Abstract
The rapid advancement of automation and artificial intelligence (AI) has transformed traditional industrial inspection processes. Smart inspection systems powered by computer vision (CV) are emerging as pivotal tools for enhancing accuracy, efficiency, and reliability in quality control and monitoring tasks. This paper reviews the principles, methodologies, and applications of computer vision-based inspection systems in manufacturing, healthcare, infrastructure monitoring, and logistics. It also discusses challenges, including data acquisition, computational complexity, and real-time processing, while providing insights into emerging trends such as deep learning-based defect detection and edge AI integration. By synthesizing recent research, this paper highlights how smart inspection systems improve operational efficiency, reduce human error, and pave the way for fully automated inspection environments.
Keywords: Computer vision, smart inspection, industrial automation, deep learning, defect detection, quality control, real-time monitoring.
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