# A Framework of Wearable Sensor-System Development for Urban 3D Modeling
## 5 Conclusions  
This study aimed to propose a framework for building a wearable sensor system optimized for complex urban structures. Thus, this study presents a workflow for wearable sensor design and a calibration framework optimized for wearable sensor systems. Furthermore, as part of the framework, a calibration method based on point-plane correspondences is proposed for efficient system calibration of wearable systems. The wearable sensor system design workflow was based on criteria prepared in consideration of the efficiency of data acquisition and the accuracy of system calibration and data fusion. In this study, a wearable sensor system was manufactured through the proposed design workflow, and the manufactured sensor system efficiently acquired images and point cloud data about the surrounding environment. The proposed framework and system calibration method contributed to the accurate calibration and data fusion of the wearable sensor system, and showed better performance than the other method. The advantages of the proposed system calibration method stem from (i) a calibration process designed in two steps, and (ii) a calibration method based on point-plane correspondences. First, through the two-step system calibration method, ROPs between sensors with low FOV overlap can be more stably derived, avoiding a decrease in accuracy obtained by calculating ROPs between same-modal sensors with low FOV overlap ratio, by instead using ROPs between a LiDAR and an optical camera, with relatively high FOV overlap ratio. Second, the system calibration method proposed in this study accurately and efficiently derived ROPs between sensors in a wearable system. The proposed method does not require any prior work to acquire GCP coordinates, and it is easy to implement as a code or program based on the conventional colinear equation by modifying the weightmatrix setting method. In addition, it offers the advantage that does not require estimation of a 3D point or line segment located at the edge of the target object in the lidar point cloud. The data fusion results through the proposed framework showed better performance in comparative evaluation with the results of methods using ICP and nominal values. In conclusion, this study offers a method of efficient and accurate data acquisition using a wearable system suitable for 3D modeling in a complex urban environment. The proposed framework contributes to accurate data fusion through calibration optimized for wearable multi-sensor systems. Furthermore, the proposed point-plane correspondences-based system calibration method supports efficient calibration because it does not require a GCP coordinate measurement process. This advantage of the point-plane correspondences-based method contributes to the implementation of in situ system calibration by using various planar objects of the site. On the other hand, the limitation of the proposed method is that it requires three or more planar targets installed perpendicular to each other. Therefore, when the directions of planar objects for calibration are similar, the performance of the proposed system calibration method may decline. However, for complex urban environments, it is expected that the limitations of the proposed method will have little effect on the accuracy of system calibration, because the urban environment generally includes planar objects in various directions. This study will contribute to accurate 3D modeling of urban spaces, the generation of the high-definition 3D road maps, and the development of smart cities, in that it supports efficient 3D data acquisition and fusion using wearable sensor systems. In the future, an in situ system calibration methodology and an accurate 3D modeling methodology for the wearable sensor system will be developed by modifying, evolving, and automating the proposed method, based on the advantage that the proposed method does not require prior work to acquire GCP coordinates. Conceptualization, K.C. ; methodology, K.C. ; software, K.C. ; validation, K.C. and C.K.