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Intelligent-lifi for simultaneous 3d sensing and motion estimation and communication

   School of Energy and Electronic Engineering

   Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Applications are invited for a self-funded, 3-year full-time or 6-year part time PhD project.

The PhD will be based in the School of Energy and Electronic Engineering and will be supervised by Dr John Chiverton.

The work on this project could involve:

  • Hardware development for light based communication and 3D sensing;
  • Signal processing using data captured in real-time on dedicated signal processing platforms;
  • Machine learning and 3D computer vision algorithm development.

Project description

Intelligent Light Fidelity or I-Lifi is a new concept that brings together the cutting edge communication technology, Lifi with 3D sensing and motion estimation. This project will involve the development of signal processing systems to perform simultaneous communication and 3D sensing using both visible light and infra-red. Transceiver arrays of modulated light waves will need to be designed that enable both the communication of information combined with distance sensing for 3D sensing and motion estimation using eg time-of-flight (tof) techniques. The developments should include new modulation techniques in terms of the underlying theory. Their implementation will also need to be considered using appropriate hardware developments ranging from analogue signal conditioning through to digital processing. The developed system should also be adaptive, allowing for additional hubs and modifications to their spatial arrangements.

Potential benefits of the results of this research include privacy preserving monitoring of public spaces, home monitoring for safety and or security. Technologically, a developed system could provide more accurate depth and 3D motion information compared to traditional visual based CCTV capture by taking advantage of existing the communication benefits of Lifi.

This research will provide ample opportunity for you to develop your knowledge of digital and analogue signal processing techniques at both the hardware and software levels. These advanced techniques and concepts would make you eminently employable in both academia and industry.

The research will be undertaken in the Schools of Energy and Electronic Engineering and Mechanical and Design Engineering with ample access to well equipped laboratories for electronics, mechanical design and manufacture and communication systems. The supervisory team has extensive experience in research and teaching in a wide range of signal processing applications including intelligent signal processing for 3D imaging and communication signal sensing.

General admissions criteria

You'll need a good first degree from an internationally recognised university or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

Specific candidate requirements

Applicants will need an engineering, physics or computer science background with a significant electronics, signal processing and or applied machine learning component coupled with a strong interest in signal processing, communication systems and or machine learning.

How to Apply

We encourage you to contact Dr John Chiverton () to discuss your interest before you apply, quoting the project code below.

When you are ready to apply, please follow the 'Apply now' link on the Electronic Engineering PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process. 

When applying please quote project code: SENE5691023.

Funding Notes

Self-funded PhD students only.
PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK students only).

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