Computer vision based efficient real-time lighting control with Haar-cascade classifier

World energy requirement has steadily increased due to population growth, urbanization, and industrial advancement. The rise of smart cities and the need for energy-efficient systems is pushing significant advancements in intelligent lighting control technology. A key feature of these systems is their ability to control lighting of a premises according to the presence or movement of persons in certain areas. Computer vision-based object detection is a modern approach in advance lighting control system. Real-time lighting control with computer vision enables automated adjustments is not only reducing energy consumption but also enhancing user experience. This article is about implementation and analysis of lighting control, which is based on the Haar-Cascade classifier to improve energy efficiency through human occupancy detection. The developed system is simplified, efficient in computation, scalable, and modular. The Arduino-based control unit regulates lights via relay, according to human occupancy sensing. This research highlights the application of camera-based identification and motion tracking, illustrating the potential of intelligent energy-saving technology to significantly contribute to climate change mitigation and the establishment of a sustainable, eco-friendly future.