Optimizing Inventory in Outdoor Warehouses: A Drone-Based Approach Using Photogrammetry and Computer Vision

Steffen Meeuw ()
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Steffen Meeuw: Carl von Ossietzky Universität Oldenburg, Department of Computing Science

A chapter in Recent Advances in Information Systems, 2026, pp 15-30 from Springer

Abstract: Abstract Efficient inventory management is critical for modern supply chain operations, yet traditional manual inventory processes in warehouses remain labor-intensive, often prone to human error due to their repetitive nature, and costly. While drone-based inventory auditing has demonstrated effectiveness in indoor warehouses, its application to outdoor warehouses remains underexplored. Unique challenges such as the absence of fixed orientation points and the diverse nature of stored products hinder straightforward adoption. This paper addresses these challenges by introducing a novel drone-based inventory system specifically designed for outdoor storage environments, where products are stored on handling units such as pallets. To ensure broad applicability, an abstract spatial representation of outdoor warehouses is developed. The proposed system integrates photogrammetry and computer vision techniques to capture aerial and front-view images, enabling automated inventory recognition and digital warehouse modeling. A real-world field experiment compares the drone-based inventory approach with traditional manual counting, demonstrating substantial improvements in efficiency, accuracy, and workforce optimization. The results indicate reduced labor dependency, enhanced digital traceability, and improved operational cost efficiency. While technical challenges affecting detection accuracy persist, this study contributes to scalable, automated inventory solutions, advancing supply chain digitalization in outdoor warehouse management.

Keywords: Inventory management; Computer vision; Outdoor warehouses; Drones; Photogrammetry (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-032-14099-9_2

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DOI: 10.1007/978-3-032-14099-9_2

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