Application Status and Development Trend of Intelligent Storage Based on Digital Twin Technology
DOI:
https://doi.org/10.53469/wjimt.2025.08(01).04Keywords:
Digital twin, Intelligent grain storage, Grain storageAbstract
In recent years, with the economic development and scientific and technological progress, industrial automation technology in the production process is more and more widely used, especially the development of computer technology makes it become an important part of industrial production automation. In this context, the concept of "intelligent warehousing" has also been put forward. Intelligent warehousing is a process that integrates all kinds of intelligent equipment into the logistics system by using modern information and communication technology, to realize supply chain management and improve the efficiency of the logistics system. It mainly includes logistics system software, network equipment, sensors, control software, and intelligent hardware.
References
Wu, Z., Chen, J., Tan, L., Gong, H., Zhou, Y., & Shi, G. (2024, September). A lightweight GAN-based image fusion algorithm for visible and infrared images. In 2024 4th International Conference on Computer Science and Blockchain (CCSB) (pp. 466-470). IEEE.
Li, S. (2024). Harnessing Multimodal Data and Mult-Recall Strategies for Enhanced Product Recommendation in E-Commerce.
Li, L., Gan, Y., Bi, S., & Fu, H. (2024). Substantive or strategic? Unveiling the green innovation effects of pilot policy promoting the integration of technology and finance. International Review of Financial Analysis, 103781.
Shakya, S., & Smys, S. (2021). Big data analytics for improved risk management and customer segregation in banking applications. Journal of IoT in Social, Mobile, Analytics, and Cloud, 3(3), 235-249.
Ravi, V., & Kamaruddin, S. (2017). Big data analytics enabled smart financial services: opportunities and challenges. In Big Data Analytics: 5th International Conference, BDA 2017, Hyderabad, India, December 12-15, 2017, Proceedings 5 (pp. 15-39). Springer International Publishing.
Chen, H., Shen, Z., Wang, Y., & Xu, J. (2024). Threat Detection Driven by Artificial Intelligence: Enhancing Cybersecurity with Machine Learning Algorithms.
Xu, G., Xie, Y., Luo, Y., Yin, Y., Li, Z., & Wei, Z. (2024). Advancing Automated Surveillance: Real-Time Detection of Crown-of-Thorns Starfish via YOLOv5 Deep Learning. Journal of Theory and Practice of Engineering Science, 4(06), 1–10. https://doi.org/10.53469/jtpes.2024.04(06).01
Wang, Z., Zhu, Y., Chen, M., Liu, M., & Qin, W. (2024). Llm connection graphs for global feature extraction in point cloud analysis. Applied Science and Biotechnology Journal for Advanced Research, 3(4), 10-16.
Lu, J. (2024). Enhancing Chatbot User Satisfaction: A Machine Learning Approach Integrating Decision Tree, TF-IDF, and BERTopic.
VenkateswaraRao, M., Vellela, S., Reddy, V., Vullam, N., Sk, K. B., & Roja, D. (2023, March). Credit Investigation and Comprehensive Risk Management System based Big Data Analytics in Commercial Banking. In 2023 9th International Conference on Advanced Computing and Communication Systems (ICACCS) (Vol. 1, pp. 2387-2391). IEEE.
Z. Ren, "Enhancing Seq2Seq Models for Role-Oriented Dialogue Summary Generation Through Adaptive Feature Weighting and Dynamic Statistical Conditioninge," 2024 6th International Conference on Communications, Information System and Computer Engineering (CISCE), Guangzhou, China, 2024, pp. 497-501, doi: 10.1109/CISCE62493.2024.10653360.
Chen, T., Lian, J., & Sun, B. (2024). An Exploration of the Development of Computerized Data Mining Techniques and Their Application. International Journal of Computer Science and Information Technology, 3(1), 206-212.
Hasan, M. M., Popp, J., & Oláh, J. (2020). Current landscape and influence of big data on finance. Journal of Big Data, 7(1), 21.
Awotunde, J. B., Adeniyi, E. A., Ogundokun, R. O., & Ayo, F. E. (2021). Application of big data with fintech in financial services. In Fintech with artificial intelligence, big data, and blockchain (pp. 107-132). Singapore: Springer Singapore.
Chen, J., Lin, Q., & Allebach, J. P. (2020). Deep learning for printed mottle defect grading. Electronic Imaging, 32, 1-9.
Bi, S., Lian, Y., & Wang, Z. (2024). Research and Design of a Financial Intelligent Risk Control Platform Based on Big Data Analysis and Deep Machine Learning. arXiv preprint arXiv:2409.10331.
Liang, X., & Chen, H. (2019, July). A SDN-Based Hierarchical Authentication Mechanism for IPv6 Address. In 2019 IEEE International Conference on Intelligence and Security Informatics (ISI) (pp. 225-225). IEEE.
Qi, T., & Liu, H. (2024, September). Research on the Design of a Sales Forecasting System Based on Hadoop Big Data Analysis. In Proceedings of the 2024 2nd International Conference on Internet of Things and Cloud Computing Technology (pp. 193-198).
Chen, J., Zhang, X., Wu, Y., Ghosh, S., Natarajan, P., Chang, S. F., & Allebach, J. (2022). One-stage object referring with gaze estimation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 5021-5030).
Xu, Y., Gao, W., Wang, Y., Shan , X., & Lin, Y.-S. (2024). Enhancing user experience and trust in advanced LLM-based conversational agents. Computing and Artificial Intelligence, 2(2), 1467. https://doi.org/10.59400/cai.v2i2.1467
Luo, Y., Wei, Z., Xu, G., Li, Z., Xie, Y., & Yin, Y. (2024). Enhancing E-commerce Chatbots with Falcon-7B and 16-bit Full Quantization. Journal of Theory and Practice of Engineering Science, 4(02), 52–57. https://doi.org/10.53469/jtpes.2024.04(02).08
Tian, Q., Wang, Z., Cui, X. Improved Unet brain tumor image segmentation based on GSConv module and ECA attention mechanism. arXiv preprint arXiv:2409.13626.
Chen, H., & Bian, J. (2019, February). Streaming media live broadcast system based on MSE. In Journal of Physics: Conference Series (Vol. 1168, No. 3, p. 032071). IOP Publishing.
Lin, S., Tan, H., Zhao, L., Zhu, B., & Ye, T. (2024). The Role of Precision Anesthesia in High-risk Surgical Patients: A Comprehensive Review and Future Direction. International Journal of Advance in Clinical Science Research, 3, 97-107.
Wang, Z., Chu, Z. C., Chen, M., Zhang, Y., & Yang, R. (2024). An Asynchronous LLM Architecture for Event Stream Analysis with Cameras. Social Science Journal for Advanced Research, 4(5), 10-17.
Z. Ren, "A Novel Feature Fusion-Based and Complex Contextual Model for Smoking Detection," 2024 6th International Conference on Communications, Information System and Computer Engineering (CISCE), Guangzhou, China, 2024, pp. 1181-1185, doi: 10.1109/CISCE62493.2024.10653351.
Xu Y, Shan X, Guo M, Gao W, Lin Y-S. Design and Application of Experience Management Tools from the Perspective of Customer Perceived Value: A Study on the Electric Vehicle Market. World Electric Vehicle Journal. 2024; 15(8):378. https://doi.org/10.3390/wevj15080378
Wang, Z., Yan, H., Wang, Z., Xu, Z., Wu, Z., & Wang, Y. (2024, July). Research on autonomous robots navigation based on reinforcement learning. In 2024 3rd International Conference on Robotics, Artificial Intelligence and Intelligent Control (RAIIC) (pp. 78-81). IEEE.