System Architecture & Scientific Methodology

Full technical disclosure of HazeMY’s machine learning methodology, evaluation benchmarks, and operational boundaries.

The Problem

Haze exposure varies by time and place. Official monitoring provides authoritative station-based conditions, while route-level planning requires a separate, explicitly modelled decision-support layer.

The HazeMY Solution

HazeMY bridges atmospheric science and geospatial routing. By integrating chronological machine learning (T+3h PM2.5 forecasting), multi-factor risk scoring, and a 70/30 commute penalty engine, it provides actionable travel decision support.

Audited Model Performance Benchmarks

Evaluated using strict chronological splits on 11,025 valid T+3h records from five Klang Valley locations (June–August 2024). Models are strictly evaluated without temporal leakage.

Model ArchitectureMAE (µg/m³)RMSE (µg/m³)R² ScoreStatus
Persistence Baseline12.19417.4250.203Benchmark
Linear Regression9.80313.3230.534Baseline
Random Forest7.60210.7870.695Evaluated
XGBoost (Application Model)7.46210.5580.707Deployed & best

*XGBoost recorded the strongest test-set performance among the evaluated models and is the deployed model. Figures are read from models/model_metadata.json.

Scientific Boundaries & Methodological Limitations
  • Training Data Scope: June–August 2024 covering 5 Klang Valley locations (11,025 valid T+3h rows). The model is not nationwide.
  • Data Nature: PM2.5 target is based on CAMS/Open-Meteo numerical atmospheric estimates, not roadside BAM physical sensors.
  • Spatial Approximation: Route-level environmental matching uses spatial nearest-hub approximation (~1.2 km segments), not microclimate roadside sensing.
  • Decision Support Only: HazeMY provides application-level decision-support scoring. It does not calculate inhaled dose or physiological burden.
  • Temporal Scenarios: Departure What-If analysis evaluates diurnal features against the latest environmental baseline; it is not a guaranteed future forecast.
  • Official Status: HazeMY notifications do not replace official Malaysian APIMS (DOE) air quality warnings or MOH public advisories.