Regional water corporation Société Wallonne des Eaux owns and operates a 50-meter-high water tower in Juprelle, Belgium, with a storage capacity of 500 cubic meters. Previous surveys revealed damage, so they took ground photos to assess the renovation work, but they couldn’t easily identify the most significant damage. To refine their methods and obtain a more insightful assessment of the water tower’s condition, they needed to apply photogrammetry, machine learning, and 3D modeling technology.
They selected ContextCapture to process over 3,000 images and generate a digital twin of the tower to visualize the entire structure and assess the damage. Using machine learning on the digital twin, they automated the accurate identification and quantification of the size of the cracks and determined the optimal corrective actions. The digital process reduced survey and modeling time and reduced costs. The digital twin could be completed in one day, enabling a quick assessment and remediation plan to ensure a reliable water supply.