Design and Implementation of Warehousing Logistics Management System

In order to improve the efficiency and intelligent demand of warehouse logistics management, this paper proposes a design framework that integrates Internet of Things, big data and artificial intelligence technology, uses RFID and barcode to realize real-time inventory tracking, and combines machine learning algorithm to predict demand and set intelligent early warning. Through functional module integration and technical empowerment, the problems of traditional warehousing information lag and extensive inventory management are solved. The application case shows that the system can improve the warehouse delivery efficiency by 30%, the inventory accuracy rate is over 98%, and the order processing time is shortened to 4 hours, which provides effective support for enterprises to reduce operating costs and enhance the response ability of supply chain.