Enterprise Digital Intelligent Remote Control System Based on Industrial Internet of Things

Enterprise Digital Intelligent Remote Control System Based on Industrial Internet of Things

Authors

  • Binbin Wu Heating Ventilation and Air Conditioning Engineering, Tsinghua University, Beijing China
  • Chenxi Shi Telecommunication Systems Management, Northeastern University,Boston, MA, USA
  • Wei Jiang Computer Science, Xidian University, Xian,China
  • Tong zhan Computer Science, Columbia University, NY, USA
  • Kun Qian Business Intelligence,Engineering School of Information and Digital Technologies, Villejuif, France

DOI:

https://doi.org/10.53469/wjimt.2024.07(02).09

Keywords:

Industrial Internet of Things, Enterprise information management, Remote operation and maintenance management, Enterprise management

Abstract

Based on the background of Industrial Internet of Things, this paper aims to explore the application of remote monitoring and maintenance technology in IT enterprise automation control system. IT equipment as the core of modern enterprise management, in today's industrial Internet of Things and intelligent development, how to better manage these equipment, do a good job of daily troubleshooting, daily maintenance, management is a moment to reflect the comprehensive strength of an enterprise. Improve the continuity of production and optimize the production process, so as to effectively and quickly deal with various problems in production and life. This paper will deeply study the basic principles, application cases, and maintenance and fault diagnosis strategies of this technology in the enterprise, in order to provide more efficient and intelligent production management solutions for the IT industry. The results show that remote monitoring and maintenance technology plays an important role in improving production efficiency, reducing costs, ensuring quality and ensuring equipment reliability, and has a positive impact on the development and sustainability of the industry.

References

Li, X., Zheng, H., Chen, J., Zong, Y., & Yu, L. (2024). User Interaction Interface Design and Innovation Based on Artificial Intelligence Technology. Journal of Theory and Practice of Engineering Science, 4(03), 1-8.

Duan, Shiheng, et al. "THE INNOVATIVE MODEL OF ARTIFICIAL INTELLIGENCE COMPUTER EDUCATION UNDER THE BACKGROUND OF EDUCATIONAL INNOVATION." The 2nd International scientific and practical conference “Innovations in education: prospects and challenges of today”(January 16-19, 2024) Sofia, Bulgaria. International Science Group. 2024. 389 p.. 2024.

Qian, Wenpin, et al. "NEXT-GENERATION ARTIFICIAL INTELLIGENCE INNOVATIVE APPLICATIONS OF LARGE LANGUAGE MODELS AND NEW METHODS." OLD AND NEW TECHNOLOGIES OF LEARNING DEVELOPMENT IN MODERN CONDITIONS (2024): 262.

Song, T., Li, X., Wang, B., & Han, L. (2024). Research on Intelligent Application Design Based on Artificial Intelligence and Adaptive Interface.

Qi, Y., Wang, X., Li, H., & Tian, J. (2024). Leveraging Federated Learning and Edge Computing for Recommendation Systems within Cloud Computing Networks. arXiv preprint arXiv:2403.03165.

The Credit Card Anti-fraud Detection Model in the Context of Dynamic Integration Selection Algorithm. (2024). Frontiers in Computing and Intelligent Systems, 6(3), 119-122. https://doi.org/10.54097/a5jafgdv

Chen, W., Shen, Z., Pan, Y., Tan, K., & Wang, C. (2024). Applying Machine Learning Algorithm to Optimize Personalized Education Recommendation System. Journal of Theory and Practice of Engineering Science, 4(01), 101-108.

K. Xu, X. Wang, Z. Hu and Z. Zhang, "3D Face Recognition Based on Twin Neural Network Combining Deep Map and Texture," 2019 IEEE 19th International Conference on Communication Technology (ICCT), Xi'an, China, 2019, pp. 1665-1668, doi: 10.1109/ICCT46805.2019.8947113.

Shi, Peng, Yulin Cui, Kangming Xu, Mingmei Zhang, and Lianhong Ding. 2019. "Data Consistency Theory and Case Study for Scientific Big Data" Information 10, no. 4: 137. https://doi.org/10.3390/info10040137.

Xiao, J., Chen, Y., Ou, Y., Yu, H., & Xiao, Y. (2024). Baichuan2-Sum: Instruction Finetune Baichuan2-7B Model for Dialogue Summarization. arXiv preprint arXiv:2401.15496.

Huo, Shuning, et al. "Deep Learning Approaches for Improving Question Answering Systems in Hepatocellular Carcinoma Research." arXiv preprint arXiv:2402.16038 (2024).

