Smart lighting is one of the main applications enabling the Smart Home System of today. Automatic lighting control systems reduce energy consumption by decreasing the operating time of lamps based on various factors, for example, occupancy, time of day, availability of daylight and so on. This paper review the existing smart lighting control techniques and investigate an image-based smart lighting simulation tool. This image-based smart lighting simulation tool are using cloud images and indoor images to detect the daylight intensity and indoor occupancy for lighting control based on fuzzy inference system, which can be used to realize the Smart Light System in the context of a smart home.
Energy saving becomes the hot topic nowadays. Lighting becomes one of the energy saving target as it contributes the highest amount of electricity consumption in buildings. The use of lighting efficiently and effectively can offer major energy and cost saving. Besides energy saving, this project also aims to advance the technology of Smart Home System. Throughout this research, a lot of the limitations of traditional sensor-based system can be overcome by using cameras as sensors.
Different smart lighting control techniques are reviewed from the point of occupancy detection. Each smart lighting control techniques have their benefits and also weaknesses. A comparison of these smart lighting control techniques have been made to explain why image-based smart lighting solution was selected according to their sensitivity and accuracy. The investigation of the image-based smart lighting simulation tool will be explained on how the implementation was carried out and what techniques and tools had been used. The results will be analyzed and evaluated to draw a conclusion for this research paper and hope this paper could contribute for future work in the field of image-based smart lighting solution.