Keywords:Adaptive Architecture, Cyber-Physical Systems, Robotic Building, Ambient Intelligence, Interior Environmental Quality
This paper presents a high-resolution intelligence implementation based on Design-to-Robotic-Operation (D2RO) principles and strategies specifically employed to attain and to sustain Interior Environmental Quality (IEQ) within a dynamic built-environment. This implementation focuses on two IEQ-parameters, namely illumination and ventilation; and is developed in three main steps. In the first step, a formal design-criteria based on D2RO principles is developed in order to imbue considerations of intelligence into the early stages of the design process. In the second step, illumination and ventilation systems are developed as IEQ-regulating mechanisms whose behavior is determined by machine-learning models that continuously learn from the occupants and their preferences with respect to interior environmental comfort. In the third and final step, the resulting implementation is tested with probands in order to demonstrate continuous intelligent adaptation with respect to illumination and ventilation, which in turn demonstrates that a D2RO approach to IEQ yields a more intelligent adaptive mechanism that promotes occupant well-being in an invisible, unobtrusive, intuitive manner.
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Copyright (c) 2017 Alexander Liu Cheng
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