# Mobile LiDAR for Scalable Monitoring of Mechanically Stabilized Earth Walls with Smooth Panels
## 6 Conclusions and Potential Directions for Future Research  
This study verified the ability of MLS for the procurement and generation of a wide range of serviceability measures for MSE walls with smooth precast concrete panels through a proposed monitoring strategy that expanded on the work of [PERSON] et al. [15], which segmented the large textured MSE walls into isolated panels for serviceability measures. This study built on this and was able to tackle larger smooth paneled MSE walls and could be utilized in evaluating the long-term serviceability of MSE walls. It could also be used to create new acceptance criteria for new projects and evaluate the serviceability of MSE walls susceptible to natural disasters. A LiDAR-based MLS which can lower infrastructure management cost and enhance performance through better overall maintenance operations was utilized to collect highly accurate, high-resolution point clouds while driving along the transportation corridor. This research also introduced a strategy for panel identification for smooth MSE walls and established extensive quality control measures through the comparison with interactive measurements of displacement in the point cloud and in-situ profiler gauge measurements. The robust performance of the proposed strategy was verified even when some intermittent access to the GNSS signal (when driving under the bridge) was present. This research also addresses the performance of the registration procedure in the alignment of a multi-sensor/multi-drive run/multi-modal scanning system and showcases the quality of the system calibration and trajectory information. The research objectives were tested through a case study in the State of Indiana where a comparative performance evaluation using TLS and MLS data acquisition modalities was conducted. The contributions/findings of the proposed strategy can be summarized as follows:  
1. The study illustrated the capability of MLS in collecting point clouds with appropriate point density to derive global and local serviceability measures without the need for installing targets. 2. The study introduced a point-cloud processing framework, which includes a hybrid approach for the fine registration of scans derived from different sensors collected from single and multiple drive runs, segmentation, panel isolation, and derive both global and local serviceability measures evaluation. 3. Point clouds from different sensors and different drive runs can increase the level of detail in the gathered point clouds when using an MLS, with a high quality GNSS/INS direct geo-referencing unit, that has been accurately calibrated. 4. The potential of MLS was evaluated through a comparative evaluation against TLS. The derived serviceability measures from TLS and MLS were in close agreement within the range of 0.3/1000 for the standard measures (i.e., \(\alpha_{L}\) and \(\alpha_{T}\)) and 1 cm and 0.3\({}^{\circ}\) for the recently-available serviceability measures (i.e., panel-to-panel differential displacements and angular deviations). 5. The derived panel-to-panel distance measure from TLS and MLS were quite similar (within the range of 0.5 cm), thus providing additional validation for the MLS potential. Moreover, the comparison with on-site measurements (using profiler gauge) confirmed the absolute accuracy of such measures. 6. Extensive testing with a large real dataset demonstrated the feasibility of the different aspects of the proposed acquisition and processing framework. Future work will focus on developing a completely automated process for MSE walls with piece-wise planar facades, improving system calibration, and GNSS/INS trajectory by considering observed discrepancies from multiple drive runs, as well as evaluating the impact of driving speed on the estimated serviceability measures. Moreover, the potential of using lower grade MLS to generate serviceability measures and expanding the strategy to handle non-identical and textured panels will also be investigated.