# Comparative Analysis of LiDAR and Photogrammetry for 3D Crime Scene Reconstruction
## 5 Conclusions  
This study investigated how mobile phone-based LiDAR and photogrammetry technologies can be used in reconstructing 3D indoor crime scenes, with a focus on the accuracy and visual quality of the maps. The results show that the built-in scanner in the iPhone 15 Pro Max with the Recon-3D app could capture the crime scene in detail with acceptable accuracy for forensic purposes. The comparative study also revealed that photogrammetry using Pix4D mobile apps could create denser point clouds with visual detail, providing accuracy of 0.017 m compared to the LiDAR-based solution with 0.012 m. Although the LiDAR solution achieved the best map accuracy in the nighttime scenario (0.006 m) due to having the lowest interference of sunlight, its visual quality (using flash lighting) was not acceptable for forensic purposes. The research also revealed the saturation problem in LiDAR with Recon-3D, potentially impacting the results of the crime scene documentation. The results are crucial for crime scene investigators to understand the accuracy of the latest 3D-mapping tools and their limitations for court presentations. Future work should investigate the recent advancements in 3D rendering techniques, such as Gaussian Splatting, and integrating AI framework to identify crime evidence. Also, the integrity of the 3D models should also be preserved by incorporating checksum calculations in the model. Recommendations for Practical ImplementationWhen using a combination of documentation techniques and technologies, when possible, employing a range of documentation methods, such as LiDAR, photogrammetry, and conventional photography, can improve the documentation results. The photogrammetry ability to create denser point clouds combined with the LiDAR capability to create visually appealing scans that are accurate in spatial measurement can enhance the results of the documented evidence and act as supporting evidence in addition to the widely used traditional photography. This approach ensures that each technology's unique strength is maximized. * Promoting the development of LiDAR sensor applications on iOS devices: Since Recon-3D is one of the first applications that utilizes LiDAR technology on iPhones/iPads for forensics science purposes and it demonstrated a relatively low RMSE compared to a professional-grade Leica scanner, there is potential for other developers to create similar applications on iOS devices. Moreover, to gain interest among researchers and developers in using smartphone-based LIDAR, it is advisable to include a viewing feature within the current study, which uses Recon-3D or other developed applications in the future. This feature should enable free viewing and sharing of 3D models without requiring users to register or subscribe. * Preserve model integrity: While this topic is not the focus of this study, it is crucial to highlight the importance of preserving the accuracy of scanned models, mainly when such models can be used not only as supporting evidence of the crime scene environment and content but also as virtual tours for the court, to better comprehend the crime scene content, dimensions, and activities. * Ensure the integrity of the reconstructed models is preserved. Checksum mechanisms should be incorporated to validate that the scanned data models are unaltered from their original state when the scan was taken. This ensures that any modifications can be identified, preserving the model's integrity. A proposed approach is integrating checksum calculations in the scanning application, whether the Recon-3D application or PIX4D. Additionally, data transmission is secured by employing encryption to ensure the model's data while uploading them to the cloud. Since Recon-3D already transfers data to the cloud, it is essential to specify the security measure implemented when the transfer is complete. **Author Contributions:** Conceptualization, F.M.S., W.M.A. and J.H.K. ; methodology, F.M.S., W.M.A. and J.H.K. ; software: F.M.S. and W.M.A. ; validation, F.M.S. and W.M.A.