Dear Colleagues,

Sensors, which provide key information for buildings, play a prominent role in built environment controls and building energy performance optimization. Sensors that are poorly designed, installed, calibrated, located, and maintained, may have great impacts on the built environment, indoor thermal comfort, building energy performance, building system operations, sustainability, and service life. Discussions on sensors, data processing, data analytics, environment, and system monitoring and control have become increasingly important for building science over the last few decades.

Moreover, with the rapid development of big data science, artificial intelligence, 5G, and the Internet of Things (IoT), the applications of advanced sensors (smart sensors, low-cost sensors, virtual sensors, soft sensors, occupancy sensors, wireless sensors, sensor network, etc.) and associated technologies (sensor fault detection, diagnosis, isolation, calibration and tolerance control, sensor fusion and data acquisition, data quality improvement, adaptively control, model predictive control, operational performance optimization, occupancy behavior identification, sensor placement optimization, etc.) have become critical components for intelligent buildings.

This Special Issue aims to gather recent developments and applications of advanced sensor technologies in various buildings and to provide researchers around the world with an opportunity to present state-of-the-art results as well as literature reviews. Topics of interest to this Special Issue include (but are not limited to):

• Sensor/actuator fault detection, diagnosis, isolation, calibration and tolerance control;
• Sensor fault impact analysis for buildings;
• Virtual sensors and soft measurement for fault isolation, occupancy identification, health state monitoring, and operational performance optimization in buildings;
• Sensor fusion, data acquisition and generation;
• Sensor placement optimization and feature learning;
• Applications of advanced deep-learning technologies in buildings (i.e., transfer learning, reinforcement-learning, deep neural networks, etc.)
• Explainable artificial intelligence (XAI) in buildings
• Data mining for building energy performance;
• Computer vision applications in buildings;
• Building energy simulation and model calibration;
• Renewable and sustainable energy control technology in buildings;
• Data quality;
• Digital twins;
• Smart sensor design for building service;
• intelligent mobile sensors, wireless sensors and sensor networks;
• Building model predictive control;
• Building life cycle cost management and carbon emissions analysis.

Prof. Dr. Guannan Li
Prof. Dr. Qianjun Mao
Guest Editors

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