Session Resource Guide
Infrastructure Intelligence Extraction Guide
A fillable worksheet to prioritize automated extraction workflows, set quality-control expectations and connect results to your systems of record. Complete it on screen, save it, print it or forward it to colleagues.
From Reality Capture to Infrastructure Intelligence
About this session
Capturing detailed infrastructure data is only the beginning; value emerges when imagery and point clouds become structured information staff can use daily.
This session examines how analytics and AI identify, measure, classify and monitor physical assets — pavement condition, signs, markings, sidewalks, poles, clearances, vegetation and street furniture.
It also covers integrating extracted results with GIS, asset management, work management, permitting, accessibility and inspection systems while maintaining quality control.
Suggested prompts
Think about these first
- Which inventory in your agency is most out of date right now?
- Estimate the annual staff hours spent manually collecting or updating that inventory.
- What confidence level would you need before acting on an AI-extracted result?
- Which compliance program (ADA, PROWAG, sign retroreflectivity) would benefit first?
- Where would extracted data need to land to actually change a workflow?
For the panel
Questions for speakers and panelists
- What extraction accuracy do you see in production, and how do you measure it?
- How much human review do you still perform, and at what sample rate?
- Which asset classes are reliably automated today, and which are not yet?
- How do you handle false positives and missed assets in the field?
- How did you integrate extracted results into your asset-management system?
- What was the measurable staff-time or cost reduction?
1. Workflows to automate
Identify where automated extraction removes the most manual effort.
2. Compliance and condition
3. Quality assurance and integration
Session notes
Space to capture what you hear during the presentations and panel discussion.