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.
If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.
As Senior Engineering Manager of Analytics at Seagate Technology I utilise the learning from my PhD ever day
Adrian Johnston - PhD in InformaticsWatch Video
Monday 6 August 2018
mid August 2018
When applying for this PhD opportunity please quote reference number: