The Application of Intelligent Information Systems Driven by 6G Big Data in Product Sales Traceability

被引:0
|
作者
Wang, FengLan [1 ]
机构
[1] Guangdong Business & Technol Univ, Zhaoqing 526020, Guangdong, Peoples R China
关键词
Healthcare supply chain; Generative artificial intelligence; Conditional generative adversarial networks with; Enhanced Q-learning with genetic algorithms (EQL-GA); Dijkstra's algorithm; Proof of authority (PoA); MANAGEMENT;
D O I
10.1007/s11277-024-11210-3
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Healthcare supply chains are complex networks that span geographical and organizational boundaries and are the foundation of many vital everyday services. Most track and trace systems now in use are centralized, which creates issues with data privacy, authenticity, and transparency in supply chains related to healthcare. In this study, we suggested using generative artificial intelligence to optimize the healthcare supply chain. The primary objectives are to precisely forecast the need for medical supplies, ensure that the right supplies are on hand when required, optimise delivery routes, and foster trust and openness in the movement of medical supplies across the supply chain. This paper offers novel ideas for using Conditional Generative Adversarial Networks to transform healthcare supply chain management. Using complex data patterns, Krill Herd Optimization (CGANs-KHO) is presented as a potent technique for very precise medical supply-demand predictions. The supply chain procedures are smoothly linked with Enhanced Q-learning with Genetic Algorithms (EQL-GA), guaranteeing accurate medical supply stocking across a range of healthcare institutions. Dijkstra's algorithm is used to optimize delivery routes, ensuring that medical supplies are moved between the central warehouse and other healthcare institutions in a timely and effective manner. Proof of Authority (PoA)-enabled private blockchains increase trust and transparency in the supply chain. Using smart contracts to automate safe supply chain agreements, this blockchain monitors the transfer of medical supplies. This increases stakeholder trust and validates transactions. The performance measures, which include Demand, Inventory level, Route, Time against Quality of Medical Supplies, and Transaction versus Transparency.
引用
收藏
页数:33
相关论文
共 50 条
  • [41] Secure Communications with THz Reconfigurable Intelligent Surfaces and Deep Learning in 6G Systems
    Kiran, Ajmeera
    Sonker, Abhilash
    Jadhav, Sachin
    Jadhav, Makarand Mohan
    Naga Ramesh, Janjhyam Venkata
    Muniyandy, Elangovan
    WIRELESS PERSONAL COMMUNICATIONS, 2024,
  • [42] Pervasive intelligent endogenous 6G wireless systems: Prospects, theories and key technologies
    Yun Chen
    Wenfeng Liu
    Zhiang Niu
    Zhongxiu Feng
    Qiwei Hu
    Tao Jiang
    Digital Communications and Networks, 2020, 6 (03) : 312 - 320
  • [43] A Hybrid Frequency Offset Estimation Combining Data-Driven Method and Model-Driven Method for 6G OFDMA Systems
    Kim, Haesik
    2024 IEEE ANNUAL CONGRESS ON ARTIFICIAL INTELLIGENCE OF THING, AIOT 2024, 2024, : 19 - 24
  • [44] Electromagnetic Information Theory: Fundamentals and Applications for 6G Wireless Communication Systems
    Wang, Cheng-Xiang
    Yang, Yue
    Huang, Jie
    Gao, Xiqi
    Cui, Tie Jun
    Hanzo, Lajos
    IEEE WIRELESS COMMUNICATIONS, 2024, 31 (05) : 279 - 286
  • [45] An Intelligent Information Forwarder for Healthcare Big Data Systems With Distributed Wearable Sensors
    Jiang, Ping
    Winkley, Jonathan
    Zhao, Can
    Munnoch, Robert
    Min, Geyong
    Yang, Laurence T.
    IEEE SYSTEMS JOURNAL, 2016, 10 (03): : 1147 - 1159
  • [46] Artificial-Intelligence-Driven RF Carrier Aggregation Filter For 6G Application
    Courouve, Pierre
    Al Shakoush, Ali
    Dehos, Cedric
    Ouvry, Laurent
    2024 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, ISCAS 2024, 2024,
  • [47] Innovative Application of 6G Network Slicing Driven by Artificial Intelligence in the Internet of Vehicles
    Ni, Xueqin
    Dong, Zhiyuan
    Rong, Xia
    INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT, 2025, 35 (02)
  • [48] An AI-Driven Intelligent Traffic Management Model for 6G Cloud Radio Access Networks
    Swain, Smruti Rekha
    Saxena, Deepika
    Kumar, Jatinder
    Singh, Ashutosh Kumar
    Lee, Chung-Nan
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2023, 12 (06) : 1056 - 1060
  • [49] Application research of graphene intelligent wearable technology driven by medical health big data
    Li, Z.
    Tian, H.
    Zhan, B. H.
    BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY, 2019, 125 : 10 - 10
  • [50] Some Observations and Thoughts about Reconfigurable Intelligent Surface Application for 5G Evolution and 6G
    HOU Xiaolin
    LI Xiang
    WANG Xin
    CHEN Lan
    SUYAMA Satoshi
    ZTE Communications, 2022, 20 (01) : 14 - 20