TPDDL Non-Technical Loss (NTL) Detection Portal
Production-grade FastAPI & AI Command Portal for Tata Power DDL that transforms raw smart meter signals into a probability-ranked enforcement hit-list for targeted electricity theft raids.
Non-Technical Losses (NTL) - electricity theft, meter tampering, and billing fraud - represent major operational costs for Tata Power DDL. Manual field inspections are expensive (₹1,500–₹5,000 per raid) and inefficient when unguided. Unranked suspect lists and high false-positive raids ('dry rolls') waste significant resources.
Built a production-grade FastAPI & ML Command Portal powered by scikit-learn (Logistic Regression L2) with skops safe serialization. Precision-first threshold calibration (0.6725) was performed against physical field audit ground truth to satisfy a 65%+ operational audit precision floor. The portal delivers a real-time, probability-ranked enforcement hit-list with High/Medium/Low risk tiers, interactive Plotly.js charts, and Supabase Cloud DB audit logging.
- →73.4% Audit Test Precision - comfortably exceeding the 65% operational floor for field raids
- →97.2% Test Recall - delivering near-complete coverage of real electricity theft cases
- →0.9696 PR-AUC score evaluated against physical field audit ground truth
- →Calibrated optimal decision threshold (0.6725) to minimize high-cost false positive raids
- →Automated cloud audit logging via Supabase DB for all user authentications and inference events
- →Single Page Application (SPA) command portal with interactive evaluation charts & risk-tiered hit-lists
- 01Threshold calibration against physical field audit ground truth drastically outperforms raw noisy recorded labels
- 02Enforcing a strict operational precision floor (65%) directly optimizes ROI by eliminating wasteful 'dry roll' raids
- 03Skops serialization enables safe model loading in production Python APIs without pickle vulnerability risks
- 04Supabase DB with local SQLite fallback ensures continuous audit logging resilience