A Supply Chain Information Pushing Method for Logistics Park Based on Internet of Things Technology

The existing push methods of supply chain information in logistics parks stay on the analysis of data surface, which leads to higher Mae value. Therefore, this paper proposes a push method of supply chain information in logistics parks based on the Internet of Things technology. Firstly, RFID structure is designed by introducing RFID, GPS, infrared, and other Internet of Things technologies to encode the materials in the logistics warehouse; secondly, the supply chain model of the logistics park is established to obtain the general ontology element model of the node enterprises in the supply chain of the park and the interaction business situation model between the node enterprises in the supply chain of the park. Finally, the average value of the node score is subtracted from the score of the node to calculate the information centralized scoring, as well as the establishment of Spark operation framework, to achieve the logistics park supply chain information pushing. In the simulation experiment, the international land port logistics park of a city is selected as a case to test. The experimental results show that the information pushing method of logistics information park supply chain based on Internet of Things technology has higher recommendation accuracy and better performance.

[1]  Najah K. Almazmomi,et al.  The Internet of Things and Big Data Analytics for Chronic Disease Monitoring in Saudi Arabia. , 2020, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[2]  J. V. Eeden,et al.  BEST PRACTICES FOR DEMAND-DRIVEN SUPPLY CHAIN MANAGEMENT IN PUBLIC HEALTHCARE SECTOR: A SYSTEMATIC LITERATURE REVIEW , 2020, South African Journal of Industrial Engineering.

[3]  James Cussens,et al.  Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity , 2017, J. Artif. Intell. Res..

[4]  S. Fong,et al.  A Supply-chain System Framework Based on Internet of Things Using Blockchain Technology , 2021, ACM Trans. Internet Techn..

[5]  Anna Burduk.  Artificial Neural Networks as Tools for Controlling Production Systems and Ensuring Their Stability , 2013, CISIM.

[6]  Li Junxing,et al.  Supply Chain Logistics Information Collaboration Strategy Based on Evolutionary Game Theory , 2020, IEEE Access.

[7]  Fenghua Wen,et al.  The Impact of the Cross-Shareholding Network on Extreme Price Movements: Evidence from China , 2019 .

[8]  Qian Long Kweh,et al.  Impact of research and development tax credits on the innovation and operational efficiencies of Internet of things companies in Taiwan , 2021, Annals of Operations Research.

[9]  Rehmat Ullah,et al.  Hierarchical Name-Based Mechanism for Push-Data Broadcast Control in Information-Centric Multihop Wireless Networks , 2019, Sensors.

[10]  Javier Bajo,et al.  Neural networks in distributed computing and artificial intelligence , 2018, Neurocomputing.

[11]  Hoo-Chang Hoo-Chang Shin Shin,et al.  Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning , 2016, Ieee Transactions on Medical Imaging.