Last-mile delivery is crucial but often plagued by inefficiencies and high costs due to its complexity. Recent advancements in Edge AI or Edge Intelligence (EI) present promising solutions to these challenges.
Edge Intelligence or Edge AI
Edge Intelligence or Edge AI moves AI computing from the cloud to edge devices, where data is generated. This is key to building distributed and scalable AI systems in resource-intensive applications. Accelerated by the success of AI and IoT technologies, there is an urgent need to push the AI frontiers to the network edge to fully unleash the potential of big data.
Edge computing involves capturing, storing, processing, and analyzing data closer to where needed to improve response times and save bandwidth. It is a distributed computing framework that brings applications closer to data sources, such as IoT devices, local end devices, or edge servers. The core idea of edge computing is that computing should occur near data sources. Edge computing could impact our society as significantly as cloud computing.
EI in last-mile operations
A recent study investigates how AI-driven technologies and real-time data processing, when integrated with EI, can improve last-mile delivery operations. A comprehensive literature review was conducted to evaluate technological advancements. Additionally, the Delphi method was employed to systematically and empirically assess the impact of EI solutions on operational efficiency and customer satisfaction.
European companies are reluctant
Despite the significant benefits of EI technologies, European companies are reluctant to adopt these innovations due to high implementation costs. However, firms that have embraced these technologies report notable improvements, including better route optimization, reduced delivery times, and enhanced service reliability. These findings underscore the importance of fostering a culture of innovation and recruiting experts with advanced qualifications to drive technological advancement in last-mile logistics.
Integrating EI marks a substantial step towards more efficient, cost-effective, and customer-centric last-mile delivery solutions. Future research should focus on refining these technologies and exploring their long-term impacts on the logistics industry.