Application Research On Intelligent Stereoscopic Warehouse Management System

Intelligent warehouse management system is an important part of modern enterprise logistics and information flow management,and has important social and economic benefits.This paper combines the advantages of NB-IoT long-distance wireless transmission technology and the theoretical advantages of ant colony algorithm for optimal path planning,and designs an intelligent warehouse management system based on NB-IoT.The system consists of data acquisition subsystem,data transmission subsystem and data processing subsystem.The specific work is as follows:In the data collection subsystem,the cargo shape detection module has the collection function of the length,width and height parameters of the cargo.The shelf vacancy detection module has the function of updating and detecting shelf occupancy information.The intelligent vehicle real-time positioning detecting module has the real-time collection function of intelligent vehicle position information.The two-point positioning method is used to determine the real-time position of the smart car by placing an NB module at the diagonal of the warehouse and combining with the optimal distribution path.In the data transmission subsystem,in order to meet the requirements of timeliness and low energy consumption of data transmission in large-scale node access scenarios,a two-level data aggregation scheme based on user clustering is designed.In this scheme,nodes are clustered according to factors such as node distance and density,and cluster heads are selected according to power factor.In order to reduce the transmission power consumption and obtain the optimal system energy efficiency,a low-power data transmission method was specifically designed,including: uploading the collected information in clusters,and adopting the PSM mechanism of NB-IoT nodes.In terms of power consumption,the optimization of the measurement and control scheme and the quantitative analysis of the system power consumption verify that this method can greatly increase the effective working time of the system.In terms of stability,the adaptive adjustment strategy of cluster head nodes is introduced to ensure the reliability of data transmission and improve the system running time by about 10 times.The data processing subsystem mainly completes the storage and processing of the the data processing subsystem mainly completes the storage and processing of the collected information.Aiming at the problem of optimal path acquisition,an optimal path acquisition scheme based on improved ant colony algorithm is proposed.Firstly,based on the embedded Linux platform,the target shelf is selected by using the volume information of the goods to be stored,the substitute cargo information and the shelf occupation information.Secondly,based on the technical advantages of ant colony algorithm,and through the introduction of genetic algorithm to accelerate the accumulation of initial pheromone,to promote the rapid global convergence of ant colony algorithm.Finally,it integrates multiple distribution situations such as the urgency of delivery,energy consumption,and delivery time to obtain the optimal access path that meets various distribution situations.Combining the two-point positioning method and the optimal route,the position of the trolley can be monitored in real time during the transportation of the cargo by the trolley,and the trolley can be controlled to travel along the optimal route,thereby achieving the purpose of precise navigation.By comparing with traditional ant colony algorithm,The fusion algorithm can shorten the number of iterations by more than half,greatly improve the accuracy and complexity,and meet the timeliness and accuracy requirements of the storage environment.