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Data Science for Hand Hygiene

Primary supervisor

David Taniar


  • Assoc. Prof. Mehmet Yuce (Department of Electrical and Computer Systems Engineering)

Hand Hygiene

This project is part of a larger project on Hand Hygiene, which aims to address hand hygiene in hospitals by combining a suite of digital monitoring products with advanced data analytics. We expect to create a system that monitors the full user journey and performs constant data analysis through a cloud-based system. This will have applications beyond hospital settings, such as in aged care, schools and hospitality.

Student cohort

Double Semester


The aim of this project is to develop a server-side application which analyses hand washing habits of healthcare workers (nurses and doctors) in the hospital. The data comes from the sensor tracking systems embedded into the wash stations and alcohol dispensers. The system will implement various machine learning algorithms, such as cluster analysis, prediction, etc. The system will be used by the hospital management to check their hand hygiene compliance.

Required knowledge

Web application development, machine learning algorithms