## 4 Conclusions
From a QC standpoint, the system provides actionable metrics--T\({}_{\rm p}\), t\({}_{\rm p}\), \(\Delta\)T (surface-core), dRH/dt, and M(t)--to support curing decisions (e.g., insulation or misting when \(\Delta\)T or dRH/dt exceed target ranges). While the present study demonstrates feasibility and reports these metrics, plant-specific f\({}_{\rm c}\)-M calibrations are planned to translate maturity into quantitative strength predictions under differing curing regimes. A direct accuracy benchmark against high-precision SHM systems lies outside the scope of this feasibility campaign; however, we outline a path for future co-located trials to quantify accuracy differences in factory environments and to link M(t) outputs with plant-specific f\({}_{\rm c}\)-M calibrations. Finally, the effectiveness of general-purpose silicone adhesive as a waterproofing method remains inconclusive due to an incident during testing that interrupted the process. Additionally, strength tests revealed that implanted sensors negatively impact indirect tensile strength results, although this effect diminishes as specimen size increases. These findings suggest a need for reevaluation of instrumentation in strength testing, considering the balance between measurement accuracy and sensor interference. Together, these results emphasize the importance of well-planned sensor design and continuous monitoring in improving the quality and durability of concrete, highlighting opportunities to optimize both instrumentation and assessment methods in the future. Conceptualization, R.P. and J.A.L. ; methodology, R.P. and T.M. ; software, B.M. ; validation, R.P., T.M. and Z.L. ; formal analysis, R.P. and Z.L. ; investigation, Z.L., B.M. and R.P. ; resources, J.A.L. and T.M. ; data curation, Z.L. ; writing--original draft preparation, R.P. and Z.L. ; writing--review and editing, R.P. and F.L. ; visualization, Z.L. and R.P. ; supervision, R.P. ; project administration, R.P. and F.L. ; funding acquisition, J.A.L. All authors have read and agreed to the published version of the manuscript. The authors would like to express their gratitude for the funding provided by the project \"PID2021-126405 OB-C32 Alarm system for bridge management systems with BIM digital twins using artificial intelligence\" funded by MICIN/AEI/10.13039/501100011033/ and \"A way to make Europe\" FEDER funds. Aslo, this research has been supported by the project SBPLY/23/180225/000113, funded under the call for grants for scientific research and technology transfer projects, in accordance with the Resolution of 22 March 2023. Not applicable. The data supporting the results of this study are available from the corresponding author upon reasonable request. The authors gratefully acknowledge Cotubo Prefabricados, S.L. (Cordoba, La Carlota, Carretera de Posadas Km 20), a leading Spanish manufacturer of precast concrete elements since 1959, for providing laboratory access, materials, and technical support during the execution of experimental tests. Special thanks go to their staff on-site for facilitating the instrumentation of sensors and sample preparation. We also appreciate the administrative and logistical support from Cotubo, enabling the integration of industry-standard practices into our research. During the preparation of this manuscript, the authors used ChatGPT (OpenAI, GPT-3.5, version April 2024) for drafting and refining sections of the Acknowledgments; the output was reviewed and edited by all authors, who take full responsibility for its content. Author [PERSON] was employed by the company COTUBO PREFABRICADOS. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.