Low-Cost Thermal Point Clouds of Indoor Environments

Abstract

The integration of low-cost thermal sensors with Apple Smart Devices supports the generation of 3D point clouds that include temperature indicators. This generates a new perspective for the study of buildings, allowing for fast and reliable examination of physical building structures. To the best of our knowledge, this study is the first to demonstrate the use of affordable sensors for 3D thermal point cloud generation. The study involved capturing data from the LiDAR and thermal sensors, followed by an extrinsic calibration process to align the datasets. Subsequently, the point cloud was segmented based on different acquisition poses of the device and finally, the thermal data was projected onto the 3D model, integrating temperature information with spatial coordinates. Our results demonstrate the effectiveness of the approach for three-dimensional point cloud generation in indoor environments, highlighting significant thermal variations and enabling thermal mapping of building structures. Furthermore, our findings underscore the feasibility of employing low-cost sensors for generating detailed thermal models, opening possibilities for widespread adoption in various building analysis applications. This approach provides a comprehensive and cost-effective solution for building monitoring, democratizing access to advanced evaluation tools.