Viedo robotizēto risinājumu lietojums datu vākšanā un apstrādē inženierkomunikāciju infrastruktūras tehnisko datu uzturēšanas optimizācijai
Summary of Doctoral Thesis
The thesis focuses on data-driven solutions for infrastructure inspection using RGB and LiDAR data collected by unmanned aerial vehicles. A large-scale data processing model has been developed to assess the technical condition of infrastructure with the help of machine learning. The study analyses the digital transformation of processes in the energy sector, the inspection of Latvia’s distribution system infrastructure, and alternative defect detection methods. An inspection solution based on optical and spatial data has been experimentally tested. The research was performed in collaboration with “Sadales tīkls” JSC, and the results have been published in five scientific articles.
Additional information
| Publication type | |
|---|---|
| DOI | |
| Defence date | 27.06.2025. |
| Format | |
| ISBN (pdf) | |
| Pages | 56 |
| Publication date | |
| Published online | |
| Publication language | |
| Publisher | RTU Press |
| Country of Publication | Latvia |
| Funding source | European Regional Development Fund, AS “Sadales tīkls” atbalsts |
