Applications are invited for a self-funded, 3-year full-time or 6-year part time PhD project.
The PhD will be based in the School of Computing and will be supervised by Dr Rinat Khusainov and Dr Richard Curry.
The work on this project could involve:
- addressing the need to provide safe living environments for people with long term conditions, like dementia and autism
- applying the latest Artificial Intelligence and Computer Vision techniques to real world data
- developing a prototype system that could become a commercial product in the future
Project description
Ambient Assisted Living (AAL) is concerned with using various technological solutions to allow people with additional care needs live independently in their preferred environment. AAL is of great importance for future healthcare services due to increases in the costs of traditional care models, caused by the growing elderly population and the number of people with long-term health conditions.
A considerable amount of previous AAL work has focused on using various sensors to detect emergencies, such as falls. In these scenarios, the aim of an AAL system is to recognise essentially static situations, such as a tap left open or a person lying on a floor. However, an ability to carry out more in-depth analysis of Activities of Daily Living (ADL), focusing on daily routines, is often required to help people with conditions like dementia or autism. Ensuring that common ADL routines, such as household chores, are performed in correct and complete sequences is essential for creating a safe independent living environment for these groups of people.
The aim of this project is to develop novel approaches for recognising ADL routines in video data. This work is aligned with the University’s strategic priorities in wellbeing and future and emerging technologies. The successful candidate will work within a team of academics and researchers with a track record in AAL, including links with care and housing providers and charities, such as Autism Hampshire. The project will utilise a bespoke research facility consisting of a fully instrumented residential house providing a real-world environment for research data collection and system prototype deployment. The School also boasts excellent computing facilities including an IBM PowerAI Vision platform for image and video analysis, and a vibrant and supportive research environment.
General admissions criteria
You'll need a good first degree from an internationally recognised university or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.
Specific candidate requirements
Good numeracy and programming skills are an advantage. Knowledge of AI and computer vision techniques is helpful.
How to Apply
We encourage you to contact Dr Rinat Khusainov ([Email Address Removed]) to discuss your interest before you apply, quoting the project code below.
When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process.
When applying please quote project code:COMP7510423
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