Progress Monitoring AI
AI that automatically tracks construction progress using photos, videos, and sensor data.
Definition
Progress Monitoring AI uses computer vision to automatically track construction progress by analyzing site photos, drone footage, and 360-degree imagery. These systems compare actual site conditions to BIM models and schedules to calculate percent complete, identify delays, and verify work quality. This automates the time-consuming process of manual progress tracking and provides project stakeholders with accurate, real-time visibility into construction status.
In Depth
Progress monitoring tracks the actual completion status of construction work against the planned schedule. AI automates this tracking by analyzing field photos, drone imagery, and field reports to quantify the percent complete for each building element without relying on subjective superintendent estimates.
Examples
Automatically calculating percent complete from weekly drone captures
Comparing as-built conditions to BIM models to identify discrepancies
Generating progress reports from site photos without manual input
Nomic Use Cases
See how Nomic applies this in production AEC workflows:
Compatible Platforms
Nomic integrates with these platforms so you can use progress monitoring ai across your existing project data:
Frequently Asked Questions
Progress Monitoring AI uses computer vision to automatically track construction progress by analyzing site photos, drone footage, and 360-degree imagery. These systems compare actual site conditions to BIM models and schedules to calculate percent complete, identify delays, and verify work quality. This automates the time-consuming process of manual progress tracking and provides project stakeholders with accurate, real-time visibility into construction status.
Automatically calculating percent complete from weekly drone captures. Comparing as-built conditions to BIM models to identify discrepancies. Generating progress reports from site photos without manual input.
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