Improving precision analysis of power line modeling and integrating data processing chains for automating 3D building rooftop modeling

The project consists of two independent segments. The first part, to be managed by PhD student Yoonseok Jwa, aims to develop and evaluate new photogrammetric computer vision algorithms for detecting and identifying POAs and insulator types attached to power lines (PL).

Developing power line network modeling method considering wind effects

This project aims to develop and evaluate new geometric modeling algorithms of power line and building objects, which are required for conducting power-line related asset risk analysis in challenging environment considering wind blowing effects.The project also aims to integrate newly developed algorithms into York University’s in-house power line modeling test bed and evaluate their performance using GDI’s extensive inventory data.

Development and Performance evaluation of 3D powerline reconstruction method using airborne LiDAR data

The North American electric power distribution network comprises a vast critical infrastructure of interconnected grids and power lines. Effective management of this system requires timely, accurate power line mapping and monitoring. Scene analysis for powerline change monitoring requires precise detection of all key corridor objects (i.e., powerlines, towers, insulators, splices, switches and other components as well as the terrain, buildings, trees, etc.).