Automated Data Extraction and Digital Twin

The Department relies on accurate survey, imagery, and geospatial information to support transportation planning, project delivery, right of way activities, and asset management. Advances in mobile LiDAR, imagery collection, and edge computing present new opportunities to automate the extraction of engineering and survey information while reducing manual processing and accelerating project delivery.

Today, much of the information collected during field surveys requires significant post-processing to identify, classify, validate, and organize features for engineering and operational use. As the volume and complexity of collected data continue to increase, there is an opportunity to modernize these workflows through intelligent automation while maintaining the accuracy and quality required for transportation projects.

California seeks AI-enabled solutions that automate the extraction of engineering and survey information from imagery and LiDAR data and support the development of authoritative digital representations of transportation infrastructure. The Department is particularly interested in approaches that leverage edge AI to improve processing efficiency while supporting scalable workflows from field collection through digital asset development.

Solutions may address one or more of the following objectives:

• Automate the extraction and classification of engineering, survey, and right of way features from mobile LiDAR, imagery, and other geospatial data sources.
• Streamline the transition from raw field data to authoritative digital representations that support engineering analysis, project delivery, and lifecycle asset management.
• Support scalable processing architectures through edge AI, cloud, or hybrid computing environments that improve processing efficiency while maintaining data quality.
• Enable quality assurance and validation workflows that support independent verification of extracted information and improve confidence in automated data products.

California seeks scalable solutions that reduce the manual effort required to process survey and geospatial data while improving the speed, consistency, and quality of digital information supporting project delivery. The desired outcome is a modern workflow that accelerates the development of authoritative digital representations of transportation infrastructure, improves operational efficiency, and provides a foundation for future digital engineering capabilities.