The project Mobispaces, in which Eviden led T3.1 (Decentralized Acquisition and In-Situ Data Processing) as well as the whole WP3 related to Trustworthy & Transparent Data Governance, successfully passed its final review on 16th September. After 30 months of work, involving EDGE team colleagues, the project received excellent feedback from the reviewers. The meeting was held in Genova (Italy). 

The project results were explained in extensive detail through presentations of each work package and through several demo videos showcasing the Data Governance Platform, the AI-based Data Management for Green Data Operations, mobility-aware large-scale decentralized analytics and the application of these to all use case scenarios.

The main results produced by Eviden in the project include: 

• Providing a GitOps approach for deploying data services in edge scenarios, ensuring the latest service versions are always available.
• Integration of the complete data path from data gathering to processing, analytics and final metadata generation.
• Deployment of user defined AI data workflows in the most suitable target cluster and monitoring of the said workloads for allocation fine-tuning.
• Kubernetes multicluster operation across the entire project and work packages.

The project's results were successfully aligned with its objectives, earning positive feedback from the reviewers and the European Commission, who stated that the work performed was excellent and that the project had achieved all expected outcomes. 

R&D Spain contribution has been key to the project’s success, providing technical guidance and development for assembling the different data services under the project’s umbrella, as well as their migration to Kubernetes environments. The team also led the integration of two different pipelines across different work packages. These contributions include: 

• Leading the design of the Work Package 3 Data Pipeline for automatic data acquisition, processing and management from the edge to the cloud.
• Providing two new microservices that enable correct communication within the entire data path in the appropriate format.
• Providing a full telemetry solution to monitor the state of deployed workflows and deliver state feedback to the relevant smart allocation components.
• Leading and designing the Work Package 4 Integration Pipeline as well as contributing a new component responsible for the final execution of AI workflows on a specific multicluster target.
• Providing a multicluster solution for workload deployment, and a GitOps Solution that is fully integrated into the multicluster ecosystem and the project’s code repository.