Vireco builds an automated digital representation of HVAC behavior and uses it to forecast system response, optimize supervisory control decisions, and deliver auditable recommendations through existing building infrastructure.
The model captures how zones, air handling units, plant equipment, control setpoints, schedules, and external drivers interact over time. Inputs include internal BMS telemetry and exogenous signals such as flight schedules, weather, occupancy, and tariff structure. The objective is to represent operational cause and effect, not just correlate variables in a dashboard.
Airport HVAC is a coupled physical system with lag, thermal inertia, equipment limits, and changing boundary conditions. A physics-informed approach helps the platform stay reliable when conditions shift, because forecasts are grounded in system behavior rather than pattern matching alone. This supports better transfer across seasons, schedules, and operating regimes while preserving interpretability for operators.
Project thermal and electrical response under multiple candidate actions and external scenarios.
Enforce comfort bands, equipment limits, policy rules, and operational preferences before selecting actions.
Select recommendations that reduce cost and peak exposure while maintaining service levels and reliability.
Record each recommendation, model context, and resulting outcome to support auditing and iterative improvement.
Airports combine high HVAC intensity, strict comfort and reliability requirements, volatile demand patterns, and meaningful tariff exposure. They are a demanding proving ground for operational decision systems. Success here demonstrates the platform can perform in constrained, high-accountability environments where poor decisions are costly.
Vireco is deployed on top of existing building management infrastructure and data feeds. No new field hardware is required. The implementation process maps site topology, validates data quality, calibrates the representation, and then delivers bounded supervisory recommendations through existing operator workflows.
Every recommendation is accompanied by traceable inputs, forecast assumptions, expected impact, and measured outcome. This creates a defensible operational record for engineering, facilities, finance, and procurement teams that need evidence, not black-box claims.