DIMCOST uses AI for concrete damage detection: cracks, spalling and efflorescence are detected, measured and classified automatically in large photo sets. Results are linked to lab data and compiled into standardized reports, with up to 70% less reporting time and full engineering control.
Every inspection produces large photo sets that someone has to go through by hand.
Different inspectors classify the same damage differently.
Compiling photos, defect maps and lab results into a report takes days.
Engineers spend their time sorting photos instead of evaluating solutions.
With AI concrete damage detection, the software handles the repetitive work and your engineers keep control of the conclusions. In four steps.
Identify, measure and classify surface cracks, spalling and efflorescence in high-resolution photo sets. Photos can come from your own inspections or from drone captures by Medexon.
Consistent classification: the same criteria are applied to every photo.
Measured defects: cracks and damaged areas are quantified, not just marked.
Correlate surface anomalies detected by AI with the underlying material test results.
Below the surface: link visible damage to internal chloride concentrations and carbonation depth.
Better diagnosis: see whether damage is cosmetic or a sign of reinforcement corrosion.
Compile raw field data, AI defect maps, 3D imagery and lab analytics into standardized engineering reports.
Up to 70% less reporting time: less administration and faster delivery.
Standardized output: the same structure for every report and every asset.
Critical structural zones are highlighted automatically.
Focus on what matters: experts evaluate solutions instead of sorting thousands of photos.
Full engineering control: your engineers review the results before conclusions are drawn.
Large photo sets processed in a fraction of the time.
Objective, repeatable defect classification.
Standardized reports generated automatically.
More time for analysis and decisions.
That want to process large photo sets quickly.
That want consistent, well-documented damage assessments.
Who want faster, comparable insight into the condition of their structures.
See how DIMCOST uses AI damage detection on cooling towers, tunnels and silos.
Surface cracks, spalling and efflorescence in high-resolution photo sets.
No. AI does the repetitive work of sorting and measuring. Engineers keep full control and review the results before conclusions are drawn.
Automated report generation cuts administrative reporting time by up to 70%.
Yes. Surface damage detected by AI is correlated with material test results such as chloride concentrations.
Tell us what type of structure it is and which photos or inspection data you already have. We’ll show you what concrete damage detection finds in them.
