Abstract
Although with the advent of the LEDs the energy consumption in buildings can be reduced by 50%, there exists a potential for energy savings due to lighting controls. Moreover, lighting controls can ensure that the near zero energy requirements by EU can be achieved for near zero energy buildings (nZEBs). For this reason, more sophisticated lighting controls must be proposed in order to take full advantage of LEDs and their flexibility concerning dimming. This paper proposes the architecture of an embedded computer camera controller for monitoring and management of image data, which is applied in various control cases, and particularly in digitally controlled lighting devices. The proposed system deals with real-time monitoring and management of a GigE camera input. An in-house developed algorithm using MATLAB enables the identification of areas in luminance values. The embedded microcontroller is part of a complete lighting control system with an imaging sensor in order to measure and control the illumination of several working areas of a room. The power consumption of the proposed lighting system was measured and was compared with the power consumption of a typical photosensor. The functional performance and operation of the proposed camera control system architecture was evaluated based upon a BeagleBone Black microcontroller board.
Highlights
Lighting is energy-intensive since the amount of energy consumed for lighting purposes corresponds to 20–40% of the total energy consumption in buildings [1,2,3]
The purpose of this paper is to present a novel system, that can be exploited in digital lighting control and consists of an AVT GigE camera control system [41] with a Fujinon
The system development was based upon a microcontroller board that supports such communication mechanism in real time
Summary
Lighting is energy-intensive since the amount of energy consumed for lighting purposes corresponds to 20–40% of the total energy consumption in buildings [1,2,3]. The heat of the luminaires indirectly influences the total energy balance of a building, by increasing the load of the cooling system. The reduction of the lighting load results in an additional reduction from 10% to 20% of the energy consumed for air-conditioning. Investing in energy-efficient lighting is one of the most effective ways to reduce CO2 emissions [4]. Today there exists a rapid development of such systems towards intelligent control units. Applications based on ARM processors and Linux operating systems in system automation are very popular [5,6].
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