## 4 Asset Digitalization Use Case: IoT and AHI App for a Bridge Maintenance
### The Bridge Health Index Model
Moreover, this AHI interpretation can be performed on an individual basis for decision-making on a specific asset or comparatively for decisions affecting a group of similar assets managed by the same organization or responsible entity under the same budgetary constraints. The comparative management of AHI values for similar assets holds particular significance in global management decisions for a network of infrastructure assets. In the interpretation process, multivariable analysis is conducted, including factors such as remaining useful life, and expected degradation. When comparing assets, the combined management of these variables facilitates the generation of overall network control and knowledge management. In the given example of the bridge case study, the simulation explored the behavior of four bridges under varying operational and maintenance conditions. Table 4 presents the initial/estimated health index, the actual achieved health index, and the deviation at the current time since the last overhaul. \begin{table}
\begin{tabular}{c c c} \hline \hline
**AHI** & **Condition** & **Requirements** \\ \hline
1–4 & Very Good & Normal maintenance \\
4–5.5 & Good & Normal maintenance \\
5.5–7 & Fair & Increase diagnostic testing, replacement depending on criticality \\
7–8 & Poor & Start planning process to replace \\
8–10 & Very poor & Immediately assess risk; replace or rebuild based on assessment \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Strategies according to the AHI calculation. According to the framework proposed in Figure 1 and its interpretation in Figure 10, in order to use the results obtained, it is possible to propose and design the necessary interfaces in the BI App. For instance, Figure 11 is an example of an interface designed to support decision-making for a group of bridges. It represents the comparative evolution status of different bridges that are managed jointly, as they share maintenance and investment resources. In Figure 11, each bridge is represented by a ball, and each bridge ball is placed at its operating time and its IHIi, while the value of IHs sets the ball diameter. The greater the relative deterioration, the greater the diameter. We would be very concerned with bridges having a very low operating time with large-diameter balls, since that is a symptom of unexpected early deterioration that could be a consequence of specific O&M conditions. In the obtained results in Table 4, it is noticeable that Bridge 1, despite accumulating the least operating time, is predicted to have the highest estimated health index due to its initial operating conditions. Bridge 1, compared to Bridge 3, has a lower real health index, indicating a faster aging rate. Figure 11 illustrates this projection, showing health index trends against the age of Bridge 1 and Bridge 4. The varying ball sizes in the figure represent relative deterioration, with larger balls indicating greater deterioration. For instance, Bridges 1 and 2, constructed within a short time difference, show differences in health index and relative deterioration, warranting further investigation. Bridge 3, despite having the highest health index, exhibits significant relative deterioration, emphasizing the need for focused attention and resource allocation to preventive maintenance activities. In contrast, Bridge 4, despite being the oldest, has a lower health index, but the deviation from the predicted health index is not alarming, suggesting a manageable health status relative to its age. Note that all these conclusions and potential \"calls for action\" are revisited every few months, whenever this information is updated. This is a mid/long-term management tool for the control of asset O&M programs, the scheduling of major overhauls, and better planning of future reinvestments.