Research Interests
Traditionally, sewer inspectors mainly rely on two different methods for conducting visual inspections, including manned entry and robotic inspection using closed-circuit television (CCTV) cameras and/or other types of sensors (e.g., LiDAR, Sonar). However, the manned entry approach presents safety concerns and is also impossible in certain scenarios, due either to access issues or to the inability to get temporary bypass of flows. The robotic solutions with multi-sensor platforms (CCTV, Sonar, LiDAR) can yield a huge amount of data, but are often very expensive. Indoor drones are changing sewer inspections for the better. Using an indoor drone to collect visual data can reduce or even eliminate the need for inspectors to enter a sewer system, vastly improving safety for the inspection process. My research interests are the use of an indoor drone with LiDAR for sewer inspection, and the development of AI-based algorithms for to pinpoint the location of defects identified from the LiDAR point cloud of a sewer pipe that are collected during inspection flights.
Education
- BES in Geomatics, University of Waterloo, September 2019 - June 2023