Zhu, Mengran, et al. "Enhancing Credit Card Fraud Detection: A Neural Network and SMOTE Integrated Approach." Journal of Theory and Practice of Engineering Science 4.02 (2024): 23-30.

Xiang, Yafei, et al. "Integrating AI for Enhanced Exploration of Video Recommendation Algorithm via Improved Collaborative Filtering." Journal of Theory and Practice of Engineering Science 4.02 (2024): 83-90.

Zhenghua Hu, Xianmei Wang, Kangming Xu, and Pu Dong. 2020. Real-time Target Tracking Based on PCANet-CSK Algorithm. In Proceedings of the 2019 3rd International Conference on Computer Science and Artificial Intelligence (CSAI '19). Association for Computing Machinery, New York, NY, USA, 343–346. https://doi.org/10.1145/3374587.3374607.

Ji, H., Xu, X., Su, G., Wang, J., & Wang, Y. (2024). Utilizing Machine Learning for Precise Audience Targeting in Data Science and Targeted Advertising. Academic Journal of Science and Technology, 9(2), 215-220.

Zhu, M., Zhang, Y., Gong, Y., Xing, K., Yan, X., & Song, J. (2024). Ensemble Methodology: Innovations in Credit Default Prediction Using LightGBM, XGBoost, and LocalEnsemble. arXiv preprint arXiv:2402.17979.

Niu, H., Li, H., Wang, J., Xu, X., & Ji, H. (2023). Enhancing computer digital signal processing through the utilization of rnn sequence algorithms. International Journal of Computer Science and Information Technology, 1(1), 60-68.

Gong, Yulu, et al. "RESEARCH ON A MULTILEVEL PRACTICAL TEACHING SYSTEM FOR THE COURSE'DIGITAL IMAGE PROCESSING." OLD AND NEW TECHNOLOGIES OF LEARNING DEVELOPMENT IN MODERN CONDITIONS (2024): 272.

Wang, Y., Bao, Q., Wang, J., Su, G., & Xu, X. (2024). Cloud Computing for Large-Scale Resource Computation and Storage in Machine Learning. Journal of Theory and Practice of Engineering Science, 4(03).

Shen, Zepeng, et al. "EDUCATIONAL INNOVATION IN THE DIGITAL AGE: THE ROLE AND IMPACT OF NLP TECHNOLOGY." OLD AND NEW TECHNOLOGIES OF LEARNING DEVELOPMENT IN MODERN CONDITIONS (2024): 281.

Wu, J., Wang, H., Ni, C., Zhang, C., & Lu, W. (2024). Data Pipeline Training: Integrating AutoML to Optimize the Data Flow of Machine Learning Models. arXiv preprint arXiv:2402.12916.

Zhang, C., Lu, W., Ni, C., Wang, H., & Wu, J. (2024). Enhanced User Interaction in Operating Systems through Machine Learning Language Models. arXiv preprint arXiv:2403.00806.

Wang, H., Bao, Q., Shui, Z., Li, L., & Ji, H. (2024). A Novel Approach to Credit Card Security with Generative Adversarial Networks and Security Assessment.

Yu, Hanyi, et al. "Machine Learning-Based Vehicle Intention Trajectory Recognition and Prediction for Autonomous Driving." arXiv preprint arXiv:2402.16036 (2024).

Zhu, M., Zhang, Y., Gong, Y., Xing, K., Yan, X., & Song, J. (2024). Ensemble Methodology: Innovations in Credit Default Prediction Using LightGBM, XGBoost, and LocalEnsemble. arXiv preprint arXiv:2402.17979.

Xiang, Yafei, et al. "Text Understanding and Generation Using Transformer Models for Intelligent E-commerce Recommendations." arXiv preprint arXiv:2402.16035 (2024).

Zhu, Mengran, et al. "Utilizing GANs for Fraud Detection: Model Training with Synthetic Transaction Data." arXiv preprint arXiv:2402.09830 (2024).

Gong, Yulu, et al. "Enhancing Cybersecurity Resilience in Finance with Deep Learning for Advanced Threat Detection." arXiv preprint arXiv:2402.09820 (2024).

Sun, Guolin, et al. "Revised reinforcement learning based on anchor graph hashing for autonomous cell activation in cloud-RANs." Future Generation Computer Systems 104 (2020): 60-73.

Wu, Yichao, et al. "LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models." arXiv preprint arXiv:2403.08822 (2024).

Che, C., Lin, Q., Zhao, X., Huang, J., & Yu, L. (2023, September). Enhancing Multimodal Understanding with CLIP-Based Image-to-Text Transformation. In Proceedings of the 2023 6th International Conference on Big Data Technologies (pp. 414-418).

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Published

2024-03-27
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