## 4 Conclusions  
High-precision systems (e.g., fiber optic SOFO, embedded/surface-bonded piezoceramics) offer superior sensitivity for strain and damage detection and have been successfully used to characterize early-age processes; however, they entail higher costs and more specialized installation. In contrast, the Arduino-based approach prioritizes affordability, ease of deployment, and continuous logging of thermal and moisture proxies that are directly actionable for curing management in precast plants. In practice, both families \begin{table}
\begin{tabular}{c c c} \hline \hline
**QC Metric** & **Surface** & **Core** \\ \hline Peak temperature, T\({}_{\rm p}\) (\({}^{\circ}\)C) & 49.46 & 48.56 \\ Time to peak, t\({}_{\rm p}\) (h) & 9.7 & 9.17 \\ Early age heating rate, d\(\Gamma\)/dt 1\({}_{\rm 0-8}\) & 1.65 \({}^{\circ}\)C/h & 1.66 \({}^{\circ}\)C/h \\ Depth gradient at peak, \(\Delta\)T (surface-core) (\({}^{\circ}\)C) & 0.9 \({}^{\circ}\)C \\ Early-age moisture loss, dRH/dt 1\({}_{\rm 0-24h}\) & \(-\)0.18\%/h \\ RH transient at \(\sim\)14 h, \(\Delta\)RH & \(-\)11.25\% \\ Maturity M(24 h) (T\({}_{\rm 0}\) = \(-\)10 \({}^{\circ}\)C) & 1104 \({}^{\circ}\)C-h \\ Maturity M(48 h) (T\({}_{\rm 0}\) = \(-\)10 \({}^{\circ}\)C) & 2064 \({}^{\circ}\)C-h \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Quality-control metrics of the New Jersey specimen. Figure 19: Average ambient temperatures, temperatures inside the concrete, and relative humidities of the concrete. are complementary: High-precision systems excel in detailed diagnostics, while low-cost networks enable frequent, distributed monitoring to enforce QC routines (e.g., alarms on T\({}_{\rm P}\), t\({}_{\rm P}\), \(\Delta\)T, and dRH/dt) across many elements. The results from the New Jersey barrier test indicate that temperature variations are more uniform in deeper zones compared to shallower ones. This pattern suggests that, for structures with significant thickness, using sensors at specific depths may suffice, potentially optimizing instrumentation and reducing costs. Implementing temperature sensors at various depths can not only enhance quality control by monitoring thermal gradients but also help prevent issues such as surface cracking, thereby improving the durability of structural elements. Data analysis from humidity sensors indicates that using closely spaced sensor arrays is recommended to achieve more accurate measurements. While individual readings may vary significantly, averaging data from multiple sensors in the same zone provides consistent trends in relative humidity. This approach is crucial for managing issues related to rapid evaporation that can compromise concrete integrity. An abrupt change in humidity readings during the New Jersey barrier test suggests the need for further investigation, possibly by repeating the test under controlled conditions to distinguish between intrinsic concrete properties and external factors. Relative humidity results from the New Jersey barrier test show a less pronounced decreasing trend compared to previous laboratory tests, highlighting the importance of extended monitoring to validate theoretical expectations. The use of neutral silicone adhesive and PVC tubing for waterproofing humidity sensors proved effective in the protected environment of the New Jersey specimen, with no significant alterations observed during testing. However, a more rigorous assessment of their effectiveness under extreme conditions is required to confirm their performance in less controlled environments. Statistical analysis confirmed the precision of the proposed sensor system, with temperature coefficient of variation values below 3% in all configurations and humidity coefficient variations below 11%. These results support the reliability of the Arduino-based monitoring system for early-age concrete assessment in both laboratory and industrial environments.