Anglia Ruskin University ARU Featured PhD Programmes
Anglia Ruskin University ARU Featured PhD Programmes

Augmented Reality Technology for Emergency First Responders PhD


School of Aerospace, Transport and Manufacturing (SATM)

Mr Samuel Court Applications accepted all year round Self-Funded PhD Students Only

About the Project

Cranfield University and the Centre for Digital Engineering and Manufacturing are seeking a top class candidate to undertake research in augmented reality leading to a PhD award. This exciting PhD will focus on delivering the visualisation opportunity for the next generation of emergency first responders. We are aiming to create the platform for automation of data processing to enable its visualisation at the point of need within a time efficient manner. This needs to also be flexible with the different stakeholders, and their associated skills. 

Background

This PhD provides the next generation of emergency first responders with the key contextual data overlaid in real-time to assist their vital role in dealing with emergency situations. The research will develop a real-time system able to visualize essential information in a number of example use case demonstrations – for example: search and rescue, fire-fighting, paramedic remote assistance and crowd control.

Situational awareness is key to prioritising emergency response. With additional sensor data and knowledge shared by other operators, Augmented Reality provides the ready means to enhance response times and link directly with control room operators. The research will explore the potential of these technologies in a series of case study investigations.

The potential technology has cross-over potential for commercial applications where consumer activity can be enhanced in real-time, expert-led training provided at the point of need or specific behaviour guidance in health and safety related scenarios.

Aim

The aim of the PhD is to develop an AR solution that focuses on assisting the next generation of emergency first responders. The solution is expected to support a wide-range of scenarios that the first responder will be involved in such as: 

Search and rescue – hazard detection, vital sign indication, beyond-visual sight enhancement

Firefighting – thermal vision, structural integrity, indoor navigation

Paramedic – diagnostic data, medical records, specialist remote assistance

The research is expected to include many concepts and technologies: Internet of Things (IoT), big-data analytics, AI, AR/VR. Consideration should be given to these concepts and the scalability of these to enhance the productivity of first responders. The project should consider what information or data needs to be provided within the context of emergency scenarios 

The AR solution will provide real-time support to the first responder in various areas such as: a) information overlay, b) sensor integration, c) situational awareness and d) prioritisation. Each of these areas provide distinct benefits to the operator and demonstrate the art of the possible with emerging technologies and embedded sensors.

Objectives

Conduct literature review to identify best practice in AR

Identify suitable use cases for the AR platform

Construct an AR solution for the next generation of emergency first responders

Establish a framework for AR-enhanced guidance for emergency first responders

At Cranfield, the candidate will be based at the Centre for Digital Engineering and Manufacturing, which hosts cutting-edge simulation and visualisation facilities. The student will have access to high-end computers for constructing the proposed solution. There will be relevant opportunities throughout the PhD to develop and demonstrate the research. 

Entry requirements

Candidates should have a minimum of an upper second (2.1) honours degree (or equivalent) preferably in Computer Science/ Computer Vision / Mathematics / Informatics but candidates in other degrees related to Engineering or related quantitative fields would be considered. Candidates with an MSc degree in these disciplines will be desirable.


Funding Notes

This is a self-funded PhD; open to UK, EU and International applicants.

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