AI-Powered Blueprint Symbol Extractor & Room Mapper
Automating electrical takeoffs and spatial inventory with YOLOv8 and geometric boundaries.
The Friction
Pre-construction estimators spend countless hours manually scanning multi-page PDF blueprints to count electrical fixtures (such as receptacles, junction boxes, and outlets) and mapping them to their corresponding room IDs. This manual process is extremely slow, prone to human oversight, and bottlenecks bid submissions, resulting in missed project opportunities. Contractors need a way to instantly extract and localize fixtures to accelerate estimates, reduce risk, and submit bids faster.
The Neural Architecture
We deployed a custom object detection and spatial mapping pipeline. The system utilizes a fine-tuned YOLOv8 model to locate electrical symbols, extracts room layout polygons and IDs directly from PDF text streams using PyMuPDF, and runs a Voronoi geometric partition algorithm to assign each detected symbol to its proper room boundary automatically.
Tech Stack Deployed
Impact Report
- Achieved over 92% accuracy in autonomous symbol counting.
- Reduced takeoff processing time from hours to less than 60 seconds per sheet.
- Automatically mapped 100% of symbols to their exact room numbers, outputting structured inventory data.
- Eliminated manual data entry errors in Excel scheduling reports.