Article citationsMore>>
Pasha, J., Elmi, Z., Purkayastha, S., Fathollahi-Fard, A.M., Ge, Y.E., Lau, Y.Y. and Dulebenets, M.A. (2022) The Drone Scheduling Problem: A Systematic State-of-the-Art Review. IEEE Transactions on Intelligent Transportation Systems, 23, 14224-14247.
https://doi.org/10.1109/TITS.2022.3155072
has been cited by the following article:
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TITLE:
Intelligent Decision-Making in Warehouse Management: How AI Automation Improves Inventory Tracking, Order Fulfillment, and Logistics Efficiency Compared to Drone Technology
AUTHORS:
Somil Nishar
KEYWORDS:
Warehouse Management, Artificial Intelligence, Automation, Inventory Management, Order Fulfillment
JOURNAL NAME:
Intelligent Control and Automation,
Vol.15 No.1,
February
1,
2024
ABSTRACT: This paper analyzes how
artificial intelligence (AI) automation can improve warehouse management
compared to emerging technologies like drone usage. Specifically, we evaluate
AI’s impact on crucial warehouse functions—inventory tracking, order
fulfillment, and logistics efficiency. Our findings indicate AI automation
enables real-time inventory visibility, optimized picking routes, and dynamic delivery
scheduling, which drones cannot match. AI better leverages data insights for
intelligent decision-making across warehouse operations, supporting improved productivity and
lower operating costs.