An ontology based smart city modelling and implementation of the artificial intelligence (multi-agent system, fuzzy logic, artificial neural network and optimisation algorithms) to control the energy and water. Self-funded PhD in Engineering Ref: 3069

About the Research Project

Location:
Streatham Campus, University of Exeter, EX4 4QJ
 

Academic Supervisors:
Dr Baris Yuce, University of Exeter
 

Project Description:
Ontological data modelling aims to collect the terms and definitions stated in natural language. Hence, ontology-based data modelling and ontology added applications provide holistic knowledge presentation infrastructures for the modelling of the complex systems like smart cities where the data management in smart city domain is mostly clustered under the big data modelling.

Since the smart city concept involves multi-dimensional problems including energy management, water management, air congestion management, traffic management, other resource management, and their supply chain management; the size of the collected data is tremendous and especially using Internet of Things technologies, the amount increases logarithmically. Hence, the proposed solutions for such complex systems should be well-designed and comprehensive modelling approach like ontological approach.

In addition, most of the control methods in smart city domain are rapid, adaptive and intelligent solutions underpinned with artificial intelligence and system theory. One of the most fundamental key problem in smart city is to manage the energy in building and district levels using multiple energy sources including thermal, electrical and renewable energies.  Since the near real-energy management in the smart city concept is a function of very complex variables, to implement an analytical solution will not be an answer, as the occupants will expect fast and rapid responses from the proposed solutions   to reduce and optimise their energy bills. Moreover, the integration of the water management in such complex optimisation models will increase the complexity of overall architecture. Therefore, an ontology added modelling underpinned with artificial intelligence added method may provide a robust integrated solution which then can be extended using web technologies to manage monitor and control over smart devices. 

For more information about the project and informal enquiries, please contact the primary supervisor: Dr Baris Yuce

Information about current fees can be found here: https://www.exeter.ac.uk/pg-research/money/fees/

Information about possible funding sources can be found here: http://www.exeter.ac.uk/pg-research/money/alternativefunding/ 

Entry requirements

Applicants for this research project must have obtained a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology Experience in Engineering is desirable.


If English is not your first language you will need to meet the English language requirements and provide proof of proficiency. Click here for more information and a list of acceptable alternative tests.

How to apply

 You will be asked to submit some personal details and upload a full CV, covering letter and two academic references. Your covering letter should outline your academic interests, prior research experience and reasons for wishing to undertake this project. You may also be asked to upload verified transcripts of your most academic qualification.

If you have any general enquiries about the application process please email emps-pgr-ad@exeter.ac.uk
Please quote reference 3069 on your application and in any correspondence about this project.

Summary

Application deadline:10th June 2018
Value:This project is self-funded
Duration of award:Not applicable
Contact: EMPS Postgraduate Research Office emps-pgr-ad@exeter.ac.uk