## 6 Conclusions and Areas for Further Research
For instance, the criticality model can be recalibrated to reflect the specific risk profiles of other asset types, while the monitoring model's IoT architecture can be tailored to different physical and operational environments. These potential adaptations are part of ongoing research and will be validated in future studies across diverse industries and asset categories. A limitation of this work is the absence of immediate quantitative metrics demonstrating the framework's impact on key performance indicators such as unplanned downtime reduction, maintenance cost optimization, or overall TOTEX or efficiency improvements. This is due to the study's focus on establishing the feasibility of integrating IoT networks with the AHI model in the context of bridge maintenance. In future research, longitudinal studies will capture these metrics over extended periods, enabling a robust comparison with traditional maintenance methods and further validating the framework's applicability to diverse asset types and industries. The authors also acknowledge that a detailed evaluation of the accuracy, uncertainty, and sensitivity of the models is essential for further validating their reliability. For instance, the Asset Health Index (AHI) model could benefit from an uncertainty analysis that examines the effects of sensor accuracy, data completeness, or environmental variability on the calculated health scores. Sensitivity analysis could also be used to identify critical parameters--such as degradation rates, risk factors, or maintenance thresholds--that have the most significant impact on the model's outputs. Additionally, exploring advanced algorithms and machine learning approaches to optimize model performance and accuracy presents exciting opportunities for future research and development. Conceptualization, E.C.F., A.C.M. and A.J.G.L. ; methodology, E.C.F. ; software, E.H.F. ; validation, E.C.F. and E.H.F. ; investigation, E.C.F., A.C.M. and A.J.G.L. ; resources, E.H.F. ; data curation, E.C.F. and E.H.F. ; writing--original draft preparation, E.C.F., A.C.M. and A.J.G.L. ; writing--review and editing, E.C.F., A.C.M. and A.J.G.L. ; visualization, E.C.F. and A.J.G.L. ; supervision, A.C.M. ; project administration, A.C.M. and A.J.G.L. ; funding acquisition, A.C.M., A.J.G.L. and E.H.F. All authors have read and agreed to the published version of the manuscript. This research was funded by the Spanish Ministry of Science and Innovation (MCIN/AEI/10.13039/501100011033) grant number PID2022-137748 OB-C32. Non applicable. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: Data is contained within the article. This article is a revised and expanded version of a paper entitled Asset Digitalization Strategy using IoT Platforms and Asset Health Model, which was presented at AMEST'24 in Cagliari [53]. While the prior work provided a high-level exploration of the methodology and a preliminary application to bridge maintenance, the current manuscript significantly expands on these foundations, offering deeper and more comprehensive contributions in several key areas: (1) This manuscript provides a detailed multi-model architecture, including the Asset Definition Model, Asset Criticality Model, Monitoring Model, and Intelligent Asset Management Models. These models are now fully described. (2) This paper goes beyond the high-level overview in [53] by integrating a detailed IoT network design, sensor node architecture, and advanced data processing workflows. This includes practical insights into real-time data acquisition, monitoring, and decision-making supported by the AHI model. (3) The methodology is here greatly enhanced with additional details, implementations, and applications that were not covered previously. While preparing this work,the authors utilized ChatGPT 4.0 to enhance clarity and readability. Following its use, the authors thoroughly reviewed and adjusted the content as necessary, taking full responsibility for the final publication.