About the Project
Smart city has been gaining attention from many bodies with the advancement of Internet of Things (IoT) technologies. With billions of IoT devices collecting data from many sources and data are stored either in public cloud or servers in a city, opportunities are arising to analyse this data for different types of usage. One potential type of data is Trace Data related with traces of moving objects in a city. Trace data represents and reflects many human behaviours in a city. Analysing the trace data and extracting knowledge about human behaviour will provide great potential for improved services in a city such as government services, public health, traffic jams, environment pollution, and natural resource issues. This study aims to mine the trace data from a city over a period of time and build the dynamic model for the human behaviour. We will use the model to provide some suggestions for improved customer services, such as business process for retailing and customer service redesign for retailing business.
Eligibility and How to Apply:
Please note eligibility requirement:
• Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
• Appropriate IELTS score, if required.
• Applicants cannot apply for this funding if currently engaged in Doctoral study at Northumbria or elsewhere.
For further details of how to apply, entry requirements and the application form, see:
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/
Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. RDF18/…) will not be considered.
Deadline for applications: 28 January 2018
Start Date: 1 October 2018
Northumbria University takes pride in, and values, the quality and diversity of our staff. We welcome applications from all members of the community. The University holds an Athena SWAN Bronze award in recognition of our commitment to improving employment practices for the advancement of gender equality and is a member of the Euraxess network, which delivers information and support to professional researchers.
Funding Notes
The studentship includes a full stipend, paid for three years at RCUK rates (for 2017/18, this is £14,553 pa) and fees.
References
1. H. Li & V. S. Lai. (2016) Understanding The Role of Social Situations On Continuance Participation Intention in Online Communities: An Empirical Perspective, Journal of Electronic Commerce Research, 17, 358-380.
2. Li, S. Tryfonas, T. Li, H. (2016) Internet of Things: A Security Point of View, Internet Research, 26, 2, 337-359.
3. Honglei Li, Cemal Tevrizci, Nnanyelugo Aham-Anyanwu, and Robert Xin Luo. (2015). The Interplay between Value and Service Quality Experience: E-Loyalty Development Process through the EtailQ Scale and Value Perception, Electronic Commerce Research, 15, 4, 585-615.
4. Li, H. and Kun-Chang, Lee. (2013) Interpersonal Relationship Framework of Virtual Community Participation Psychology: from Covert to Overt Process, Journal of Social Science Computer Review, 31, 6, 703-724.
5. Zequn Li, Honglei Li & Ling Shao (2016) Improving Online Customer Shopping Experience with Computer Vision and Machine Learning Methods In HCI in Business 2016, Los Angeles, USA, Toronto, Canada, 17-22 July 2016.
6. Nnanyelugo Aham-Anyanwu & Honglei Li. (2015) Toward E-Public Engagement: A Review of Public Participation for Government Governance. In International Conference on Information Systems, Fort Worth, Texas, USA. 13-16 December 2015.
Continue with Facebook
