Honours and Masters project

Passive acoustic monitoring is a well-established, non-invasive technique for wildlife monitoring, with growing interest in bioacoustic individual-level recognition—the ability to distinguish individual animals based on their vocalisations. While existing approaches perform well when all individuals are known a priori, wildlife populations are inherently dynamic, making such closed-set assumptions unrealistic in natural environments.

This project focuses on understanding and applying control charts as a tool for monitoring and improving process quality. It involves designing some basic control charts and evaluating their performance in detecting process variations under different conditions. The evaluation will be based on key metrics such as Average Run Length (ARL), false alarm rate, and detection speed, providing insights into the effectiveness of various chart types in maintaining quality standards.