# Field Evaluation and Application of Intelligent Quality Control Systems
## 5 Conclusions  
This study assessed the feasibility of applying intelligent QC systems in the field based on comparative tests with conventional QC methods. The field test was conducted at the SOC Demonstration Center of the Korea Institute of Construction Technology, using actual road fill materials to simulate road embankment sections. The same materials and systems were used for the field tests across all sections. Traditional tests, including PLT, DCPT, and LWDT, were conducted, and the results were compared and analyzed. After evaluating the field applicability of the intelligent QC system, four stages were proposed for practical field use, with the results as follows.  
First, four types of tests were conducted: an intelligent QC test, PLT, LWDT, and DCPT. The intelligent QC test value (CMV) increased as the compaction level rose; PLT also showed a tendency for the K30 value to increase as the number of compactions increased. The LWDT confirmed that the modulus of elasticity (E value) increased with the number of compactions, while DCPT showed that the DPI value decreased as the number of compactions increased. The correlation analysis between the intelligent QC system and PLT, LWDT, and DCPT yielded R-square values of 0.69, 0.91, and 0.95, respectively, indicating significantly high correlations. Second, to apply the intelligent QC system in the field, comparative analyses were performed using results from the conventional QC tests, including PLT, LWDT, and DCPT. The Pearson correlation analysis showed very high correlation coefficients: 0.83 for the intelligent QC method and PLT, 0.96 for LWDT, and 0.98 for DCPT, suggesting that the intelligent QC system could be applied in the field. Third, four stages were proposed for implementing this intelligent QC system in the field. Stage 1 involves automatically recording the number of compactions to manage the site, while  
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Stage 2 involves automatically recording the number of compactions and measuring the IC values at necessary locations, performing PLTs at points where the intelligent quality values are lowest. Stage 3 involves automatically recording both the number of compactions and IC values, using intelligent quality values to automatically specify the locations for PLT. Finally, Stage 4 involves managing the quality of road construction sites using intelligent quality values without conventional QC tests.  
Overall, our study proposed stages for evaluating the applicability of intelligent QC systems on granitic weathered soil grounds and their field implementation. To apply intelligent quality values in actual field conditions, additional testing and analysis will be needed to perform tests under various ground conditions and scenarios. Further analysis will be required in various situations.  
Conceptualization, J.-Y.K. and J.-w.C.; conducting an experiment in the field, J.-Y.K., J.-w.C. and S.-Y.L.; data analysis, J.-Y.K.; writing--original draft preparation, J.-Y.K.; writing--review and editing, J.-w.C. and S.-Y.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Ministry of Land, Infrastructure and Transport and the Korea Agency for Infrastructure Technology Advancement (Project No. 21 SMIP-15713002).  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.