a matter of days , without construction or service interruptions. This facilitates extending the solution to more data centers and technical rooms, as well as enhancing the edge computing node network , both in Germany and in other countries where the Telefónica Group operates.
How to manage data centers with AI and IoT sensors
Data centers and technical sites account for a significant portion of the telecom sector's electricity consumption. With the growth of data traffic and the increased demand for digital services, the challenge is no longer just expanding capacity, but making better use of existing infrastructure without causing energy bills to skyrocket.
In this scenario, the solution developed with EkkoSense relies on a dense layer of IoT sensors that collect information on temperature, airflow, rack occupancy, and the behavior of critical equipment. All this information is sent in real time to a platform that processes the data and feeds the 3D digital twin, supported by AI infrastructure partnerships.
From there, operators have access to a dynamic map of thermal and load risks , where they can see overcooled or overheated areas, as well as racks that are near their capacity or underutilized. Based on this information, the system generates automatic recommendations that help reorganize equipment, adjust airflow, or modify temperature setpoints to reduce energy consumption without compromising performance.
This approach also extends the lifespan of the equipment , since maintaining more stable thermal conditions that meet the manufacturer's specifications reduces the stress placed on the hardware. Indirectly, this translates into fewer incidents, fewer downtimes, and more predictable operation.
The tool is designed to be manageable by network operations teams, avoiding the complexity historically associated with some DCIM solutions. According to Telefónica Germany's experience, the combination of immersive visualization, real-time analysis, and automation makes it easier for technical staff to adopt the system and integrate it into their daily operations.
Impact on energy consumption and daily operation
Initial measurements of this deployment indicate an estimated 15-20% savings in energy consumption for data center cooling systems . In practical terms, this translates into a direct reduction in energy-related operating expenses (OpEx), one of the most significant cost components for these infrastructures.
Beyond the percentages, continuous monitoring of thermal behavior is allowing Telefónica to avoid unnecessary investments: by making better use of available capacity, expansions of air conditioning or space that were previously considered essential are postponed. In other words, the infrastructure is being used more efficiently before considering expansion.
Another important effect relates to risk prevention . Predictive alerts and proactive maintenance help detect patterns that anticipate failures, allowing time to act before a problem affects service availability. At the same time, automating reports with auditable data simplifies regulatory compliance and the preparation of internal and external reports.
All of this contributes to consolidating a more resilient operating model in the face of peak demand and increases in IT load, an aspect that is especially critical in contexts of traffic growth, 5G deployments or expansion of advanced digital services.
In parallel, the use of digital twins fits with the Group's sustainability objectives, by reducing the environmental footprint of data centers and supporting the transition towards more responsible energy consumption, both in Spain and in the rest of the European markets where Telefónica has a significant presence.
Career advancement within the Telefónica Group and demonstrators
The deployment of these AI-powered digital twins is being carried out progressively, prioritizing sites with the highest energy consumption . As the results in Germany are consolidated, the Group is working to extend this approach to other countries, sharing lessons learned, methodologies, and use cases.
Telefónica views this solution as another piece in its global autonomous network strategy , alongside other initiatives aimed at automating infrastructure planning, configuration, and operation. The combination of real-time data, AI, and digital models enables progress toward an environment where critical decisions are made faster and, in many cases, automatically.
To bring this technology closer to customers, partners, and internal teams, the company has set up physical demonstrators . In Spain, the solution can be seen at LaCabina, in Distrito Telefónica (Madrid) , a space dedicated to showcasing technological use cases. In Germany, it is present in the Innovation Experience Area of O2 Telefónica in Munich , where it explains how the digital twin helps manage the data center more efficiently.
These environments also showcase other solutions driven by the GCTIO area that illustrate how Telefónica is progressing in its Autonomous Network Journey , combining automation, virtualization and data analytics to transform the way networks are designed and operated.
This AI-powered digital twin approach in data centers aims to become an internal standard for the Group, supporting both cost-saving objectives and those related to sustainability and quality of service. The experience gained in Germany and in the demonstrators in Madrid and Munich will serve as a foundation for new deployments in Europe and other markets , where the pressure to improve energy efficiency in critical infrastructure is constantly increasing.
