Intelligent Logistics Enterprise Management Based on the Internet of Things

Abstract

At this stage, many large domestic logistics companies have problems such as complex processes, low efficiency, and chaotic vehicle management. This usually leads to vehicle failure, material loss, or improper installation of the company’s factory, which affects the company’s interests and damages the company’s reputation. In response to the above problems, this article proposes, designs, and implements an intelligent logistics management system based on the Internet of Things technology through the research of the Internet of Things technology at home and abroad. The specific content is as follows: one is to study the origin and current situation of the Internet of Things technology at home and abroad, to understand related theories and cutting-edge technologies of the Internet of Things; the other is to imitate intelligent logistics companies, study the processes and existing problems of the logistics link, and integrate the management concepts of the Internet of Things. A model of intelligent logistics enterprise management is established with enterprise intelligent technology; the third is to conduct an experiment on the management of an intelligent logistics enterprise and do an experimental data analysis of the management of an intelligent logistics enterprise. Experimental research shows that the data of factors affecting logistics operations in smart logistics companies are low, and smart logistics companies are operating in good condition, and the established data model is suitable for smart logistics enterprise management. The Internet of Things and intelligent logistics management are both emerging concepts, while the intelligent logistics management based on the Internet of Things is still in its infancy, and relevant scholars have little research on the intelligent logistics management based on the Internet of Things. It plays a guiding role for the intelligent logistics management of enterprises and promotes the management of intelligent logistics enterprises.

Optimization Model and Strategy for Dynamic Material Distribution Scheduling Based on Digital Twin: A Step towards Sustainable Manufacturing

“…It connects various smart devices to physical resources, creating intelligent entities with sensing, positioning, and communication capabilities, thus enabling communication and data exchange between objects and opening new possibilities for logistics distribution management [16]. For instance, Li et al proposed an intelligent logistics management system based on IoT technology, showing significant advantages in addressing complex processes, inefficiency, and vehicle management chaos in logistics companies [17]. Lei et al introduced an IoTbased intelligent distribution model that effectively solved the problems of decision-making time and speed in a large-scale information interaction environment [10].…”

Tourism Consumer Demand Forecasting under the Background of Big Data

“…Steps for Demand Forecasting. In order to shorten the time of demand forecasting and ensure the timeliness of forecast results, it is best to predict according to the following procedures: first, to determine the purpose and use of forecasting; second, to select the object of forecasting; third, to analyze the factors and weights that affect demand forecasting; fourth, to collect and analyze current and past historical data; fifth, to select forecasting methods and models; sixth, to calculate and verify preliminary prediction results; seventh, to estimate the error of forecasting; and eighth, to make decisions based on predicted values [32,33].…”