Abstract
ABSTRACT The use of AI technologies in Smart Buildings is increasing as there are wide-scale benefits that can be derived from improving the efficiency of a building's operation and management. Buildings currently account for around 40% of global energy use, with AI technologies offering the opportunity to significantly reduce energy consumption through better automation, control, and reliability. These technologies can also be utilised to improve the safety and comfort of building occupants. This paper provides a literature review of research that has been conducted into AI technologies for use in Smart Buildings across the major AI topics including expert systems, fuzzy logic, genetic algorithms, machine learning, machine vision, natural language processing, neural networks, and pattern recognition. This process resulted in the determination that the volume of research conducted to-date is skewed towards some AI topics such as machine learning, neural networks and pattern recognition over other topics such as deep learning and natural language processing. It has also served to provide insights into which areas are likely to benefit the most from focusing future research efforts in that direction.
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