Optimizing Automotive Inventory Management: Harnessing Drones and AI for Precision Solutions

Qian Zhang, Dan Johnson, Mark Jensen, Connor Fitzgerald, Daisy Clavijo Ramirez, Mia Y. Wang

2025

Abstract

Inventory errors within the automotive manufacturing industry pose significant challenges, incurring substantial financial costs and requiring extensive human labor resources. The inherent inaccuracies associated with traditional inventory management practices further exacerbate the issue. To tackle this complex problem, this paper explores the integration of cutting-edge technologies, including UAV (Unmanned Aerial Vehicle) drones, computer vision, and deep learning models, for monitoring inventory in parking lots adjacent to manufacturing plants and harbors before vehicle shipment. These technologies enable real-time, automated inventory tracking and management, offering a more accurate and efficient solution to the problem. Leveraging drones equipped with high-resolution cameras, the system captures real-time imagery of parked vehicles and their components, while deep learning models facilitate precise inventory analysis. This forward-looking approach not only mitigates the costs associated with inventory errors but also equips manufacturers with the agility to optimize their production processes, ensuring competitiveness within the automotive industry.

Paper Citation

in Harvard Style

Zhang Q., Johnson D., Jensen M., Fitzgerald C., Ramirez D. and Wang M. (2025). Optimizing Automotive Inventory Management: Harnessing Drones and AI for Precision Solutions. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 1140-1145. DOI: 10.5220/0013284900003890

in Bibtex Style

@conference{icaart25,
author={Qian Zhang and Dan Johnson and Mark Jensen and Connor Fitzgerald and Daisy Ramirez and Mia Wang},
title={Optimizing Automotive Inventory Management: Harnessing Drones and AI for Precision Solutions},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={1140-1145},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013284900003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Optimizing Automotive Inventory Management: Harnessing Drones and AI for Precision Solutions
SN - 978-989-758-737-5
AU - Zhang Q.
AU - Johnson D.
AU - Jensen M.
AU - Fitzgerald C.
AU - Ramirez D.
AU - Wang M.
PY - 2025
SP - 1140
EP - 1145
DO - 10.5220/0013284900003890
PB - SciTePress