Airline Anomaly Detection Engine

Statistical anomaly detection across five major U.S. carriers using z-score analysis on DOT operational data. Adjust the sigma threshold and filters to surface unusual performance periods.

Detected Anomalies

DateAirlineMetricValueMeanZ-ScoreDirectionSeverity

How This Was Built

This dashboard is a fully self-contained HTML application that performs real-time statistical anomaly detection on U.S. airline operational data — no server, no build step, no dependencies beyond a single CDN-hosted charting library.

Data

  • Monthly operational metrics for American, Delta, United, Southwest, and Frontier airlines spanning January 2022 through December 2024 (36 months per carrier).
  • Sourced from the DOT Bureau of Transportation Statistics T-100 Domestic Segment database and On-Time Performance tables.
  • Five metrics tracked: On-Time %, Cancellation Rate, Diversion Rate, Average Delay (minutes), and Total Flights.

Anomaly Detection

  • Uses z-score analysis: for each airline + metric combination, the engine computes the rolling mean (μ) and standard deviation (σ) across the selected time window.
  • Any data point where |z| ≥ threshold is flagged as anomalous. The user-adjustable sigma slider (1.0–3.5) controls sensitivity.
  • Anomalies are classified by severity: High (≥ 3σ), Medium (2–3σ), or Low (below 2σ).
  • All computation runs client-side in plain JavaScript — no Python, no backend, no API calls.

Visualization

  • Chart.js 4.4 renders the interactive time-series chart with per-airline trend lines and anomaly markers.
  • Anomaly points are drawn as enlarged, highlighted scatter points overlaid on the line series.
  • KPI summary cards update dynamically as filters change, showing total anomalies, most-affected carrier, highest z-score, and data coverage.

Architecture

  • Single-file HTML — all CSS, JavaScript, and data are embedded inline.
  • Dark theme (#090c14) with responsive sidebar layout that collapses on mobile.
  • Deployed as a static page on Netlify — zero infrastructure, instant global CDN delivery.

Stack

  • HTML5 / CSS3 / JavaScript (ES6+) — no frameworks, no transpilation
  • Chart.js 4.4.1 — time-series visualization
  • Statistical Methods — z-score anomaly detection, descriptive statistics