Next Generation Building Envelope Inspection using Robotics and Artificial Intelligence

Building envelopes are essential for structural integrity, moisture control, and air management in a building. Damage to a building envelope could result in safety concerns for building occupants, reductions in operational efficiency, or ingress moisture leading to long-term degradation. This project is focused on the development of an autonomous building envelope inspection system using an unmanned aerial vehicle (UAV) and artificial intelligence. This work will include the conduct of field inspections using a UAV, development and application of novel autonomous UAV navigation techniques, and the use of machine learning algorithms for object detection and damage recognition. Outcomes of this work have the potential to improve the safety of building envelope inspections by eliminating the need for human inspectors to access roofs, improving the reliability of inspections by collecting quantitative building envelope performance data, and increase inspection efficiency using autonomously navigating robots, something that could also be used in post-disaster scenarios.

Faculty Supervisor:

Joshua Woods;Melissa Greeff

Student:

Partner:

Maintenance Drone Co.

Discipline:

Engineering

Sector:

Technology; Artificial Intelligence; Construction

University:

Queen's University

Program: