Artificial intelligent technique for power management lighting based on FPGA

Abstract EN

The modern technological advances gave rise to new intelligent ways of performance and management in various fields of our lives.

The employment of the artificial intelligent techniques proved influential in enhancing the technological developments and in meeting the demands for new, more efficient, more reliable and faster ways of performing activities and tasks.

Lighting systems are an important part of human life.

For this reason, it is important to reduce and manage energy consumption properly.

Light dimming paves the way for massive energy saving in lighting applications.

The options include simply reducing the output during the night and achieve maximum saving with variable dimming.

Advantage can be taken of off-peak times (no light needed) to reduce energy consumption significantly.

Pulse Width Modulation (PWM) technique is used as dimming method.

The proposed system offers intelligent management of lighting to reduce power consumption, extend lamp life and reduce maintenance.

In this work, we will be using multiple sensors such as light dependent resistor (LDR) and Motion Sensor (PIR) for LED dimming system to achieve intelligent LED lighting system to manage energy consumption.

The data collected by sensors is processed by Artificial Neural Network (ANN), which is implemented by using Field Programmable Gate Arrays (FPGAs), Spartan 3A starter kit that controls the 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 of the FPGAs, which can support the re-configuration necessary to implement the design.

VHDL program was used to describe the functions of all necessary components used.

Xilinx ISE 14.7 design suite and MATLAB R2012A were used as software tools to perform Spartan 3A starter kit program.

The Simulation results were obtained with Xilinx blocks found in MATLAB program.