Innovation

Technology

Seven core technological advances combining digital twin engineering, AI/ML optimisation, and open standards to redefine data centre sustainability.

The Problem

Why Current Tools Fall Short

❌ Today's Challenges
  • Data centres consume 2–3% of global electricity with demand accelerating due to AI and cloud growth.
  • Siloed management tools handle cooling, power, and compute in isolation with no unified view.
  • Vendor lock-in through proprietary APIs prevents cross-system optimisation.
  • PUE-only focus ignores carbon source; Carbon Usage Effectiveness (CUE) is unmeasured.
  • Reactive operations respond to failures rather than predicting and preventing them.
✓ The iDT4GDC Solution
  • Unified AI platform connecting cooling, power, compute, workloads, and sustainability KPIs.
  • Open architecture with standard REST APIs enabling any vendor to integrate.
  • Real-time digital twin physics-based simulation for predictive, proactive management.
  • CUE + renewable integration — not just efficiency but climate neutrality as the target.
  • AI/ML-driven decisions from intelligent workload scheduling to dynamic energy pricing.
Core Innovations

Seven Technological Advances

Each innovation addresses a distinct gap in current data centre management, together forming a comprehensive platform.

01
🔮
Open Digital Twin Architecture
Real-time physics-based simulation of thermal dynamics, power distribution, and compute layers in a unified, vendor-agnostic platform. Connects physical infrastructure to its digital counterpart with sub-second update cycles.
02
🧠
AI/ML-Driven Scheduling
Constraint-based solvers, deep neural networks, and reinforcement learning jointly optimise workload placement decisions in real time. Balances performance SLAs with energy cost and carbon intensity simultaneously.
03
☀️
Green Energy Forecasting
Advanced deep learning forecasting models predict renewable energy availability hours ahead, enabling proactive carbon-aware workload scheduling. Integrates grid carbon intensity signals for real-time decisions.
04
💹
Dynamic Energy Pricing
An AI-driven pricing engine aligns compute-job pricing with real-time energy costs and carbon intensity. Creates market incentives for customers to shift workloads to green energy windows automatically.
05
🖥️
Hardware-Aware Workload Placement
Dynamically maps AI training, HPC, and cloud workloads to the most energy-efficient hardware. Considers thermal state, power draw, and workload characteristics to minimise cooling overhead per job.
06
🔗
Cross-Vendor Interoperability
Open REST APIs enable any DCIM, BMS, cooling controller, or cloud orchestrator to integrate without proprietary adapters. No vendor lock-in — works across heterogeneous hardware environments.
07
🌿
EU Green Deal Alignment
Built-in compliance with Climate-Neutral Data Centre Pact commitments, ETSI EN 303 470 standards, and EU sustainability reporting frameworks. Supports Taxonomy Regulation disclosures.
KEY
🏆
Open-Source Foundation
Dual licensing model (community + commercial) lowers adoption barriers while enabling sustainable business models. Community-driven innovation accelerates development beyond the consortium.
Architecture

Platform Stack

The iDT4GDC platform is built on a Service-Oriented Architecture (SOA) with open APIs at every layer, ensuring maximum interoperability.

📊
Unified Dashboard (KER-7)
Real-time visualisation of power, cooling, workloads, carbon KPIs
⚙️
AI Optimisation Engine (KER-1, 2, 3, 4)
ML models for scheduling, forecasting, pricing, and hardware allocation
🔮
Digital Twin Engine (WP2)
Physics-based real-time simulation of the full data centre
🔧
Backend & DCIM Integration (KER-6)
Open-source SOA backend with full DCIM digital twin integration
iDT4GDC Platform Layers
📊 Integrated Dashboard · KER-7
↕
🧠 AI Optimisation Layer · KER-1,2,3,4
↕
🔮 Digital Twin Engine · WP2
↕
⚙️ Backend & API Gateway · KER-6
↕
🏗️ Physical Infrastructure (Any Vendor)
Open REST APIs at every layer
Market Positioning

Competitive Advantage

iDT4GDC provides capabilities that leading proprietary solutions cannot match, particularly in carbon-awareness and open interoperability.

Capability iDT4GDC IBM Maximo Schneider EcoStruxure Sunbird DCIM EkkoSense Siemens Building X
Open-source core ✓ Dual license ✗ ✗ ✗ ✗ ✗
Carbon-aware scheduling (CUE) ✓ Native ✗ ~ Partial ✗ ✗ ~ Partial
Real-time digital twin ✓ Physics-based ~ Asset model ~ Facilities only ~ Monitoring ~ Thermal only ~ Facilities
Compute-layer integration ✓ Full stack ~ Limited ✗ Facilities only ~ DCIM only ✗ Thermal only ✗ Facilities only
AI-driven workload scheduling ✓ AI-driven ✗ ✗ ✗ ~ Rule-based ✗
Cross-vendor open APIs ✓ Open REST ✗ Proprietary ✗ Proprietary ~ Limited ✗ Proprietary ✗ Proprietary
Green energy forecasting ✓ Advanced AI ✗ ✗ ✗ ✗ ✗