A Study on the Effectiveness of Computer Vision Models for Addressing Environmental Problems Using UAVs and USVs

The research project, guided by Professor Stephen Smith, focuses on addressing environmental challenges related to water pollution and debris detection in the water areas, with a specific emphasis on garbage and waste detection on the water surface. The project entails a systematic literature review and analysis of various computer vision models to detect and classify garbage, which involves processing raw data from sensors on board aerial vehicles. Additionally, the project investigates how to plan the motion of the aerial vehicles over a body of water to detect and monitor garbage’s subsequent motion. The research will attempt to propose a new algorithm or modify an existing algorithm for more accurate waste detection in the water using computer vision techniques. While the project does not involve the direct use of unmanned aerial vehicles or unmanned surface vehicles, the intern will conduct a thorough investigation of their potential implementation in environmental monitoring. The expected outcomes of the project are generating insights into the effectiveness of computer vision models for environmental monitoring and management, and identifying potential applications for future research.

Faculty Supervisor:

Stephen Smith

Student:

Partner:

Kharkiv National University of Economics

Discipline:

Computer science

Sector:

Artificial Intelligence; Sustainability & the Environment; Environmental Science and Technology

University:

University of Waterloo

Program: