Artificial Intelligent Technique for Power Management Lighting Based on FPGA


The modern technological advances gave rise to new intelligent ways ofperformance and management in various fields of our lives. The employment ofthe artificial intelligent techniques proved influential in enhancing thetechnological developments and in meeting the demands for new, more efficient,more reliable and faster ways of performing activities and tasks. Lighting systemsare an important part of human life. For this reason, it is important to reduce andmanage energy consumption properly. Light dimming paves the way for massiveenergy saving in lighting applications. The options include simply reducing theoutput during the night and achieve maximum saving with variable dimming.Advantage can be taken of off-peak times (no light needed) to reduce energyconsumption significantly. Pulse Width Modulation (PWM) technique is used asdimming method. The proposed system offers intelligent management of lightingto reduce power consumption, extend lamp life and reduce maintenance. In thiswork, we will be using multiple sensors such as light dependent resistor (LDR)and Motion Sensor (PIR) for LED dimming system to achieve intelligent LEDlighting system to manage energy consumption. The data collected by sensors isprocessed by Artificial Neural Network (ANN), which is implemented by usingField Programmable Gate Arrays (FPGAs), Spartan 3A starter kit that controlsthe light intensity of LED from changing the duty cycle of the PWM signals.FPGA was used to implement the design, because of the re-programmability ofthe FPGAs, which can support the re-configuration necessary to implement thedesign. VHDL program was used to describe the functions of all necessarycomponents used. Xilinx ISE 14.7 design suite and MATLAB R2012A were usedas software tools to perform Spartan 3A starter kit program. The Simulationresults were obtained with Xilinx blocks found in MATLAB program