Looking to list your PhD opportunities? Log in here.
This project is no longer listed on FindAPhD.com and may not be available.
Click here to search FindAPhD.com for PhD studentship opportunitiesAbout the Project
Please refer to application reference SCEBE-20-027-MMSF
About the project
Indoor positioning is still an open problem with wide-ranging applications such as automatic guidance for people or robots, and augmented reality systems. It is usually hard for people to find their way in large buildings such as hospitals, universities, museums. The same is true for mobile robots that need to operate in indoor environments. The proposed system should be able to pinpoint indoor location and direction. That could be done deploying specially designed light-based beacons and an ad-hoc receiver, or by using a small camera. In the case of mobile robots, this approach could be improved using an additional light sensing device to improve positioning resolution at particular locations.
This approach can be readily used to produce real-time navigation instructions. Additionally, the system could keep track of the position of all devices present in the building to take actions under safety alerts.
Aims
The device will be very low-cost, low-power, based on light communications with ceiling-mounted beacons. These beacons can be deployed as stand-alone ones or implemented on current LED luminaires. This system determines current position and orientation, which is key for any mobile platform (or person) moving inside a building.
This PhD will extend an existing low-cost light-based positioning system, which was recently nominated by The Times Higher Education as innovation of the year at UK universities, to improve its resolution and also determine orientation with additional receivers and expand it to wider area coverage using regular cameras. The new device should be readily adapted to any mobile platform requiring indoor positioning, either having a camera or making use of the specialized receiver.
Specifications
The successful applicant will hold a UK honours degree (or equivalent) on Electronic Engineering (2:1 or above) or a Masters degree. Equivalent professional qualifications and any appropriate research experience may be considered. A minimum English language level of IELTS score of 6.5 (or equivalent) with no element below 6.0 is required.
Candidates are requested to submit a more detailed research proposal with their own view of the project area as part of their application (of a maximum of 2000 words).
How to Apply
Applicants will normally hold a UK honours degree 2:1 (or equivalent); or a Masters degree in a subject relevant to the research project. Equivalent professional qualifications and any appropriate research experience may be considered. A minimum English language level of IELTS score of 6.5 (or equivalent) with no element below 6.0 is required. Some research disciplines may require higher levels.
Candidates are encouraged to contact the research supervisors for the project before applying. Applicants should complete the online GCU Research Application Form, stating the Project Title and Reference Number (listed above).
Please also attach to the online application, copies of academic qualifications (including IELTS if required), 2 references and any other relevant documentation.
Applicants shortlisted for the PhD project will be contacted for an interview.
For more information on how to apply and the online application form please go to:
https://www.gcu.ac.uk/research/postgraduateresearchstudy/applicationprocess/
Funding Notes
See more on fees and funding. https://www.gcu.ac.uk/research/postgraduateresearchstudy/feesandfunding/
References

Search suggestions
Based on your current searches we recommend the following search filters.
Check out our other PhDs in Glasgow, United Kingdom
Check out our other PhDs in United Kingdom
Start a New search with our database of over 4,000 PhDs

PhD suggestions
Based on your current search criteria we thought you might be interested in these.
PhD Position: Rare-earth based photonic devices for quantum information processing
UNSW Sydney
PhD in Boron-based Optoelectronic Organic Materials for electroluminescent devices
University of St Andrews
Use of Deep Learning for Image-Based Fruit Trees Disease Detection on Edge Devices.
Glasgow Caledonian University