良好的照明規劃可讓空間舒適明亮，有效且均齊地引入自然光，除了避免眩光問題造成視覺上的不適感外，可以讓人與環境聯結，建立時間感，使人心情開朗和充滿活力與朝氣，更可以節省室內燈光的耗能。本研究的目標是透過百葉窗戶與室內燈具控制的即時模擬達成節能與視覺舒適的最佳室內照明。相較於市售自動控光系統使用數個測光點估算，無法確實量測室內光分布的均齊性，相關建築研究採用感測器迴路達成自動控制的作法更是需要仰賴專業知識擺設感測器，且控制過程需要持續反饋當前照明狀態來修正結果。而採用全場域生成渲染估算的模擬方法，則因單一控制估算需要數分鐘至數小時的計算時間，無法於實務上達到即時反饋。本研究在給定之建築場景、百葉窗戶位置、室內光源位置及耗能資訊、工作區域標註與室內觀測位置及方向後透過拆解窗戶控制與自然光源兩相依函數預計算複雜光線傳遞反應，以即時估算動態自然光環境下任意控制參數的照明結果，並使用最佳化分析法計算當前環境下符合節能且舒適照明目標的最佳控制參數，達成直覺且不仰賴控制反饋的開窗及燈光控制系統。為避免連續控制因快速照明變化帶來的不適感，本研究將上個最佳化控制結果作為下次最佳化分析的輸入來達成時序上連貫的控制。實驗設計中本研究根據建築師指示設計常見有日照需求的室內環境來驗證方法在各式日照時段及不同建築開窗方位下的最佳控制結果。

Good interior illumination can let residents and audience feel bright and comfortable. Introducing daylighting can make residents connect with time and environments but inadequate daylight guiding may result in daylighting glare. Nowadays, commercially available daylighting controllers using “spot measurement” cannot measure luminance distribution. Furthermore, predicting the lighting of a shot under controlled parameters using physically-based light transportation takes minutes to hours. This makes it impossible for real-time prediction and control. Traditionally, architects properly introduce daylights for perceptual comfort and energy conservation with a complex sensor-feedback control algorithm required precise placement of various sensors.
This work develops an intuitive and easily-installed one-step blind and light control framework which formulates illumination level, lighting distribution, and energy consumption as cost functions while real-time evaluating control-affected lighting using shadow mapping sun radiance reconstruction, visibility-convolved spherical harmonic sky lighting, and precomputed interior lighting. Our system can directly select the optimal control states using mesh adaptive direct searching while having the states of the previous period as initials for temporal control coherence to minimize mechanical adjustment and adapting discomfort. While testing on architect-recommended scenes and target surfaces with captured daylights and sun-window movements, our framework can automatically and optimally select blinds' and lights' states after easily and intuitively setting the environment, control states, and target surfaces and view points.

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