Paper
27 March 2024 Modeling the cost in human-assisted data acquisition processes
Pengju Wang, Weiqiang Sun
Author Affiliations +
Proceedings Volume 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023); 131054K (2024) https://doi.org/10.1117/12.3026523
Event: 3rd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 2023, Qingdao, China
Abstract
With the continuous advancement of digitization across various industries, the demand for data has significantly increased, making data production a critical component in different industry production chains. Throughout different stages of digitalization, there exists a considerable variance in the degree of automation in data acquisition. Human-assisted data acquisition (HADA) processes, such as complex image recognition, extraction of unstructured textual data, and recording of data in traditional production scenarios, often incur higher acquisition costs. The understanding of data acquisition costs holds great significance in making optimal resource allocation decisions to acquire high quality data for subsequent applications during industry digitalization processes. This paper, based on Cost of Quality (CoQ) and Performance Shaping Factor (PSF) theories, proposes a universal cost analysis framework model for general human-assisted data acquisition processes. We contend that there exists a trade-off relationship between data quality and labor cost in human-assisted data acquisition processes. Furthermore, we take dietary data acquisition as an example and conduct a quantitative analysis of the trade-off relationship between data quality and labor cost using the proposed framework.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Pengju Wang and Weiqiang Sun "Modeling the cost in human-assisted data acquisition processes", Proc. SPIE 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 131054K (27 March 2024); https://doi.org/10.1117/12.3026523
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KEYWORDS
Data acquisition

Data modeling

Point spread functions

Data processing

Analytical research

Binary data

Industry

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