AI-POWERED OBJECT DETECTION-BASED STREET LIGHT AUTOMATION: A STRUCTURE FOR INTELLIGENT AND SUSTAINABLE URBAN LIGHTING

Abstract

Energy consumption has significantly increased as a result of urbanization, especially for infrastructure related to public lighting. Because of their set schedules and inability to adapt to changes in the environment, conventional street lighting systems use a lot of energy. Artificial intelligence (AI)-driven smart street lighting systems with object identification techniques provide a viable answer to this problem. These systems increase safety and user experience while achieving energy savings via the use of adaptive control and real-time sensing. This study offers a thorough examination of AI-based street light automation systems that use object detection, talks about their multidisciplinary elements—from cutting-edge computer vision technologies to IoT integration—and assesses current models, difficulties, and potential future directions in this field.