Scientometric analysis identifies trends in AI applications within smart buildings, suggesting future research directions.
With urbanization accelerating, Smart Buildings have garnered increasing attention, with artificial intelligence (AI) playing a vital role in their development. This study employs a scientometric approach to examine the current landscape and emerging trends of AI applications in Smart Buildings. It identifies three development phases: initial exploration (1992–2009), steady growth (2010–2019), and rapid development and adjustment (2020–present). Spatially, research is concentrated in China, the U.S. and the U.K. forming a tripolar pattern, though global participation remains uneven. Research hotspots have evolved from a focus on energy efficiency to broader applications including deep learning, digital twins, and reinforcement learning. A notable shift from technology-driven to human-centered approaches is observed. Collaboration networks show multi-centric structures, with strong institutional partnerships, though international cooperation still needs strengthening. This study offers a systematic overview of AI's integration into Smart Buildings and suggests future research directions.
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Luan et al. (2025) studied this question.