Rapti Feed Fleet — Fuel Integrity & Mileage Intelligence System

This case study demonstrates the engineering of a fuel and mileage intelligence system for Rapti Feed Industries' vehicle fleet, solving a deceptively hard problem: a single tank fill can cover three trips, or one trip can need two top-ups. Built using Next.js, MongoDB, React Query, and NextAuth, the platform uses a full-to-full interval method, accumulating liters in a running per-vehicle bucket until a driver marks a fill as complete, then computing real mileage against a baseline.

Results are automatically flagged Normal, Over-used, Excessive, or Check when the numbers look suspiciously good, a soft signal for siphoning or a bad odometer reading, with parallel trip logs cross-checked against odometer deltas as a built-in sanity check. The complete technical implementation highlights anomaly-detection logic and fleet-data engineering tailored for operational accountability.