## 5 Conclusions  
In this paper, a cyber-physical model is constructed by integrating the Internet of Things (IoT) technology into the fault indicator to solve the problem that the traditional fault indicator cannot communicate in mountain or forest areas. Due to the communication attenuation characteristic of the IoT communication technology, both communication reliability and power-supply reliability should be considered in the optimal configuration of the fault indicator. In this paper, an optimization framework has been formulated to obtain the optimal numbers and locations of acquisition and collection units of the fault indicators. The effectiveness of the proposed optimization framework has been validated by the simulation results under feeder 4 connected to bus 6 of the IEEE RBTS. * As shown in Table 1, we can spend only 228.48 USD to quickly locate the fault that occurred on feeder 4 within 1.5 h using the proposed IoT-based fault indicators. * The optimal placement of the IoT-based fault indicators is affected by many factors in the field. With the increase in patrol speed, the total cost and the time required for accurate fault location are both gradually reduced, which greatly improves the power-supply reliability, as shown in Table 2 and Figure 8. In the case of sufficient capital budget, increasing the number of installations of fault indicators on the line reasonably is conducive to the rapid removal of fault points, thus improving the reliability of power supply, the corresponding results are shown in Table 3 and Figure 10.
* The optimal placement of the IoT-based fault indicators is different with each distribution line. The effects of the power line length and junction node on the optimal placement scheme have \begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline
**Relationship between probability of Error and Distance** & **Installation Number of Acquisition Unit** & **Installation Position of Acquisition Unit** & **Installation Number of Collection Unit** & **Installation Position of Collection Unit** & **Total Cost (USD)** \\ \hline linear & 14 & \(\begin{array}{c}3,5,6,8,9,10,\\ 11,12,13,15,\\ 18,19,22,23\end{array}\) & 1 & 7 & 228.48 \\ \hline nonlinear & 14 & \(\begin{array}{c}3,5,6,8,9,10,\\ 11,12,13,15,\\ 18,19,22,23\end{array}\) & 1 & 7 & 222.05 \\ \hline \end{tabular}
\end{table} 
Table 6: Optional placement of fault indicators under different relationships between probability of error and distance. been discussed in this paper. The results show that the cost will rise up with the increase in line lengths and the number of junction nodes, which is shown in Tables 4 and 5 and Figure 11.  
At present, the research of fault location in the distribution network based on unmanned aerial vehicle (UAV) has received the attention of scholars, such as [36] and [37]. They are essentially another cyber-physical system to locate the fault section in the distribution system. Although there are some differences between the fault location based on UAV and our proposed location method based on IoT-based fault indicators, such as a UAV-based fault indicator to UAV (UFI-to-UAV) channels module, our proposed optimization framework combining the power-supply reliability and communication reliability is also applicable to obtain the optimal placement scheme in such cyber-physical systems. The effectiveness of the proposed method will be validated in these novel fault location methods in our future work. Conceptualization, J.L. and J.T. ; methodology, J.L. and J.T. ; software, X.W. ; hardware, S.Z., Z.Z., W.Q. and Z.L. ; validation, J.L. and H.H. ; investigation, J.L. ; data curation, S.Z., Z.Z., W.Q. and Z.L. ; writing--original draft preparation, J.L. ; writing--review and editing, J.T. and B.X. ; supervision, J.L. ; project administration, J.L. ; funding acquisition, J.T. and J.L. All authors have read and agreed to the published version of the manuscript.