Solutions for Residential Building
Automated Scan2BIM via 3D laser point
Delivering centimeter-accurate scans to smart maintenance for residential buildings, driving safety and digital transformation
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Integrated Scan2BIM Reverse Modeling
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We use AI and foundation model to provide the infrastructure industry
with high-precision engineering-ready digital models
with high-precision engineering-ready digital models
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The core technology of the German Railway case applies the semantic segmentation function of Wolken Analytics, the core technology of the German Railway case applies the semantic segmentation function of Wolken Analytics, the core technology of the German Railway case applies the semantic segmentation function of Wolken Analytics,
Solutions
The core technology of the German Railway case applies the semantic segmentation function of Wolken Analytics, the core technology of the German Railway case applies the semantic segmentation function of Wolken Analytics, the core technology of the German Railway case applies the semantic segmentation function of Wolken Analytics,
Solutions
The core technology of the German Railway case applies the semantic segmentation function of Wolken Analytics, the core technology of the German Railway case applies the semantic segmentation function of Wolken Analytics, the core technology of the German Railway case applies the semantic segmentation function of Wolken Analytics,
Industry Pain Points
2D Design
Limits
Flat drawings obscure spatial relationships, increasing errors.
Aging Data
Gaps
Renovations rely on rough measurements, risking structural misjudgments.
Hidden
Hazards
Walls and internal defects require destructive testing, raising costs.
Data
Silos
Isolated project phases slow decisions with document-driven workflows.
Key Technologies
Segmentation
Point Cloud Processing
Semantic Modeling
Using deep neural networks to perform high-precision semantic segmentation of residential building point clouds and images, automatically identifying key components such as walls, doors and windows, stairs, and roofs.
Combined with rule-based post-processing to optimize the results, this approach provides comprehensive and accurate semantic data support for geometric reconstruction and functional analysis.
Deep neural networks enable high-precision semantic segmentation of residential point clouds and images,
automatically identifying walls, doors, windows, stairs, and roofs with rule-based post-processing
to deliver comprehensive, accurate semantic data for geometric reconstruction and functional analysis.
Neural networks classify room functions while detecting performance risks (lighting/CFD/energy), producing BIM-integrated reports for data-driven facility management.
Product Process
Deeply aligned with user needs, building an optimized experience closed-loop operation
Business Values
Innovative spatial data production methods balancing precision, cost and experience
Precision Modeling
Cloud-based semantic segmentation and AI reconstruction
Delivering 1:1 digital twins for reliable design/construction data
Delivering 1:1 digital twins for reliable design/construction data
Risk Control
Proactive structural risk detection
Shifting accident prevention from reactive to predictive
Shifting accident prevention from reactive to predictive
Green Enablement
Optimizing material use and digital archives
Supporting sustainable retrofits
Supporting sustainable retrofits
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We use AI and foundation model to provide the infrastructure industry
with high-precision engineering-usable digital models
with high-precision engineering-usable digital models
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