smart logistics
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In order to improve the comprehensive performance of the e-commerce system, this paper combines 5G communication technology and the Internet of Things technology to improve the e-commerce system, and conduct end-point analysis on the e-commerce client data analysis system and smart logistics system. Moreover, this paper uses 5G technology to improve machine learning algorithms to process e-commerce back-end data and improve the efficiency of e-commerce client data processing. In addition, this paper combines the Internet of Things to build an e-commerce smart logistics system model to improve the overall efficiency of the logistics system. Finally, this paper combines the demand analysis to construct the functional module structure of the e-commerce system, and verifies the practical functions of the system through experimental research. From the experimental research results, it can be seen that the e-commerce system based on 5G communication technology and Internet of Things technology constructed in this paper is very reliable.

2022 ◽  
Vol 101 ◽  
pp. 57-70
Xiaoyu Yan ◽  
Weihua Liu ◽  
Ming K. Lim ◽  
Yong Lin ◽  
Wanying Wei

2022 ◽  
Vol 2022 ◽  
pp. 1-13
Ailing Zhang ◽  
Sha Li ◽  
Lin Tan ◽  
Yingchao Sun ◽  
Fuxiao Yao

With the upgrading of logistics demand and the innovation of modern information technology, the smart logistics platform integrates advanced concepts, technologies, and management methods, maximizes the integration of logistics resources and circulation channels, and effectively improves the efficiency of logistics transactions, but its energy consumption problem is particularly prominent. The study of intelligent measurement and monitoring of carbon emissions in smart logistics is of great value to reduce energy consumption, reduce carbon emissions in buildings, and improve the environment. In this paper, by comparing and analyzing the accounting standards of carbon emissions and their calculation methods, the carbon emission factor method is selected as the method to study the carbon emissions of the smart logistics process in this paper. The working principle of each key storage technology in the smart logistics process is analyzed to find out the equipment factors affecting the carbon emission of each storage technology in the smart logistics process, and the carbon emission calculation model of each key storage technology is established separately by using the carbon emission factor method. Meanwhile, according to the development history of energy consumption assessment, the assessment process of different stages from logistics storage energy consumption assessment to smart logistics energy consumption assessment is analyzed, and based on this, a carbon emission energy consumption assessment framework based on 5G shared smart logistics is constructed. This paper applies the supply chain idea to define the smart logistics supply chain, constructs a conceptual model of the smart logistics supply chain considering carbon emissions, and at the same time combines the characteristics of the smart logistics supply chain to analyze the correlation between the carbon emissions of the smart logistics supply chain and the related social, environmental, and economic systems.

2022 ◽  
pp. 1-12
Huipeng Li ◽  
Lin Lu ◽  
Liguo Yang

The rapid development of the Internet has accelerated the expansion of e-commerce sacle of fresh agricultural products. The actual audience of smart logistics distribution of fresh agricultural products is customers, and customers enjoy the process and results of distribution services. However, the current research mainly selects indicators from the aspects of enterprise performance, cost and technical level based on the perspective of managers and technicians, which make it difficult to truly reflect customers’ feelings in the evaluation results. At the same time, the evaluation methods mainly focus on the comprehensive evaluation method and fuzzy evaluation method. These evaluation methods are greatly affected by subjective factors in the evaluation grade distribution, and the assignment is often relatively complete and inaccurate. To solve these problems, this paper constructs the evaluation index system of intelligent logistics distribution of fresh agricultural products from the perspective of customers, so that the selection of indicators is more in line with the real wishes of customers. And we use the extension function to construct the correlation function for multi-level extension evaluation to ensure the accuracy of the evaluation results. Taking X logistics enterprise as an example, this paper verifies the scientificity of the evaluation index system of intelligent logistics distribution of fresh agricultural products through empirical research, which has reference significance for further improving the intelligent logistics distribution of fresh agricultural products.

IEEE Access ◽  
2022 ◽  
pp. 1-1
Yassine Issaoui ◽  
Azeddine Khiat ◽  
Karim Haricha ◽  
Ayoub Bahnasse ◽  
Hassan Ouajji

Jaromir Tovarek ◽  
Pavol Partila ◽  
Sergej Jakovlev ◽  
Miroslav Voznak ◽  
Tomas Eglynas ◽  

2021 ◽  
Vol XXIV (Special Issue 4) ◽  
pp. 535-548
Jerzy Korczak ◽  
Maria Sasin ◽  
Dorota Janiszewska

2021 ◽  
Vol 2021 ◽  
pp. 1-5
Shuaiqi Wang

With the continuous development of artificial intelligence technology, the supply chain logistics industry has shown new changes. The products of the intelligent era such as smart devices, big data computing, and Internet of Things technology have gradually become the transformation and innovation of logistics and supply chain enterprises. The important driving force of the logistics and supply chain industry will greatly improve the operational efficiency of the logistics and supply chain industry. Methods. This article studies the technical framework of artificial intelligence and explores the upgrading and transformation of supply chain logistics enterprises in logistics infrastructure, production tools, and logistics operation processes under the promotion of artificial intelligence technology, from warehouse location, inventory management, warehousing operations, transportation, and distribution. The data analysis and prediction analyze the impact of artificial intelligence on the supply chain logistics field and finally point out the problems in the intelligent development of the supply chain logistics field and put forward targeted suggestions to promote the modern supply chain logistics to become more intelligent. developThe new development trend of smart logistics is towards sharing economy, automation, service efficiency, and cost reduction. Results. In this context, if logistics companies want to achieve higher-quality development, they cannot do without business model innovation and larger-scale collaboration, transparency of logistics information, and more comprehensive information sharing. The new trend of the development of smart logistics is to develop in the direction of sharing economy, automation, service efficiency, and cost reduction. Conclusion. Intelligence and the Internet of Things are the inevitable trend of the development of smart logistics, which is mainly realized through the Internet of Things path in terms of visual information technology, intelligent robot operation, vehicle scheduling, and cargo traceability.

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