PhD Study : IoTools: Tools to support collection, processing, visualisation and sharing of data from IoT devices.

Summary

The explosive growth in the number of devices connected to the Internet of Things (IoT), coupled with the associated exponential increase in data consumption, demonstrates how the growth of big data analytics perfectly overlaps with that of IoT. The management of this data in a continuously expanding network gives rise to non-trivial concerns regarding data collection efficiency, data processing, analytics, and security (Davies, 2017,). To address these concerns, researchers have examined the challenges associated with the successful deployment of IoT. The convergence of big data, analytics, and IoT, creates several opportunities for flourishing big data and analytics for IoT systems. The value of IoT will come from sharing of information (Nugent, 2016, Synnott 2016). For this to flourish, however, will require the development of automated tools for the capture, processing, validation, visualisation and interpretation of this information (Cleland, 2016).

The aim of this project is to develop automated tools to facilitate the collection, processing, inference, visualisation and sharing of data from IoT devices. The project will leverage aspects of big data and data analytics to widen access to available data in an open science research context. These tools will be applied to application areas within smart cities and connected health.

The objectives of the research are:

1.To investigate and implement intelligent gateway solutions that provide seamless integration and interoperability between various protocols for data collection.

2.To develop enhanced solutions by adding context and meaning to data and helping users process and utilise heterogeneous IoT data at the device, gateway, and cloud levels with various scopes and granularities.

3.To facilitate data sharing through the creation of tools for the intelligent interpretation and visualisation of  IoT data.

4.To engage with stakeholders from multidisciplinary and intersectoral backgrounds including clinical, municipality, industry and research to develop and evaluate these tools.

5.To validate the use of these tools within smart cities and connected health paradigm.

This project will be aligned with the aims of the Connected Health Innovation Centre (CHIC) at Ulster.

Cleland, I., Nugent, C. and Lee, S., 2016, May. The ground truth is out there: challenges with using pervasive technologies for behavior change. In Proceedings of the 10th EAI International Conference on Pervasive Computing Technologies for Healthcare (pp. 322-325). ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering).

Davies, N. and Clinch, S., 2017. Pervasive Data Science. IEEE Pervasive Computing, 16(3), pp.50-58.

Nugent, C., Cleland, I., Santanna, A., Espinilla, M., Synnott, J., Banos, O., Lundström, J., Hallberg, J. and Calzada, A., 2016, May. An initiative for the creation of open datasets within pervasive healthcare. In Proceedings of the 10th EAI International Conference on Pervasive Computing Technologies for Healthcare (pp. 318-321). ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering).

Synnott, J., Nugent, C., Zhang, S., Calzada, A., Cleland, I., Espinilla, M., Quero, J.M. and Lundstrom, J., 2016, May. Environment simulation for the promotion of the open data initiative. In Smart Computing (SMARTCOMP), 2016 IEEE International Conference on (pp. 1-6). IEEE.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• First Class Honours (1st) Degree
• Masters at 70%

Funding and eligibility

The University offers the following levels of support:

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,000 (tbc) per annum for three years (subject to satisfactory academic performance).

This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

• Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
• Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
• Other non-ROI EU applicants are ‘International’ are not eligible for this source of funding.
• Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies. Further information on cost of living