Develop a working proof-of-concept that is capable of:Recognizing symbols, components, and connections in drawings and/or photos.Unambiguously identifying these visual elements and linking them to relevant data in a dataset/database.Enabling automated actions based on this, such as:Asset inventoriesValidation of drawingsHarmonization and standardization of drawingsRequirements for the solutionRecognition rate of at least 70% reliability on a representative dataset.Results must be unambiguous and reproducible: fewer reliable matches are preferable, above matches that requires additional validation.The solution should be scalable towards: an autonomous component that can act independently within a workflow (e.g., signaling missing assets or deviations).Why is this challenge important for our organisation?Unlocking Efficiency and Insight with AI-Powered Image Recognition at EQUANSAs a leading technical service provider, EQUANS manages and maintains a vast and diverse portfolio of customer assets. Implementing AI-driven image recognition transforms how we can interact with these assets—turning photos, drawings, and symbols into actionable data. By automatically identifying equipment, infrastructure elements, and schematic symbols, we can enrich our master data contextually, giving visual elements meaning and traceability.This capability reduces manual labor and site visits, enabling remote asset verification and condition monitoring. It enhances operational efficiency by accelerating asset registration, maintenance planning, and compliance checks.From a CSR perspective, image recognition supports safer, more sustainable operations—minimizing unnecessary travel, improving worker safety, and ensuring accurate documentation for environmental and regulatory reporting.Ultimately, this technology empowers EQUANS to scale smarter, respond faster, and manage assets with greater precision—delivering value across labor optimization, cost control, data quality, and customer satisfaction.

How can we contribute to sustainable innovations in smart buildings, focusing on new services, leveraging existing technologies, AI integration, and overcoming privacy challenges?