Well-designed automated lighting control can take advantage of the natural light and save energy. Integration with a window shading system with blinds could enable a strategy that regulates the amount of natural light while maintaining occupants' visual comfort. Previous studies have developed various automated lighting and blind control systems. Most of the works directly take light level and glare index listed in lighting guidelines or previous studies as the control set point and the criteria to evaluate visual comfort. However, users have subjective preferences for lighting level, visual comfort, and moreover, for outside views and privacy. That is, the consideration for each user's need is required. The objective of this work is to develop an occupant-centered integrated lighting and blind control system using machine learning, sensor network, and control. For the implementation of the system, pyranometer, photometer, thermocouples, camera, and occupancy sensors are utilized to receive the environmental conditions, indoor and outdoor. The Arduino board is adapted for hardware control. By capturing occupants' interaction with the blind and lighting system and by learning the relationships between occupants' behavior and the environmental conditions, we build a preference profile of lighting and shading for each individual, and provide the feedback to regulate the control system. Through this work, an occupant can have a personalized optimal adjustment for the lighting and blind control based on her/his personal preferences. By considering personal preferences, the system can provide not only a user friendly but also an environmental friendly approach to control lights and blinds.
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