Improving Last Mile Delivery Efficiency with Advanced Machine Learning Models

Because of its wide range of applications and possibilities, artificial intelligence (AI) is becoming more and more significant in many sectors. Particularly in logistics, rising consumer expectations and rising cargo quantities are making it more difficult to predict delivery timeframes, particularly for the last mile. Efficient delivery systems increasingly need third-party logistics, which allows businesses to buy carrier services rather than a costly fleet of vehicles. Attended Home Delivery, the most popular e-commerce business model, is the most costly and timeconsuming when a small delivery window is mutually agreed upon with the consumer, reducing potential and maximising flexibility. However, last-mile logistics is evolving as choices need to be made instantly. Due to its complexity, the last-mile delivery phase—the last step in which items travel from a distribution centre to customers—faces considerable inefficiencies and high prices. New developments in Edge AI, also known as Edge Intelligence (EI), provide encouraging answers to these problems. This research investigates how EI, real-time data processing, and AI-driven technology might improve last-mile delivery operations. A comprehensive literature analysis was carried out to evaluate technical developments, and the effect of EI solutions on operational efficiency and customer satisfaction was systematically and experimentally evaluated using the Delphi technique. Despite the significant advantages of EI technology, EU businesses are reluctant to embrace these advancements because of the hefty implementation costs. Businesses who have used these technologies, however, claim significant gains, such as improved service dependability, shortened delivery times, and better route optimisation. These results emphasise the need of hiring professionals with advanced degrees and fostering an innovative culture in order to propel technical improvement in last-mile logistics. An important step towards last-mile delivery systems that are more effective, economical, and customer-focused is the integration of EI. Subsequent studies have to focus on improving these technologies and investigating their long-term effects on the logistics sector.