Machine Learning for Drone-Based Last Mile Delivery of Perishables

Selwyn Piramuthu ()
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Selwyn Piramuthu: University of Florida

A chapter in Smart Services Summit, 2023, pp 201-209 from Springer

Abstract: Abstract Last mile delivery of perishables is challenging in situations where necessary infrastructure to accomplish this task is lacking. However, the need for perishables, such as fresh blood for transfusion, does not disappear simply because of transportation-related issues. While last mile delivery has traditionally been done through ground-based modes, recent advances in drone-based technology calls for serious consideration of air-based delivery mode. In response to this call, current last mile delivery includes a mix of ground- and drone-based modes. In addition to the rest of the supply chain, the need to consider the last mile delivery aspect invariably renders the system more complex and requires the consideration of effective methods. Machine learning has been successfully used in complex systems. We therefore consider machine learning in various facets of last mile delivery scenarios with specific focus on classification, clustering, and optimization. We discuss possible applications of machine learning across these facets in drone-based last mile delivery of perishables.

Keywords: Drones; Last mile delivery; Machine learning; Perishables; Sustainability (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-031-36698-7_21

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DOI: 10.1007/978-3-031-36698-7_21

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