This research developed an integrated human-centered framework for intelligent environmental control in a building. The physiological signals of the occupants, as well as their ambient environmental data, were integrated by using sensing agents (such as wearable as well as remote sensors) and embedded environmental sensors in the building. This enabled bio-sensing-driven multi-criteria decisions for determining building thermal and lighting system controls that potentially lowered energy usage while improving occupant comfort.
This human-centered approach provided a framework that 1) addressed sensor data processing and analysis challenges that were inherent in large and dynamic datasets generated from sensing agents; 2) developed methods for optimizing decisions and solutions to multiple-criteria problems pertaining to occupants’ preferences; and 3) established a human-centered control approach that was integrated with a conventional control system for building retrofits to enable real-time decision making and system optimization that enhanced energy-efficient operations and occupants’ comfort. Such a three-fold approach could lead to tailored building environmental control systems with the potential for dramatically improving the efficiency of a building’s performance, increasing sustainability, and leveraging informatics technology that improved the occupants’ quality of life.