Problem detection and aerial mapping for construction site management

On time discovery of problems and constant monitoring of construction sites have great economical benefit. It requires the capability of highly efficient and accurate object detection and segmentation algorithms that can work with coarsely labelled training samples. The project is aimed to develop new learning-based object detection and segmentation algorithms for problem detection and mapping of construction sites with high accuracy and efficiency. This project will improve operation efficiency for construction related projects. This project is also able to advance the application and research of advanced AI technologies in industries, which can increase the competitive advantage of Canadian companies in international market.

Faculty Supervisor:

Steven Waslander

Student:

Lei Wang

Partner:

SiteVue Incorporated

Discipline:

Aerospace studies

Sector:

Information and cultural industries

University:

Program: