Regenerative Logistics in Supply Chains using Computer Vision

Abstract

This paper provides an in-depth review of Computer Vision (CV) tracking systems in the logistics industry, emphasizing their significant role in transforming warehouse operations and supply chain management. With automation and digital transformation becoming essential in modern logistics, CV-based tracking technologies offer key benefits such as greater accuracy in inventory control, enhanced operational efficiency, and improved real-time supply chain monitoring. The review classifies existing studies on CV tracking technologies, exploring fundamental approaches, including object detection, barcode and RFID scanning, motion tracking, and deep learning-driven image recognition.
Additionally, concerns regarding data privacy, security, and surveillance in warehouse environments pose further barriers to large-scale implementation. It reviews existing research, points out challenges in using CV, and suggests future ideas to better integrate this technology, helping to create a smarter and stronger supply chain. By analysing these challenges and highlighting opportunities for future research and innovation, this paper seeks to contribute to the advancement of intelligent logistics solutions. The findings reinforce the potential of CV-driven automation to reshape supply chain operations and enhance efficiency in an increasingly competitive global market.