Occupant Comfort Analysis AI
AI prediction and optimization of occupant thermal and visual comfort.
Definition
Occupant Comfort Analysis AI predicts occupant thermal and visual comfort using environmental simulation and comfort models. It analyzes temperature, humidity, air movement, and lighting to optimize building systems for occupant satisfaction and productivity.
In Depth
Occupant comfort encompasses thermal comfort (temperature and humidity), visual comfort (daylighting and glare), acoustic comfort (background noise and privacy), and air quality. AI evaluates designs against the comfort criteria in ASHRAE 55 (thermal), IES standards (visual), and ASHRAE 62.1 (air quality) simultaneously.
Thermal comfort analysis goes beyond temperature to include radiant asymmetry (cold windows, hot walls), air velocity (draft from diffusers), and humidity. AI models these factors across the occupied zone, identifying areas where comfort conditions are compromised — the desk next to the curtain wall that experiences cold radiant asymmetry in winter, or the conference room that overheats in the afternoon because of west-facing glazing.
Examples
Analyzing thermal comfort
Predicting PMV/PPD
Optimizing indoor conditions
Nomic Use Cases
See how Nomic applies this in production AEC workflows:
Frequently Asked Questions
Occupant Comfort Analysis AI predicts occupant thermal and visual comfort using environmental simulation and comfort models. It analyzes temperature, humidity, air movement, and lighting to optimize building systems for occupant satisfaction and productivity.
Analyzing thermal comfort. Predicting PMV/PPD. Optimizing indoor conditions.
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