On 1-2 July 2026, the EdgeAI consortium gathered in Reims, France, for the project’s Final Review Meeting, marking the successful completion of 3.5 years of collaborative research and innovation under the Chips Joint Undertaking. During the meeting, partners presented the project’s key achievements, demonstrated the final technology developments through live demonstrations and highlighted the impact of EdgeAI in advancing trustworthy, energy-efficient and intelligent AI solutions at the edge.
As a project partner, ITML contributed both to the project’s strategic dissemination activities and to the development of innovative Edge AI technologies for the mobility domain.
On the project management and communication side, ITML led WP7, coordinating the project’s communication, dissemination and stakeholder engagement activities. Throughout the project, ITML was responsible for maximizing the visibility and impact of EdgeAI by coordinating communication campaigns, managing the project’s digital presence, organizing dissemination activities, promoting scientific and industrial results and supporting collaboration with the wider European Edge AI ecosystem.
From a technical perspective, ITML actively contributed to Value Chain 4 (VC4) – Mobility, with a particular focus on Demonstrator VCD4.2: Roadside Perception Units (RSPUs) connected through a LoRa 2.4 GHz Mesh Network, supporting the development of AI-enabled edge intelligence for smart mobility applications. The demonstrator combined distributed sensing, edge AI processing and resilient wireless connectivity to enable real-time perception and collaborative decision-making in intelligent transportation environments.
During the live demonstrations at the Final Review Meeting, ITML showcased two of its AI-powered solutions developed within VCD4.2:
- Health & Performance Anomaly Monitoring (HPAM): an intelligent monitoring solution that leverages Artificial Intelligence to continuously assess system health, detect anomalies at an early stage and improve the reliability and availability of edge systems.
- Air Quality Index (AQI): an AI-enabled environmental monitoring application based on collaborative and privacy-preserving learning techniques, allowing distributed edge devices to jointly improve air quality prediction while keeping sensitive data local.
ITML is proud to have contributed to the success of this ambitious European initiative and looks forward to building upon the knowledge, technologies and collaborations established through EdgeAI in future research and innovation projects.