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In the rapidly evolving landscape of logistics and warehousing, efficient inventory management is one of the most important issues. Forklifts, as indispensable tools in these environments, play an essential role, especially in the movement of goods. This paper introduces an innovative application of the You Only Look Once (YOLO) deep learning algorithm in the realm of visual warehouse management, specifically tailored for forklift operations. YOLO, as a state-of-the-art object detection algorithm applied to warehouse environment monitoring, can detect, classify, and track various items and obstacles in real-time. Our work presents the results of field trials and demonstrates the substantial improvements in warehouse management achieved through the implementation of YOLO-based visual perception of forklifts. The application not only streamlines inventory control, but also enhances safety, reduces operational costs, and ensures compliance with industry regulations. The innovative approach offers a holistic solution for real-time inventory monitoring, safety enhancement, and operational efficiency. It represents a significant stride towards the realization of smart, autonomous warehouses that promise to revolutionize the industry.
Keywords: Deep learning, warehouse operations, YOLO, object detection, forklift detection© This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.