Research on the Impact of Artificial Intelligence on Data Collection Methods for Communication Power Monitoring

Authors

  • Haotian Zhang Sussex School of Artificial Intelligence, Zhejiang Technology and Business University, Hangzhou 361000, Zhejiang, China

Keywords:

Artificial intelligence, Communication power monitoring, Data acquisition

Abstract

With the rapid development of information technology, the application of artificial intelligence technology in the field of communication power monitoring and data acquisition is becoming increasingly widespread. This article aims to explore how artificial intelligence technology affects the data collection methods for communication power monitoring, analyzing from four aspects: data collection efficiency, data quality, data processing capability, and data security. Research has shown that the application of artificial intelligence technology significantly improves the efficiency and quality of data collection, enhances data processing capabilities, and improves data security. At the same time, this article also deeply analyzes the current application status, key technology research, and future development trends of artificial intelligence technology in communication power monitoring data collection, providing theoretical support and practical guidance for the intelligent development of communication power monitoring data collection.

References

Meng, Q., Wang, J., He, J., & Zhao, S. (2025). Research on Green Warehousing Logistics Site Selection Optimization and Path Planning based on Deep Learning.

Xiangyu, G., Yao, T., Gao, F., Chen, Y., Jian, X., & Ma, H. (2024). A new granule extrusion-based for 3D printing of POE: studying the effect of printing parameters on mechanical properties with “response surface methodology”. Iranian Polymer Journal, 1-12.

Yao, T. (2024, August). Research on the Local Head Loss Coefficient in Short-Tube Hydraulic Testing. In 2024 3rd International Conference on Applied Mechanics and Engineering Structures (AMES 2024) (pp. 89-97). Atlantis Press.

Ge, J. (2022). The Failure of International Diplomacy and Economic Sanctions in Response to Japan’s Aggression in East Asia, 1931-1937. Available at SSRN 4817444.

Wu, W. (2025). Fault Detection and Prediction in Models: Optimizing Resource Usage in Cloud Infrastructure.

Tang, Y., & Zhao, S. (2025). Research on Relationship Between Aging Population Distribution and Real Estate Market Dynamics based on Neural Networks.

Long, Y., Gu, D., Li, X., Lu, P., & Cao, J. (2024, September). Enhancing Educational Content Matching Using Transformer Models and InfoNCE Loss. In 2024 IEEE 7th International Conference on Information Systems and Computer Aided Education (ICISCAE) (pp. 11-15). IEEE.

Yan, H., Wang, Z., Xu, Z., Wang, Z., Wu, Z., & Lyu, R. (2024, July). Research on image super-resolution reconstruction mechanism based on convolutional neural network. In Proceedings of the 2024 4th International Conference on Artificial Intelligence, Automation and High Performance Computing (pp. 142-146).

Downloads

Published

2025-04-02

How to Cite

Zhang, H. (2025). Research on the Impact of Artificial Intelligence on Data Collection Methods for Communication Power Monitoring. Journal of Theory and Practice in Sciences, 2, 23–28. Retrieved from https://woodyinternational.com/index.php/jtps/article/view/186