About the Project
Smart city has been gaining attentions 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, there arising the opportunities for analysing these data for different type 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 (evidence required by 1 August 2017).
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 ensure you quote the advert reference above on your application form.
Deadline for applications: 20 January 2017
Start Date: 2 October 2017
Northumbria University is an equal opportunities provider and in welcoming applications for studentships from all sectors of the community we strongly encourage applications from women and under-represented groups.
Funding Notes
This project is being considered for funding in competition with other projects, through one of two types of funding packages available:
• Fully funded studentships include a full stipend, paid for three years at RCUK rates for 2017/18 (this is yet to be set, in 2016/17 this is £14,296 pa) and fees (Home/EU £4,350 / International £13,000 / International Lab-based £16,000), and are available to applicants worldwide.
• As Northumbria celebrates its 25th anniversary as a University and in line with our international outlook, some projects may also be offered to students from outside of the EU supported by a half-fee reduction.
References
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.
Li, S. Tryfonas, T. Li, H. (2016) Internet of Things: A Security Point of View, Internet Research, 26, 2, 337-359.
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.
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.
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.
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.
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