Coventry University Featured PhD Programmes
Newcastle University Featured PhD Programmes
King’s College London Featured PhD Programmes
Brunel University London Featured PhD Programmes
University of Reading Featured PhD Programmes

An AI-driven approach to proactive Internet Of Things (IoT) based systems - Project ID SOC0008

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

The Internet of Things (IoT) refers to the ever-growing network of physical objects such as smart devices, vehicles, buildings and other items embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to interact autonomously and intelligently. IoT is the foundation of so-called smart systems which provide critical services in many emerging application domains such as smart home, smart city, energy supply and traffic management. IoT based smart systems is creating huge new markets and solutions to improve our economy, society and life. They have been a key drive in many economic sectors and many parts of the society and people’s life.

However, when use the actual smart systems in practice, people often feel that the system is not that smart as they expected or as advocated by the vendors. Disappointingly, the systems often produce very limited or even wrong response to the user need. The current research on building the smart systems is still quite basic and leaving the current smart systems with no or little learning abilities to understand the user need at an appropriate deep level. This problem becomes worse because user needs are usually dynamic, i.e. changing from time to time. Furthermore, the advances of sensors and computing technologies plus the wide spectrum of application domains have made these smart systems very diverse, large and complex.

In this PhD project, the successful candidate will explore the current state of the art on software architecture and Internet Of Things and then develop a new approach to endorsing the proactive learning ability to the IoT and therefore enable these smart systems to provide resilient and adaptive services that best match the dynamically changing user needs. The approach will provide a key solution to one of the greatest concerns of the current IoT-based smart systems.

Applications from potential part-time students are also welcomed.

Edinburgh Napier University is committed to promoting equality and diversity in our staff and student community https://www.napier.ac.uk/about-us/university-governance/equality-and-diversity-information.

Academic qualifications
A first degree (at least a 2.1) ideally in Computer Science with a good fundamental knowledge of software engineering, or artificial intelligence or Internet Of Things.

English language requirement
IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available here https://www.napier.ac.uk/research-and-innovation/research-degrees/application-process

Essential attributes:
• Experience of fundamental software design and development
• Knowledge in design of Internet Of Things applications
• Good written and oral communication skills
• Strong motivation, with evidence of independent research skills relevant to the project
• Good time management

Desirable attributes:
Some knowledge of machine learning would be beneficial.

Funding Notes

This is an unfunded position

References

“Context-Active Resilience in Cyber Physical Systems (CAR)”, EU H2020 Marie Skłodowska-Curie Actions – European Fellowships Project, Coordinator, 2016-2018, http://www.msca-car.eu/ .

Claus Pahl, Frank Fowley, Pooyan Jamshidi, Daren Fang and Xiaodong Liu, “A classification and comparison framework for cloud service brokerage architectures”, IEEE Transactions on Cloud Computing, accepted, online early access first, DOI: 10.1109/TCC.2016.2537333, 2016.

How good is research at Edinburgh Napier University in Computer Science and Informatics?

FTE Category A staff submitted: 10.70

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.

Your enquiry has been emailed successfully





FindAPhD. Copyright 2005-2019
All rights reserved.