## 3 Results and Discussion
### Water Pipe Leakage and Localization Identification Field Experiment  
In this study, an AI water pipe leakage and location identification system and a database based on the CNN autoencoder were developed to assist leak detection personnel in conducting intelligent inspection and water leakage diagnosis. To prove that the system is reliable, we worked with the leak detection personnel of the Taiwan Water Corporation. We had them carry AI water leakage diagnostic instruments to conduct system verification in the pipeline network in Hsinchu and Miaoli. The AI water leakage diagnostic instruments are used in conjunction with the intelligent cloud sound-assisted water leakage diagnostic service system to conduct pipeline inspections and leak detection during inspections. When the system finds that there is a leak in the pipe section, the area of the leakage will be reported, as shown in Figure 16. According to the area reported by the system and the results of AI diagnosis, a marking will be sprayed at the leak, as shown in Figure 17. Factory personnel is then informed to conduct an excavation to verify whether the underground pipeline is leaking, as shown in Figure 18. This study actually recorded and counted relevant verification information, including excavation results, leakage volume, pipe diameter, etc., to verify the effectiveness of the CNN autoencoder AI water pipe leakage and location identification system and database. Figure 16: Leak detection personnel of Taiwan Water Corporation used localized AI water leakage diagnostic instruments to determine the scope of leakage. Figure 17: Leak detection personnel of Taiwan Water Corporation sprayed markings within the specified area. From April 2020 to the end of March 2022, the leak detection personnel in the third area of the Taiwan Water Corporation used AI water leakage diagnostic equipment to inspect 214 road sections. The AI reported 214 leakage points, and markings were sprayed to indicate leakage locations. The statistics of the 214 leakage locations after excavation and the details of the pipe types are shown in Table 1. Most pipes are PVC pipes, accounting for 97.20% of the overall excavation results, totaling 208 pieces, and joint pipes account for 1.87%. No leakage was found in two cases (0.93%). Therefore, the data showed that the PVC pipe was the main cause of the leakage, followed by the joint pipe. Table 2 shows detailed information on different pipe diameters in 214 locations of leakages after excavation. The results show that leaking pipes whose diameter is less than 80 mm (i.e., pipelines for the end-user) account for 69.16% of the overall excavation results (148 pieces in total). Of the analyzed pipes, 100 mm pipes account for 19.16% (41 pieces in total), 150 mm pipes account for 5.61% (12 pieces in total), and 200 mm pipes account for 3.74% (8 pieces in total). Pipes whose diameter exceeds 250 mm account for 1.40% (three cases in total), and no leakage was found in two cases, accounting for 0.93% of the excavation. The above data show that pipeline end-users with diameters less than 80 mm are the main factor in leakage events. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Type of Leaking Pipe** & **Number of Excavation Pieces** & **Overall Percentage** \\ \hline PVC pipe & 208 & 97.20\% \\ \hline Junction tube & 4 & 1.87\% \\ \hline No leakage & 2 & 0.93\% \\ \hline Sum & 214 & 100\% \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Localized AI water leakage diagnostic instrument excavation verification: leaking pipe category statistics. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Leaking Pipe Diameter** & **Number of Excavation Pieces** & **Overall Percentage** \\ \hline \(<\)80 mm & 148 & 69.16\% \\ \hline
100 mm & 41 & 19.16\% \\ \hline
150 mm & 12 & 5.61\% \\ \hline
200 mm & 8 & 3.74\% \\ \hline \(>\)250 mm & 3 & 1.40\% \\ \hline No leakage & 2 & 0.93 \\ \hline Sum & 214 & 100\% \\ \hline \hline \end{tabular}
\end{table}