Funded PhD Opportunity

RECASE: Robot-Enabled Care system in Smart Environments

Subject: Computer Science and Informatics


Summary

Background: Smart environments have been developed for daily activity monitoring to support independent living over the past decade. The rapid development of sensor technology and IOT has brought smart environments into daily life, especially in supporting home care. Recent years have seen the rising of robots and AI and their applications at home to provide service and care. While these have drawn attentions from the research community, it remains challenge to develop a more intelligent and autonomous system to support independent living at home.

Aim: The proposal aims to develop a robot-enabled care system in smart environments to support elderly people living at home independently. The project will enable robot communicates with IOT sensors and wearable sensors in the smart environment to monitor daily activity patterns, aid daily activities, and prevent risks such as falls. The project will extend existing projects on robot indoor navigation and situational reasoning with focus on multi-agent control, data fusion and integrative reasoning.

Methodology: A ROS-based re-programmable robot will be used in the study. Sensors in the smart environments will include IOT sensors and wearable sensors such as PRIs, cameras, switches, microphones, activity wrist bands and blood pressure monitors. The RECASE robot will take integrated readings from the sensors and apply machine learning algorithms to detect events and activities. Based on multi-agent based reasoning, the robot will make decisions to support the user living at home. Multi-agent approaches with Bayesian analysis and knowledge-based reasoning algorithms will be developed. Coaching will be the main role of the proposed RECASE robot.

Outcome: The expected outcome and impact of this project will be a set of robust machine learning and reasoning algorithms for the RECASE care robot system. The project aligns with the research strategy of data analytics and connected health in Pervasive Computing Research Group and Computer Science Research Unit. High quality of research papers will be expected from the project and this PhD project will provide preliminary study leading to a RCUK research proposal on care robots.

References:

Khosla, R., Nguyen, K., & Chu, M. T. (2016). Socially assistive robot enabled personalised care for people with dementia in Australian private homes.

Wilson, G., Pereyda, C., Raghunath, N., de la Cruz, G., Goel, S., Nesaei, S., ... & Cook, D. J. (2019). Robot-enabled support of daily activities in smart home environments. Cognitive Systems Research, 54, 258-272.

Hesse, S., Tomelleri, C., Bardeleben, A., Werner, C., & Waldner, A. (2012). Robot-assisted practice of gait and stair climbing in nonambulatory stroke patients. J Rehabil Res Dev, 49(4), 613-622.

Goel, S. (2019, August). Teaching robots to interact with humans in a smart environment. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (pp. 6434-6435). AAAI Press.


Essential criteria

  • Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC)
  • Sound understanding of subject area as evidenced by a comprehensive research proposal

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

  • Publications record appropriate to career stage
  • A comprehensive and articulate personal statement
  • Applicants will be shortlisted if they have an average of 75% or greater in a first (honours) degree (or a GPA of 8.75/10). For applicants with a first degree average in the range of 70% to 74% (GPA 3.3): If they are undertaking an Masters, then the average of their first degree marks and their Masters marks will be used for shortlisting.

Funding

    The University offers the following awards to support PhD study and applications are invited from UK, EU and overseas for the following levels of support:

    Vice Chancellors Research Studentship (VCRS)

    Full award (full-time PhD fees + DfE level of maintenance grant + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees and provide the recipient with £15,000 maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training studentship grant (RTSG) allocation to help support the PhD researcher.

    Vice-Chancellor’s Research Bursary (VCRB)

    Part award (full-time PhD fees + 50% DfE level of maintenance grant + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees and provide the recipient with £7,500 maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training studentship grant (RTSG) allocation to help support the PhD researcher.

    Vice-Chancellor’s Research Fees Bursary (VCRFB)

    Fees only award (PhD fees + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training studentship grant (RTSG) allocation to help support the PhD researcher.

    Department for the Economy (DFE)

    The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £ 15,009 per annum for three years. EU applicants will only be eligible for the fee’s component of the studentship (no maintenance award is provided). For Non-EU nationals the candidate must be "settled" in the UK. This scholarship also comes with £900 per annum for three years as a research training studentship grant (RTSG) allocation to help support the PhD researcher.

    Due consideration should be given to financing your studies; for further information on cost of living etc. please refer to: www.ulster.ac.uk/doctoralcollege/postgraduate-research/fees-and-funding/financing-your-studies


Other information


The Doctoral College at Ulster University


Reviews

As Senior Engineering Manager of Analytics at Seagate Technology I utilise the learning from my PhD ever day

Adrian Johnston - PhD in Informatics

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Key dates

Submission deadline
Friday 7 February 2020

Interview Date
Late March 2020


Applying

Apply Online  


Campus

Jordanstown campus

Jordanstown campus
The largest of Ulster's campuses


Contact supervisor

Professor Huiru (Jane) Zheng


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