Smart City Logistics: Leveraging AI for Last-Mile Delivery Efficiency

Urban environments face significant challenges in last-mile delivery, which is a crucial component of logistics. To address these challenges, we introduce a framework called Smart City Logistics, utilizing artificial intelligence (AI) to enhance delivery efficiency. The framework optimizes routing and improves resource allocation by analyzing real-time data from multiple sources, including traffic patterns and user preferences. The system employs machine learning algorithms for predictive analytics, enabling it to adjust in response to evolving demand. Furthermore, we investigate the integration of AI with advanced infrastructure, such as smart traffic signals and autonomous delivery drones, fostering a more agile delivery network. Case studies across various cities reveal substantial improvements in both delivery speed and operational costs, showcasing AI’s transformative impact on logistics and its potential for sustainable urban delivery solutions.

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Publication Details

Published
2025-03-21
DOI
https://doi.org/10.1109/iscait64916.2025.11010309
Citations
2
Primary Topic
Urban and Freight Transport Logistics
Type
article
Field-Weighted Citation Impact
2.01
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article

Smart City Logistics: Leveraging AI for Last-Mile Delivery Efficiency

Jian‐Sheng Wang
2 citations
Urban and Freight Transport Logistics
2.01
article

Smart City Logistics: Leveraging AI for Last-Mile Delivery Efficiency

Jian‐Sheng Wang
article en
2 citations

Abstract

Urban environments face significant challenges in last-mile delivery, which is a crucial component of logistics. To address these challenges, we introduce a framework called Smart City Logistics, utilizing artificial intelligence (AI) to enhance delivery efficiency. The framework optimizes routing and improves resource allocation by analyzing real-time data from multiple sources, including traffic patterns and user preferences. The system employs machine learning algorithms for predictive analytics, enabling it to adjust in response to evolving demand. Furthermore, we investigate the integration of AI with advanced infrastructure, such as smart traffic signals and autonomous delivery drones, fostering a more agile delivery network. Case studies across various cities reveal substantial improvements in both delivery speed and operational costs, showcasing AI’s transformative impact on logistics and its potential for sustainable urban delivery solutions.

Carnegie Mellon University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 14%
Urban and Freight Transport Logistics
2.01
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Smart City Logistics: Leveraging AI for Last-Mile Delivery Efficiency — Jian‐Sheng Wang · (2025) | TGRS Research Map | TGRS