Use Case #1
Data for Crane Safety
Imagine detecting every crane movement with near-perfect precision, before any risk becomes reality.
Challenge
Real-world data for training AI to accurately segment crane for further analysis is scarce, expensive, and slow to collect.
Approach
By building a realistic virtual construction site, we simulate thousands of real-world scenarios, from extreme weather to rare crane deformation, generating over tens of thousands of photorealistic synthetic images with perfect mask annotations in a fraction of the time and cost. We train a segmentation model only with our synthetic data and apply it in real-world.
Result
The result is a vision AI model that is accurate in crane segmentation, providing a strong foundation for crane movement analysis. Best of all, we estimated that we slashed data acquisition costs and labor in developing the AI model by ~80%.
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1. Generating synthetic data and annotations
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2. Training an AI model using only our synthetic data
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3. Segmenting real-world cranes