Integration and Development Trend of 5G Communication Technology and Artificial Intelligence

Integration and Development Trend of 5G Communication Technology and Artificial Intelligence

Authors

  • Danying Liu Shanxi Zhongji Project Management Co., Ltd. Xi an 710075, Shanxi, China
  • Yun Gao Beijing zhongwang huatong design consulting co., ltd. Beijing 100000, China

DOI:

https://doi.org/10.53469/wjimt.2025.08(05).04

Keywords:

5G Communication Technology, Artificial Intelligence, Integration, Development Trends

Abstract

The convergence of 5G communication technology and artificial intelligence has made initial progress and has been applied to varying degrees in numerous fields. In light of this, based on the definition of the concepts of 5G communication technology and artificial intelligence, this paper analyzes the value of the integration and the innovative applications resulting from the fusion of 5G communication technology and artificial intelligence. It also explores the trends in this fusion development, with the hope of further promoting the coordinated development of 5G communication technology and artificial intelligence in China, providing technical support for our countrys social and economic development.

References

Shen, Z., Wang, Y., Hu, K., Wang, Z., & Lin, S. (2025). Exploration of Clinical Application of AI System Incorporating LSTM Algorithm for Management of Anesthetic Dose in Cancer Surgery. Journal of Theory and Practice in Clinical Sciences, 2, 17-28.

Xu, J., Wang, Y., Chen, H., & Shen, Z. (2025). Adversarial Machine Learning in Cybersecurity: Attacks and Defenses. International Journal of Management Science Research, 8(2), 26-33.

Wang, Z., Shen, Z., Chew, J., Wang, Y., & Hu, K. (2025). Intelligent Construction of a Supply Chain Finance Decision Support System and Financial Benefit Analysis Based on Deep Reinforcement Learning and Particle Swarm Optimization Algorithm. International Journal of Management Science Research, 8(3), 28-41.

Wang, Y., Shen, Z., Hu, K., Yang, J., & Li, C. (2025). AI End-to-End Autonomous Driving.

Liu, S., Zhao, Z., He, W., Wang, J., Peng, J., & Ma, H. (2025). Privacy-Preserving Hybrid Ensemble Model for Network Anomaly Detection: Balancing Security and Data Protection. arXiv preprint arXiv:2502.09001.

Guo, X., Cai, W., Cheng, Y., Chen, J., & Wang, L. (2025). A Hybrid Ensemble Method with Focal Loss for Improved Forecasting Accuracy on Imbalanced Datasets.

Weng, Y., Fan, Y., Wu, X., Wu, S., & Xu, J. (2024, November). A Multi-Layer Alignment and Adaptive Weighting Framework for Multi-Task Model Fusion. In 2024 International Conference on Intelligent Robotics and Automatic Control (IRAC) (pp. 327-330). IEEE.

Xing, Jinming, et al. "Network Traffic Forecasting via Fuzzy Spatial-Temporal Fusion Graph Neural Networks." 2024 11th International Conference on Soft Computing & Machine Intelligence (ISCMI). IEEE, 2024.

Wu, Yingyi, et al. "Recent Technologies in Differential Privacy for NLP Applications." 2024 11th International Conference on Soft Computing & Machine Intelligence (ISCMI). IEEE, 2024.

Gao, Min, et al. "Leveraging Large Language Models: Enhancing Retrieval-Augmented Generation with ScaNN and Gemma for Superior AI Response." 2024 5th International Conference on Machine Learning and Computer Application (ICMLCA). IEEE, 2024.

Xi, Kai, et al. "Enhancing Problem-Solving Abilities with Reinforcement Learning-Augmented Large Language Models." 2024 4th International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI). IEEE, 2024.

Lyu, T., Gu, D., Chen, P., Jiang, Y., Zhang, Z., & Pang, H. & Dong, Y.(2024). Optimized CNNs for Rapid 3D Point Cloud Object Recognition. arXiv preprint arXiv:2412.02855.

Liu, Y. et al. (2025). SPA: Towards A Computational Friendly Cloud-Base and On-Devices Collaboration Seq2seq Personalized Generation with Causal Inference. In: Hadfi, R., Anthony, P., Sharma, A., Ito, T., Bai, Q. (eds) PRICAI 2024: Trends in Artificial Intelligence. PRICAI 2024. Lecture Notes in Computer Science(), vol 15282. Springer, Singapore. https://doi.org/10.1007/978-981-96-0119-6_25

Liu, M., Bo, S., & Fang, J. (2025). Enhancing Mathematical Reasoning in Large Language Models with Self-Consistency-Based Hallucination Detection. arXiv preprint arXiv:2504.09440.

Wang, Y., Yang, T., Liang, H., & Deng, M. (2022). Cell atlas of the immune microenvironment in gastrointestinal cancers: Dendritic cells and beyond. Frontiers in Immunology, 13, 1007823.

Wang, J. (2025). Smart City Logistics: Leveraging AI for Last-Mile Delivery Efficiency.

LI, X., & Wang, Y. (2024). Deep learning-enhanced adaptive interface for improved accessibility in e-government platforms.

Yuan, J. (2024, December). Efficient techniques for processing medical texts in legal documents using transformer architecture. In 2024 4th International Conference on Artificial Intelligence, Robotics, and Communication (ICAIRC) (pp. 990-993). IEEE.

Song, X. (2024). Leveraging aigc and human-computer interaction design to enhance efficiency and quality in e-commerce content generation.

Chen, J. (2025). Geospatial Neural Networks: Enhancing Smart City through Location Intelligence.

Wang, H. (2024). The Restriction and Balance of Prior Rights on the Right of Enterprise Name.

Gong, C., Lin, Y., Cao, J., & Wang, J. (2024, October). Research on Enterprise Risk Decision Support System Optimization based on Ensemble Machine Learning. In Proceeding of the 2024 5th International Conference on Computer Science and Management Technology (pp. 1003-1007).

Bohang, L., Li, N., Yang, J. et al. Image steganalysis using active learning and hyperparameter optimization. Sci Rep 15, 7340 (2025). https://doi.org/10.1038/s41598-025-92082-w

Zhao, H., Chen, Y., Dang, B., & Jian, X. (2024). Research on Steel Production Scheduling Optimization Based on Deep Learning.

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Published

2025-05-12

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