A multi‐agent architecture for intelligent building sensing and control

Abstract

We describe a new approach to intelligent building systems, that utilises an intelligent agent approach to autonomously governing the building environment. We discuss the role of learning in building control systems, and contrast this approach with existing IB solutions. We explain the importance of acquiring information from sensors, rather than relying on pre‐programmed models, to determine user needs. We describe how our architecture, consisting of distributed embedded agents, utilises sensory information to learn to perform tasks related to user comfort, energy conservation, safety and monitoring functions. We show how these agents, employing a behaviour‐based approach derived from robotics research, are able to continuously learn and adapt to individuals within a building, while always providing a fast, safe response to any situation. Finally, we show how such a system could be used to provide support for older people, or people with disabilities, allowing them greater independence and quality of life.