Artificial intelligence and networking in integrated building management systems

In recent years the emphasis has moved towards integrating all a building’s systems via centralised building management systems (BMS). To provide a more intelligent approach to the facility management, safety and energy control in building management systems (IBMS), this paper proposes a methodology for integrating the data within a BMS via a single multi-media networking technology and providing the BMS with artificial intelligence (AI) through the use of knowledgebased systems (KBS) technology. By means of artificial intelligence, the system is capable of assessing, diagnosing and suggesting the best solution. This paper outlines how AI techniques can enhance the control of HVAC systems for occupant comfort and efficient running costs based on occupancy prediction. Also load control and load balancing are investigated. Instead of just using pre-programmed load priorities, this work has investigated the use of a dynamic system of priorities which are based on many factors such as area usage, occupancy, time of day and real time environmental conditions. This control strategy which is based on a set of rules running on the central control system, makes use of information gathered from outstations throughout the building and communicated via the building’s data-bus.