## 4 Results and Discussion
#### Discussion--Table Summary and Research Gap
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Year** & **Authors** & **Focus Area** & **CC** & **EC** & **SC** & **LCCA** & \multicolumn{3}{c}{**Overall Findings/Tools**} \\ \hline
2023 & [PERSON] et al. [103] & \begin{tabular}{c} Cost-benefit analysis of water distribution \\ rehabilitation methods \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \
\begin{tabular}{c} - \\ \end{tabular} &
\begin{tabular}{c} Identified pipe bursting, compact pipe, pipe, running, trenchless methods, \\ SCADA, CIPPRT, zoning network, \\ and sliplining as cost-effective \\ approaches for reducing non-revenue \\ water \\ \end{tabular} \\ \hline
2023 & \begin{tabular}{c} [PERSON] and \\ [PERSON] \\ [104] \\ \end{tabular} & \begin{tabular}{c} Rehabilitation of \\ sewer systems \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \
\begin{tabular}{c} - \\ \end{tabular} &
\begin{tabular}{c} Joint grouting was most effective, \\ reducing infiltration by 94\% \\ CIPPRT and EX Liner were less \\ effective \\ \end{tabular} \\ \hline
2024 & \begin{tabular}{c} [PERSON] et al. \\ [19] \\ \end{tabular} & \begin{tabular}{c} Comparison of TT \\ and ET \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \
\begin{tabular}{c} - \\ \end{tabular} &
\begin{tabular}{c} TT was found to reduce CO\({}_{2}\) \\ emissions by 59.2\% compared to ET. \\ \end{tabular} \\ \hline
2024 & \begin{tabular}{c} [PERSON] et al. \\ [9] \\ \end{tabular} & \begin{tabular}{c} Risk-based asset \\ management framework \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \
\begin{tabular}{c} - \\ \end{tabular} &
\begin{tabular}{c} YOLO-v8 was chosen for its real-time \\ object detection capabilities \\ \end{tabular} \\ \hline
2024 & \begin{tabular}{c} [PERSON] \\ [PERSON] [53] \\ \end{tabular} & \begin{tabular}{c} Analytical approach \\ for pipeline LCCA \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \begin{tabular}{c} \\ \end{tabular} & \
\begin{tabular}{c} - \\ \end{tabular} &
\begin{tabular}{c} Proposed an analytical framework \\ integrating inspection, repair, and \\ failure costs \\ - \\ - \\ - \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 3: _Cont._for selecting rehabilitation strategies tailored to site-specific needs. [PERSON] [101] utilized Gradient Boosting and Random Forest models to enhance cost estimations and pipe condition predictions, highlighting their potential to reduce uncertainties in large-scale projects. [PERSON] [105] implemented adaptive neuro-fuzzy systems and Monte Carlo simulations for assessing risks in reinforced concrete sewer pipes, demonstrating ML's capacity to predict vulnerabilities and mitigate costs effectively. [PERSON] [100] used Gradient Boosting and XGBoost for sewer pipe asset management, emphasizing ML's utility in asset longevity. [PERSON] et al. [106] explored Bayesian inference and surrogate models for uncertainty reduction in cost analysis, while [PERSON] et al. [10] used data mining techniques to predict water main failures. These studies collectively showcase ML's capability to integrate construction, environmental, and social costs into robust LCCA frameworks. Despite the insights provided by these studies, several gaps remain in the application of analytical tools for cost prediction in sewer rehabilitation.