As people spend most of their time indoors, the quality of the indoor lighting environment plays a crucial role in occupant health, mood, and productivity. While modern glazed curtain walls improve daylighting potential, they also heighten the risks of glare and associated solar heat gains that may result in occupant discomfort and overheating. To continuously ensure visual comfort while providing shading, kinetic responsive facades controlled by sensors and actuators can change the angles of the elements. Conventional control methods for shading devices mainly involve the unified control of each element. However, as each element of the kinetic responsive facade can be controlled independently, the number of potential control actions increases exponentially with the number of facade elements and possible angles. Traditional rule-based methods are challenging for handling this multi-objective high-dimensional control problem. This paper introduces a novel self-learning, real-time reinforcement learning (RL) controller that can interact with the environment to find a globally optimal control solution for each element in kinetic responsive facades, thereby meeting visual quality and shading goals. The configuration and workflow of the proposed RL controller are introduced and tested vertically, diagonally, and radially folding responsive facades. The results demonstrate that the proposed RL controller effectively maintains horizontal and vertical illuminance, with 72.92% of test points in occupied spaces falling within the defined comfort range. Additionally, it keeps the daylight glare probability (DGP) below 0.35, a level generally considered imperceptible.

This concept paper illustrates a new simulation method to assess how building facades distribute light into interior spaces and how data from simulation studies can inform design for better facade performance. Facade photometry, a term developed by the authors, uses annual simulations and localized weather data to create temporally based illuminance and luminance distributions. This photometric chart is a unique signature of a particular facade design measured at a specific point in a specific climate. By linking data from the daylight simulation to the facade, the areas of the facade that need to be adjusted for improved performance are highlighted. Facade photometry is intended to allow designers to easily compare the performance of complex building geometry and daylight control systems, thus becoming an efficient tool to further aid designers in creating highly energy-efficient, high-performance, and comfortable building facades.

This paper presents the use of panoramic 3D estimation in lighting simulation. Conventional lighting simulation necessitates detailed modeling as input, resulting in significant labor effort and time cost. The 3D layout estimation method directly takes a single panorama as input and generates a lighting simulation model with room geometry and window aperture. We evaluate the simulation results by comparing the luminance errors between on-site High Dynamic Range (HDR) photographs, 3D estimation model, and detailed model in panoramic representation and fisheye perspective. Given the selected scene, the results demonstrate the estimated room layout is reliable for lighting simulation.

Virtual staging technique can digitally showcase a variety of real-world scenes. However, relighting indoor scenes from a single image is challenging due to unknown scene geometry, material properties, and outdoor spatially-varying lighting. In this study, we use the High Dynamic Range (HDR) technique to capture an indoor panorama and its paired outdoor hemispherical photograph, and we develop a novel inverse rendering approach for scene relighting and editing. Our method consists of four key components: (1) panoramic furniture detection and removal, (2) automatic floor layout design, (3) global rendering with scene geometry, new furniture objects, and the real-time outdoor photograph, and (4) virtual staging with new camera position, outdoor illumination, scene texture, and electrical light. The results demonstrate that a single indoor panorama can be used to generate high-quality virtual scenes under new environmental conditions. Additionally, we contribute a new calibrated HDR (Cali-HDR) dataset that consists of 137 paired indoor and outdoor photographs. The animation for virtual rendered scenes is availablehere.