Due to advances in today’s sensing and mobile technologies, more and more data can be easily and effectively collected by various and advanced means. It is now feasible to collect and process big data about environmental satisfaction levels of a building’s occupants in real time and non-invasive manners. A human body naturally reacts to ambient environmental conditions to minimize any environmental stress, based on its autonomic nervous system and expressed by different poses. Therefore, the goal of this special issue is to enhance the interdisciplinary knowledge (i.e., AI, IoT, big data, deep learning, computer vision) to advance building indoor environmental sensing and control technologies as a function of human bio-signals (i.e., physiological signals) and poses. To identify intellectual challenges and research gaps, state of the art research results in the following research areas are welcomed to achieve building energy efficiency by smart sensing and control.