Deliverable D20 – Use-case Deployment and Demonstrations v2.0 documents the workcarried out under Work Package 5, Tasks 5.3 (Lab Experimentation) and 5.4(Demonstrations), across the full thirty-eight-month duration of the CODECO project. Itpresents a comprehensive account of how the CODECO framework was deployed, validated,and demonstrated across six use-cases spanning smart city infrastructure, urban mobility,media delivery, energy management, industrial automation, and smart buildings.The six pilots — led respectively by the University of Göttingen, i2CAT, Telefónica, theUniversidad Politécnica de Madrid, fortiss GmbH, and Almende — each addressed a distinctreal-world challenge requiring dynamic orchestration of computational and networkingresources across the Edge-Cloud-IoT continuum. The technical results confirm that CODECO delivers measurable value in each deploymentcontext. In P1, dynamic workload offloading improved LiDAR analytics throughput by 32%under constrained edge conditions, with CODECO responding effectively to pod failures,channel degradation, and latency increases. In P2, CODECO's reinforcement learning-drivenorchestration reduced Age of Information by 13.5% and positional tracking Error Distance by23.6% relative to a centralised baseline at peak vehicular load, while maintaining bothdeployments within the 3.5-metre lane-width safety threshold. In P3, CODECO's ALTO-basednetwork awareness enabled more efficient placement of media delivery caches and fasteradaptation to network disturbances than a static Kubernetes deployment. In P4, thedecentralised energy management system achieved the targeted 5–10% improvements inenergy efficiency and carbon footprint reduction across three UPM campuses, with faulttolerance validated at the 2-minute recovery target. In P5, CODECO demonstrated reducedCPU consumption, more stable communication patterns, and successful stateful SLAMmigration on physical AMR hardware, with all operational KPIs addressed or partiallyevidenced. In P6, automated deployment and event-driven redeployment — triggered bytopology changes and occupancy-derived BLE statistics — demonstrated a class of adaptivesmart building management that would be practically unachievable through manual operation.Cross-pilot analysis of CODECO component engagement reveals that ACM and NetMA werethe universal foundation of the framework across all six pilots, while SWM provided workloadmigration capabilities in five, PDLC provided learning-based orchestration intelligence in four,and MDM provided data-flow observability in three. The variation in component engagementreflects the genuine diversity of the pilots rather than incomplete integration: each partnerengaged the subset of CODECO's capabilities that matched their application's operationalrequirements, and in several cases — P4's energy-domain integration, P6's Virtual Kubeletlayer — developed custom bridging components that extended CODECO's reach intopreviously unsupported device classes and data modalities.