Digital Twin | How Telefonica Is Driving Energy Efficiency in Its Data Centers

Key Takeaways

• Digital twin cuts cooling energy 15‑20% in pilot sites.
• Real‑time sensor analytics optimize PUE and prevent over‑provisioning.
• Deployment integrates new sites within days, no downtime.
• Predictive alerts extend equipment life and reduce CapEx.
• Solution scalable across Telefonica Group, enhancing sustainability.

Pulse Analysis

Data centers are among the most energy‑intensive assets in the telecom industry, with cooling systems accounting for a large share of total power draw. As traffic volumes surge, operators must find ways to improve efficiency without compromising performance. Digital‑twin technology—creating a live, 3‑D replica of physical infrastructure—offers a granular view of thermal dynamics, enabling precise adjustments that traditional DCIM tools cannot achieve.

Telefonica Germany’s partnership with EkkoSense leverages dense IoT sensor networks and edge analytics to feed continuous temperature, humidity and load data into a unified digital model. The platform automatically generates risk maps, suggests optimal set‑points for HVAC equipment and forecasts potential overloads, delivering measurable gains such as a 15‑20% cut in cooling energy use. Because the system can be installed in days and operates without interrupting service, it sidesteps costly construction cycles and accelerates rollout across the network’s heterogeneous sites.

The broader impact extends beyond immediate cost savings. Predictive maintenance prolongs hardware lifespan, reducing capital expenditures, while automated reporting simplifies compliance with ESG metrics. As Telefonica scales the solution across its European footprint, it showcases a replicable pathway for other carriers seeking to meet tightening carbon regulations and stakeholder expectations. The digital‑twin approach is poised to become a cornerstone of next‑generation, sustainable telecom infrastructure, marrying operational resilience with environmental responsibility.