Smarter workflow in civil engineering: This photo organizes itself

For civil engineers, a photo of an open trench, a building connection, or a coupling is more than just an image. It can document a section of a construction project, provide proof of completed work, or serve as the basis for billing. At cec Ingenieure GmbH, employees previously had to review the photos manually and assign them to the appropriate projects. Today, AI handles that task.

Smarter workflow in civil engineering: This photo organizes itself
cec Ingenieure and Deutsche Telekom have automated the documentation of project data. Using n8n and AI, photos can be automatically assigned to civil engineering projects. © GettyImages-1326076301_copyright_M-Production

cec Ingenieure GmbH has automated the documentation of image and project data together with Deutsche Telekom. Using n8n and AI, construction-site photos can now be assigned to the relevant civil engineering projects more quickly and consistently. Based in Feldkirchen near Munich, the company specializes in planning and surveying services for the expansion of telecommunications and energy networks. The automated assignment process provides a reliable basis for documentation, proof of work, and billing.

Civil engineering projects generate large volumes of construction-site photos. Until now, these images have largely had to be reviewed, classified, and assigned to individual construction orders manually. Together with cec Ingenieure GmbH, Telekom MMS developed an end-to-end AI-powered automation solution based on n8n. The Berlin-based startup specializes in digitizing repetitive workflows. Depending on the use case, different apps, interfaces, and services can be combined through a graphical user interface.

From construction-site photos to structured project documentation

In the automated process, AI analyzes photos taken at the construction site, identifies construction phases, routes, and components, and adds information such as location, time of capture, and project assignment. Using GPS data, images can be automatically assigned to specific buildings or sections of a construction project. A dedicated AI model trained with Azure Custom Vision recognizes typical objects and work steps in civil engineering, such as main routes, building connections, and specific components, and assigns the photos to the appropriate categories and projects. The files are also optimized for efficient storage. The processing is integrated into the existing Microsoft environment, including SharePoint and Power BI. Instead of storing photos manually in folders, metadata is used to structure them so they can be filtered, searched, and analyzed.

As a certified partner, Deutsche Telekom supports small and medium-sized businesses in purchasing licenses and in implementing and operating n8n-based automation solutions and process workflows.