PhD Research Studentship
School of Engineering and Built Environment
Reference Number: SEBE_2015_7
Studentship Project Title: The Application of Big Data in Ambient Assisted Living and
Smart Homes
Applications are invited for a full-time PhD research studentship at Glasgow Caledonian University within
the school of Engineering and Built Environment. The studentship is for a period of three years - subject
to satisfactory progress - and provides payment of tuition fees at the UK/EU rate plus an annual stipend
of £14,800 [please note that students from outside the EU are required to pay the difference between the
International and EU fees, currently this would amount to £7,100 per annum which, if required, can be
deducted from the student annual stipend]. The successful candidate will carry out up to 6 hours of
academic-related work per week as part of their research training.
Research Discipline
Computer Science, Electronic and Electrical Engineering
Research Theme
Health informatics
Research Project Summary
Approximately 20% of the world population will be age 60 or older by 2050. Aging brings many
challenges to older adults due to their cognitive decline, chronic age-related diseases, as well as
limitations in physical activity, vision, and hearing. In fact, 89% of the older adults prefer to stay in the
comfort of their own homes, and given the costs of nursing home care, it is imperative to develop
technologies that help older adults to age in place more comfortably.
A smart home is a regular home which has been augmented with various types of sensors and actuators.
The smart home concept is a promising and cost-effective way of improving access to home care for the
older adults and disabled. The information from the individual sensors and actuators in smart homes and
ambient assisted living (AAL) must be pre-processed, integrated and mined to provide a most likely
model of activity which maximises information content in a health monitoring context. Moreover, the
decision-making process (e.g., classification of regular activities or medical attention needed activities)
needs to be implemented and fine-tuned taking into account the specific characteristics of sensors and
people.
The project will investigate the application of big data in AAL and smart homes. The volumes of data
generated and managed in health and social care are becoming more complex and very hard to process
with the traditional tools. Big data has the potential to revolutionary transform AAL and smart homes
delivery of services. It is also expected that big data is able to improve patient-centred services, reduce
operational costs and monitoring with its real-time analysis capability. Various machine learning
techniques and solutions will be studied to classify and fine-tune activities and responses from the
sensors in smart homes. From the techniques investigated and simulations, the most effective and
suitable big data implementation in AAL and smart homes will be selected. A pilot study in a number of
North Glasgow Housing Association homes would be developed to prove the viability of the selected
solutions.
Supervisory Team
Dr. Bernardi Pranggono (School of Engineering and Built Environment)
Prof. Lynne Baillie (School of Engineering and Built Environment)
Staff Contact
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For informal enquiries and further details of this project please contact:
Dr. Bernardi Pranggono (b.pranggono@gcu.ac.uk)
Candidate Background
We are looking for a highly motivated candidate with a good honours degree (minimum 2.1) or Masters
in CS/Engineering or related discipline with good analytical and programming skills and a strong interest
in some or all of the following areas: big data, machine learning, health informatics, networking, sensor
networks, etc. The candidate must also have a positive attitude toward interdisciplinary research and
teamwork.
Candidates whose first language is not English are expected to hold a current IELTS qualification (or
equivalent) with an overall score of 6.5 with no element below 6.0.
How to Apply
Applicants should complete the University Research Application Form, available from
http://www.gcu.ac.uk/research/postgraduateresearchopportunities/ under “How to Apply”
Please send the form, stating the studentship project title and reference number, with a CV, copies of
academic qualifications, references, and any other required documentation to:
researchapplications@gcu.ac.uk
At GCU we are committed to promoting a flexible, accessible and inclusive working
environment. Anticipated flexible work patterns for PhD students can be discussed with the project
supervisory team at the interview stage.
The closing date for applications is 22nd May 2015
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