Intelligent Lighting Control Providing Semi-Autonomous Assistance
Keywords:Intelligent lighting control, image recognition, CNNs, resident’s activity
Increasing resident’s comfort and reducing energy costs have always been two primary objectives of intelligent lighting control systems. It is quite difficult to provide control satisfying the level of individual comfort, sufficient illumination and the energy reduction goals simultaneously. However, finding the balance between resident’s preferred and recommended illumination for the current resident’s activity may be beneficial. This paper addresses the problem of ensuring semi–autonomous assistance in controlling the intensity of light sources. The proposed decision making algorithm allows to provide gradual adaptation to the recommended illumination according the resident’s activity. Resident‘s activity recognition is performed using one of the most popular models of deep learning, such as Convolutional Neural Networks (CNNs).
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