An Intelligent Smart Lighting System Integrates IOT Technology with Deep Learning

Abstract

In present smart environments, an intelligent smart lighting system is essential for increasing user comfort and energy economy. This proposal suggests a cutting-edge smart lighting solution that combines deep learning algorithms with Internet of Things (IoT) technology to allow for automatic and adaptive lighting control. The sensing layer, network layer, and application layer make up the system’s three-layer architecture. Real-time environmental and occupancy data is gathered using a variety of sensors, including motion detectors and light sensors. For additional processing, the gathered sensor data is sent to a cloud or edge computing platform via wireless communication technologies including Wi-Fi, ZigBee, and Bluetooth. The system can automatically turn lights on or off or change brightness depending on user activity and ambient lighting conditions thanks to the use of deep learning models that analyse occupancy patterns and forecast ideal illumination levels. The experimental findings demonstrate that the suggested solution maintains efficient lighting performance while drastically lowering wasteful energy use. As a result, the combination of deep learning and the Internet of Things offers an intelligent, scalable, and effective lighting system that can be used in smart city applications, commercial buildings, and households.