Funding

Self-funded

Project code

SEM10400526

Start dates

October, February and April

Application deadline

Applications accepted all year round

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 Electrical and Mechanical Engineering and will be supervised by Dr Salem Aljareh.

 

The work on this project will:

  • Investigate the most suitable indoor tracking technologies and techniques to achieve robust and precise indoor localisation, even in challenging conditions.
  • Design algorithms and systems to provide real-time navigation assistance to first responders during emergency situations, enabling them to reach their destinations rapidly and track other team members efficiently.
  • Design the system while considering compatibility and seamless integration with existing emergency response infrastructure, allowing for rapid deployment and widespread adoption.
  • Highlight how work carried out in this project directly contributes to saving lives by improving the precision and speed of indoor navigation for first responders during critical situations.

 

 

According to recent statistics released by the UK’s Home Office In the year ending June 2025, England's “Fire and Rescue Services 628,764 incidents in the year ending June 2025, an increase of 5.7% compared with the previous year (594,836). Of these incidents, there were 165,697 fires, which was an increase of 28% compared with the previous year (129,638). In an era where rapid and precise emergency response is paramount, the Enhancing Emergency Response with Indoor Tracking and Localisation project at the University of Portsmouth embarks on a mission to revolutionise indoor navigation and tracking for first responders, aligning with the University of Portsmouth's dedication to research that addresses real-world challenges.

The project addresses a critical need in a wide range of emergency response scenarios. Whether it's firefighters rushing into a burning building, paramedics navigating through crowded spaces, or law enforcement officers responding to security breaches, every second counts. This project aims to tailor recent advances in indoor navigation technology to enable emergency responders to better navigate indoor environments with speed and precision reducing incident response times.

Traditional GPS systems are excellent for outdoor navigation but fall short when responders enter buildings, where satellite signals are significantly weaker. Our approach is multidimensional, focusing on the integration of multiple sensor technologies. We can leverage Wi-Fi, RFID and Bluetooth Low Energy (BLE) to create a comprehensive indoor positioning system suitable for such scenarios and use cases. This fusion of technologies enables precise tracking even in scenarios with limited visibility, such as smoke-filled buildings. 

The project will investigate cutting-edge tracking and locating technologies to propose a comprehensive indoor navigation system that can be easily deployed for emergency services, providing active, real-time navigation to the incident location and tracking of other team members and their whereabouts.

 

 

Fees and funding

Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

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

 

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

Entry requirements

You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in a related area. 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.

 

Candidates should hold a relevant degree such as computer science, electrical engineering, electronic engineering or a related discipline. Knowledge in sensing technology, machine learning, data analytics, radio signals, Digital Signal Processing (DSP) and software development. The candidate should also demonstrate  strong programming in MatLab/python/java and mathematical analysis skills. Experience in C/C++ programming is desirable. This PhD study is part of a collaboration between the university and an industrial partner (leading company in technology and engineering) and the candidate will benefit from the collaboration during and after the study.

 

How to apply

We’d encourage you to contact Dr Salem Aljareh  (salem.aljareh@port.ac.uk) to discuss your interest before you apply, quoting the project code.

 

 

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.

If you want to be considered for this self-funded PhD opportunity you must quote project code SEM10400526 when applying.