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Security for mass scale remote health monitoring using IoT and machine learning

About This PhD Project

Project Description


Currently, research into security for wearable devices using Internet of Things (IoT), for controlling patients’ health indicators remotely is of interest. This is motivated by the need for advanced security and sophisticated requirements necessary for health monitoring and
preventive medicine compared to the large number of patients and elderly people. On the other hand, people are looking for another way to be monitored by their physicians instead of going to the clinics, especially in emergency cases. This can be done through the
application of wearable devices to ensure reliable health monitoring , by continuously keeping under observations of healthy parameters. As this remote health monitoring needs a consistent wireless communication, low power devices embedding long range wide area network (LoRaWAN) protocols (a license free technology), is also required to ensure a continuous communication between wearable devices worn by the patients and their respective doctors. It is also important to note that LoRaWAN device have the capability of saving energy through energy harvesting techniques. Therefore, this research will evaluate and propose the enhanced security mechanisms to remotely monitor patients by applying LoRaWAN (IoT platform) device, and using machine learning.


- Investigate the performance of security for existing health monitoring technologies.
- Investigate the energy reduction techniques to be used with security.
- Propose the enhanced method of security for health monitoring by applying LoRaWAN technology and advanced machine learning.
- Perform a consistent healthy monitoring and provide real-time (real-life) measurements (real-time vital signs) using low power LoRaWAN equipped with energy harvesting techniques and evaluating security vulnerabilities.
- Reduce the overall costs for prevention and monitoring using wearable devices embedding LoRaWAN technology with security.
- Evaluating the impact of Life saving due to the efficient monitoring of remote patients


The successful applicant will be able to demonstrate possession of some or all of the following
skills: IoT, security, machine learning, tele health, and security.

Additional application requirements:
Candidates are requested to submit a single document (maximum 1,000 words) briefly explaining a general methodology and a list of potential tools to be used for the implementation of this project.

Research Strategy and Research Profile

Glasgow Caledonian University’s research is framed around the United Nations Sustainable Development Goals, We address the Goals via three societal challenge areas of Inclusive Societies, Healthy Lives and Sustainable Environments. For more. This project is part of the research activity of the following Research Groups:
- Cyber Security, Networking and Communications (CNSC)
- Musculoskeletal health Research Group

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.

Please send any enquiries regarding your application to: 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

Dr Kenneth Owens -

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