Computer Vision Based Auto-ID for Optimizing Logistics Operations

The increase in logistics demand has resulted in a rapid growth of logistics warehousing management. Enterprises need to manage not only their goods but also their flow and storage. Automatic Identification technology based on barcodes and RFID can help identify items in the supply chain quickly and automatically. However, using barcodes can be inefficient, and RFID technology has issues with false alarms in logistics operations. To address these limitations, we propose a new solution using computer vision techniques. This proposal aims to optimize the identification process with a new set of visual codes called Bleecker and a computer vision-based system architecture that can be implemented in any logistics warehousing management system. The proposed solution offers a cost-effective and practical alternative to RFID-based methods, overcoming the limitations of traditional identification technologies. The authors provide a comprehensive case study of the proposed system, which was implemented in a primary plant of a company that specializes in the production and packaging of fresh horticultural products.