A mobile mapping solution for VRU Infrastructure monitoring via low-cost LiDAR-sensors - Vogt, Johanna; Ilic, Mario; Bogenberger, Klaus (Journal of Location Based Services, 2023)
LiDAR scanning is a widely-used method for accurately assessing roads and vehicular infrastructure. However, it can be costly and often overlooks infrastructure important for Vulnerable Road Users (VRU) like pedestrians and cyclists. Advances in electronics now permit high-performance LiDAR sensors made of standard semiconductor materials to be integrated into personal devices like smartphones and tablets. This study introduces a new classification category of handheld LiDAR systems for the purpose of VRU infrastructure mapping on a smaller scale. Qualitative experiments using a handheld LiDAR system were conducted to achieve low-cost mobile mapping of VRU infrastructure. The 3D Scanner App facilitated detailed and qualitative point cloud generation at low speeds. Moreover, it demonstrated precise detection of perpendicular potholes and bumps on roads. A quantitative analysis based on several infrastructure damages was performed, revealing mean average percentage errors of 3.53%, 4.43%, and 10.57% in the x-, y-, and z-directions, respectively. While the accuracy in the x- and y-directions is acceptable, the higher z-direction error indicates overestimation of infrastructural damage depth. In conclusion, the sensor's capabilities enable cost-effective mobile mapping solutions for VRU infrastructure monitoring, such as crowd-sourcing for urban data mining and urban digital twin interfaces, significantly reducing expenses compared to traditional sensors.
CRIS-Team Scopus Importer:2023-09-22
Keywords: handheld LiDAR system; Low-cost LiDAR Sensor; mobile 3D mapping; Urban data mining; VRU infrastructure mapping

Smartphone-Based Hyperspectral Imaging - Low-Cost Application for Telemedicine - Vogt, Johanna; Martin, Sina; Franke, Jörg (dHealth 2023, 2023)
In this paper we outline a cost-effective design for the improvement of telemedicine applications through a two components concept. A normal smartphone is equipped with a small device containing different filter options, which provide particular spectral information for the identification of skin lesions. By merging the measured spectra, a higher data density and more information can be obtained using an ANN to improve an early diagnosis of skin lesions through telemedicine applications in remote areas.
CRIS-Team Scopus Importer:2023-06-02
Keywords: artificial intelligence; hyper spectral imaging; smartphone-based application; telemedicine