My research focuses on the application of artificial intelligence, computer vision, machine learning, and intelligent control systems to address real-world challenges in smart manufacturing, food processing, and intelligent transportation. Through the development of advanced deep learning models, including the YOLO family of object detection algorithms, my work explores automated quality inspection, real-time process optimisation, and adaptive decision-making systems. My publications span both fundamental reviews and applied research, covering AI-driven rice quality assessment, real-time rice milling automation, closed-loop industrial control, and intelligent urban traffic monitoring. Collectively, these studies demonstrate how modern AI technologies can improve efficiency, accuracy, sustainability, and automation across diverse industrial and smart city applications while bridging the gap between laboratory research and practical deployment. Explore these publications below.