Abstract The need for efficient logistics management and supply chain optimization has grown with the rapid expansion of global trade and e-commerce. Traditional logistics methods often face inefficiencies, high costs, and slow response times, making it necessary to explore innovative solutions. This study integrates artificial intelligence (AI) and Internet of Things (IoT) technologies to optimize logistics processes in transportation and inventory management. By using the random forest algorithm, this research focuses on improving transportation route planning, reducing inventory costs, and enhancing order processing efficiency. Real-time sensor data from IoT devices such as GPS and RFID tags provided valuable inputs, ensuring accurate and up-to-date information for decision-making. The results demonstrate a 28 % reduction in transportation time, a 16.7 % decrease in fuel consumption, and a 20.2 % reduction in inventory holding costs. Additionally, customer satisfaction increased by 14.1 % points. These findings indicate that the integration of AI and IoT offers significant improvements in logistics management, presenting a promising avenue for cost reduction and enhanced customer service.
Chunling Yang (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: