Education, Science, Technology, Innovation and Life
Open Access
Sign In

Information Data Acquisition Method and Process Based on Artificial Intelligence

Download as PDF

DOI: 10.23977/autml.2025.060115 | Downloads: 2 | Views: 323

Author(s)

Haoyu Wang 1

Affiliation(s)

1 Philippine Christian University Center for International Education, Manila, 1004, Philippines

Corresponding Author

Haoyu Wang

ABSTRACT

Data collection involves extracting, transforming, and standardizing data from various sources to facilitate subsequent analysis, processing, and utilization. This process includes multiple steps, such as identifying data sources and cleaning data. In the field of artificial intelligence, data collection is fundamental to achieving machine learning and deep learning technologies, enhancing prediction accuracy, and aiding in model training. This paper focuses on the methods and processes of artificial intelligence data collection, briefly explaining the principles, importance, and guidelines of AI data collection. It provides an in-depth analysis of different collection methods and emphasizes the specific procedures involved in data collection.

KEYWORDS

Artificial Intelligence; Information Data; Acquisition Method; Process

CITE THIS PAPER

Haoyu Wang, Information Data Acquisition Method and Process Based on Artificial Intelligence. Automation and Machine Learning (2025) Vol. 6: 127-134. DOI: http://dx.doi.org/10.23977/autml.2025.060115.

REFERENCES

[1] Zhao Yinhao, Wang Yalin, Qin Guangtao, et al. Research and Application of Automatic Data Acquisition and Intelligent Processing Technology for Experiments [J]. Computer Knowledge and Technology, 2025,21(15):82-86.
[2] Chen Haigen, Dong Xinying, Jin Jiangtao, et al. Design and Implementation of a Full-Station Survey Data Acquisition Program for Android/Hongmeng Smart Terminals [J]. Urban Survey, 2025, (02):204-208.
[3] Wang Lei. Research and Application of Intelligent Collection System for Financial News Data Set [J]. Industry and Information Technology Finance Science and Technology, 2025, (02):48-59.
[4] He Jing. Research on mechatronics data acquisition method based on intelligent sensors [J]. Science and Technology Innovation, 2025, (07):85-88.
[5] Gao Chen, Ye Baozhu, Liu Haidong, et al. Application of Intelligent Computing in Data Collection and Analysis for Electricity Consumption Inspection [J]. Integrated Circuit Applications, 2025,42(04):302-303.
[6] Chen Jinquan. Research on Data Acquisition and Management Methods for Incremental Distribution Networks Based on Intelligent Communication Protocols [J]. Communication Power Technology, 2025,42(3):43-45.
[7] Yan Chong. AI-based automated data collection technology for digital media [J]. Radio and Television Network, 2025,32(03):39-42.
[8] Yang Chengzhi. Research on the Real-time Data Acquisition and Analysis System for Intelligent Storage Racks [J]. China Machinery, 2025, (08):102-105.
[9] JahaniRahaei A ,Milelli M ,Chiesa G . Urban weather dataset for building energy simulations: Data collection and EPW file generation for Torino, Italy (2014–2023) [J]. Data in Brief, 2025, 61 111708.
[10] Cian H ,Dou R ,Irwin C . Embedding historical and contextual sensitivity in QuantCrit approaches to STEM identity research: implications for data collection and analysis techniques [J]. Current Opinion in Behavioral Sciences, 2025, 64 101530.
[11] Antonova P D ,Jelyazkov J ,Pavlova I . Air quality monitoring platform with multiple data source support [J]. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2025, 47 (1): 8454-8470.
[12] Klein K ,Muller A ,Wohde A , et al. An AI-assisted workflow for object detection and data collection from archaeological catalogues [J]. Journal of Archaeological Science, 2025, 179 106244.
[13] Rahman A A ,Mridul C M ,Roy P , et al. A Multi-Head Attention mechanism assisted MADDPG algorithm for real-time data collection in Internet of Drones [J]. Vehicular Communications, 2025, 54 100944.
[14] Nikooharf H M ,Shirinbayan M ,Ghodsian N , et al. Toward advance/digitalized FFF: real-time multimodal synchronized data acquisition and ML/DL-driven process optimization [J]. Progress in Additive Manufacturing, 2025, (prepublish): 1-18.

Downloads: 3722
Visits: 166908

Sponsors, Associates, and Links


All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.