Next-Gen AI-Embedded Vision Systems: Real-Time Optimization for Surveillance, Autonomous Vehicles, and Industry 4.0

AI-powered embedded vision systems are transforming visual data processing by enabling real-time decision-making across critical applications such as autonomous vehicles, industrial automation, and surveillance. This paper introduces a system that merges advanced machine learning algorithms with energy-efficient hardware, designed to optimize performance and minimize power consumption. The system achieves a detection accuracy of 94.5%, processes images at 30 FPS, and maintains computational efficiency at 2.5 MB/Watt. These results underscore the system’s effectiveness in real-time object detection with minimal latency. Despite these advances, challenges remain in maintaining accuracy under varying conditions and further optimizing the system. Future work will focus on improving robustness, exploring new applications, and integrating emerging technologies. This research highlights the significant impact and future potential of AI-driven vision technology, providing a framework for advancing capabilities in embedded vision systems.