Smart Building Control for Energy‑Efficient and Low‑Carbon Cities

Smart building control has emerged as a critical enabler of energy efficiency, occupant comfort, and sustainable urban development. Advances in sensing technologies, Internet of Things (IoT) devices, artificial intelligence, and data analytics now allow buildings to operate as intelligent, adaptive systems rather than static infrastructures. By integrating real-time monitoring, predictive control, and automated decision-making, smart control strategies can significantly reduce energy consumption, carbon emissions, and operational costs while enhancing indoor environmental quality. As buildings account for a substantial share of global energy use, innovative control approaches are essential to achieving climate goals and developing resilient, human-centric built environments.The goal of this Research Topic is to advance the state of the art in smart building control by bringing together innovative research, practical implementations, and interdisciplinary perspectives. It aims to explore novel control strategies, data-driven methods, and intelligent optimization techniques that enhance energy efficiency, flexibility, and occupant well-being. Contributions addressing integration of renewable energy, demand response, digital twins, cybersecurity, and human-in-the-loop control are particularly welcome. By fostering collaboration among researchers and engineers across energy systems, building science, and data-driven control. This issue seeks to accelerate the deployment of scalable, resilient, and sustainable smart building solutions for future low-carbon cities.This Research Topic welcomes original research articles, review papers, and case studies addressing theoretical developments, modeling approaches, experimental validation, and real-world applications in smart building control. Topics of interest include, but are not limited to:- Advanced control algorithms for building energy systems, - Machine learning and data‑driven methods for smart building control, - Model predictive control techniques, - Occupant-centric control strategies, - Intelligent building energy management systems,- Digital twins for monitoring, simulation, and operational optimization, - Building-grid interaction and demand response, - Cybersecurity in building automation.Interdisciplinary contributions bridging engineering, data science, and architecture are encouraged. All submissions will undergo rigorous peer review in accordance with the journal’s standards. Authors should prepare manuscripts following the journal’s formatting guidelines and submission procedures available on the journal website. Topic editors: Xilei Dai, Kate Qi Zhou Source: https://www.frontiersin.org/research-topics/79074/smart-building-control-for-energy-efficient-and-low-carbon-cities