CLEAR

CLEAR project aims to address the growing challenges in integrating diverse, multimodal data into industrial AI systems and improving the reliability of their outputs. By leveraging advanced AI techniques and context-aware capabilities, CLEAR will boost and capitalize on the capabilities of Large Multi-Modal Models (LMMs) and Large Language Models (LLMs) to efficiently manage complex data inputs. This effort is expected to reduce operational costs, increase safety, and improve system reliability across sectors such as transportation, agriculture, manufacturing, and telecommunications. At its core, CLEAR seeks to tackle the limitations of current AI systems in processing a wide range of real-time, multi-modal data—including satellite and on-ground visual data, emergency response, geospatial, and time-series data—while minimizing issues like "hallucinations" in AI-generated outputs. The project aims to deploy AI solutions that facilitate rapid, reliable decision-making, resulting in cost savings, higher availability, and enhanced user satisfaction. By advancing multimodal integration and implementing context-aware tools for diagnostics and troubleshooting, CLEAR will improve business efficiency, and bolster Europe’s competitive edge in industries aligned with digital manufacturing and Industry 4.0.