## 4 Results and Discussion
### Image Processing Result
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Scenario No.**} & \multirow{2}{*}{**Obstacle Type**} & \multicolumn{5}{c}{**Longitude (\({}^{\circ}\)E)**} \\ \cline{2-7}  & & **Proposed** & **Image** & **Manual** & **\% Error** & **\% Error** \\  & & **System** & **Processing** & **Inspection** & **(PS vs. IP)** & **(PS vs. MD)** \\ \hline
1 & B & 77.5261 & 76.5725 & 78.65 & 1.23 & -1.45 \\
2 & B & 77.5261 & 76.4872 & 76.50 & 1.34 & 1.32 \\
3 & P & 77.5265 & 76.4799 & 76.49 & 1.35 & 1.34 \\
4 & B & 77.5266 & 76.6505 & 76.61 & 1.13 & 1.18 \\
5 & B & 77.5268 & 77.1004 & 77.17 & 0.55 & 0.46 \\ \hline \hline \end{tabular}
\end{table} 
Table 12: Comparison of depth/height between the proposed system (PS), image processing (IP), and manual inspection (MI) for the R2 test site. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Scenario No. **} & \multirow{2}{*}{**Obstacle Type**} & \multicolumn{5}{c}{**Depth/Height (cm)**} \\ \cline{3-6}  & & **Proposed** & **Image** & **Manual** & **\% Error** & **\% Error** \\  & & **System** & **Processing** & **Inspection** & **(PS vs. IP)** & **(PS vs. MD)** \\ \hline
1 & B & 9.27 & 8.8695 & 8.88 & 4.32 & 4.21 \\
2 & B & 2.20 & 2.1318 & 2.15 & 3.10 & 2.34 \\
3 & P & 8.63 & 8.3590 & 8.29 & 3.14 & 3.96 \\
4 & B & 13.12 & 12.9271 & 12.93 & 1.47 & 1.47 \\
5 & B &  
much better efficiency. The analysis results demonstrated the use of ultrasonic sensors mated with an Arduino, GPS receivers, and HUD module, which runs on several filters. Dynamic time warping was also one of the algorithms used, which makes the validation process more manageable and is also one of the reasons for the increased efficiency. The presented Hanuman algorithm could detect the potholes and speed bumps accurately and efficiently. The calculated accuracy of the system was 95.48%, and the use of inexpensive components makes it the most cost effective framework among the existing systems. The model proposed in this paper serves two critical purposes (i.e., automatic detection of potholes, bumps, and alerting vehicle drivers to evade potential accidents). The HUD application provides real-time alerts about potholes and bumps right in front onto the windshield, making it more ergonomic. The framework works perfectly in all seasons, especially in monsoon as the signal/warning is generated from a database. The novel framework ha the highest efficiency when compared to all preexisting systems. Since it is a cost effective long time solution for pothole management, it can be easily provided to the maximum number of people; which can furthermore save many lives. Integration of GMaps and Satnav with the system can be done for ease of use. This framework can be applied to different types of road conditions and will be the future scope of this work. [PERSON] prepared the inspection system for the experiment and performed the experiments of this research. [PERSON] and [PERSON] conceived the original idea. [PERSON] designed the methodology and gave guidance and helped to improve the quality of the manuscript. [PERSON] wrote the original draft preparation in consultation with [PERSON]. [PERSON] reviewed and edited the final manuscript. All authors have read and agreed to the published version of the manuscript. This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1A5A808320111, No. NRF-2019R1G1A1004577). The authors would like to thank [PERSON], [PERSON], and [PERSON], students at Amity University, who helped in conducting this research. The authors declare that they have no conflict of interest. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.