Cloud-Based parallel implementation of an intelligent classification algorithm for fault detection and diagnosis of HVAC systems

Artificial Immune Recognition System (AIRS) is an algorithm inspired by animal immune system in the biological world. It is specialized in solving pattern recognition problems. Heating, Ventilation and Air Conditioning (HVAC) systems are widely installed in modern buildings to provide the occupants with a satisfactory indoor environment. HVAC systems are the some of the most power consuming equipment in buildings, and a malfunctioning HVAC system will consume more energy and lead to an uncomfortable indoor environment. Thus, efficient Fault Detection and Diagnosis (FDD) of an HVAC system is essential for achieving energy savings. Cloud computing is a recently emerging research area that allows customers to use limited local computing resources to solve large scale computing problems. In this paper, a cloud based on OpenStack is utilized to host the AIRS in handling the FDD problem for an HVAC system simulated in Trnsys.