User-in-the-loop smart lighting control system

In commercial buildings, smart lighting control systems are applied to minimize the electrical energy consumption. These systems use occupancy and light sensor data to adapt artificial light in accordance with changing occupancy and daylight conditions. In these systems, the performance relies on a pre-calibration phase to achieve daylight adaptation of artificial light. Since the pre-calibrated value is achieved by artificial light, the changes of daylight and/or reflectance changes can cause deviations against desired illumination. For example, the deviation takes place when the daylight distribution is affected by the reflectance changes in the environment. Additionally, these systems cannot account for individual user preferences at the workplace in real-time. A contribution of this thesis is to introduce human interaction to the smart lighting control system, taking user’s satisfaction into account to achieve better performance in terms of the desired illumination. A proposed sensor-driven human-in-the-loop lighting control system is developed to incorporates user feedback in addtion to occupancy and light sensor inputs. Camera-based visible light communication (VLC) is applied for the user to identify the luminaires within its neighborhood by its smartphone camera. Also, the intensity sensed by the smartphone camera is used as the illumination information offered from the user. A control algorithm is designed that incorporates these user inputs along with occupancy and light sensor inputs to determine the dimming levels of the luminaires to achieve illumination levels acceptable to users. The performance of the proposed lighting control system is compared with the state-of-the-art lighting control system in an experimental office space environment.