Computer Vision + Applied ML
Real-Time Infrastructure Defect Detection
Built real-time anomaly detection and inspection systems integrating live drone feeds, ML predictions, and analytics dashboards.
90%
accuracy
4x
faster processing
30%
lower inspection costs
25%
faster stakeholder decision-making
The problem
Infrastructure inspection workflows are slow and costly when dependent on manual review.
What I built
Developed ensemble ML models and real-time analytics pipelines for structural defect classification.
Technical approach
- Knowledge distillation
- Ensemble ML
- Live video feed integration
- Analytics dashboards
- Report automation
Visuals
Detection pipeline
Dashboard mockup
Accuracy/latency metrics