Smart Environments Research Facility

Lead Research Organisation: University of East Anglia
Department Name: Computing Sciences


This multifunctional equipment request will contribute to a Smart Environments Research Facility at UEA and builds on EPSRC-facing research within the School of Computing Sciences at UEA and is made in the context of 3 of the Grand Challenges of the UK Industrial Strategy, namely (i) artificial Intelligence and data, (ii) ageing society and (iii) the future of mobility. The equipment requested will enhance the laboratory facilities in direct support of the research activities of established and early-career researchers and PhD students from across the School of Computing (CMP), and in support of projects linking with Norwich Medical School (MED) and the School of Environmental Sciences (ENV).

The equipment requested will enable the cohort of researchers to further develop and leverage their research with organisations such as Turing, BT , Quadram Institute and others linked to existing EPSRC Research Grants and position them to further develop new internationally leading proposals to EPSRC. A value add will be promotion of the Working Together agenda in support or research linked to joint EPSRC-NERC and EPSRC-BBSRC collaborations. In addition, we will also target opportunities under the joint EPSRC-Science Foundation Ireland Programme.

The facilities requested will enable us to generate more complex experiments that require increased multi-core compute, storage and higher speed network connections to generate better quality data and further our understanding of algorithmic performance and prototype models. Our five research laboratory groups in the School will benefit as follows and further examples are provided in the attached Case for Support and Appendices.

Planned Impact

The equipment we have requested and listed in the JoR will have immediate impact on PhD students and PDRAs working on projects in the School linked to companies such as BT and Aviva. This includes projects to further develop research by ECRs who have been working with the Turing Institute on the "sktime": A toolbox for data science with time series classification. They will benefit from having access to higher performance systems with increased compute and storage capacity to support multiple parallel experiments that generate higher volumes of data to stress test their algorithms. Across the timeline of key activities as indicated in the workplan we will ensure that early stage impact is achieved by bringing systems on-line in the first 3 months of the project roll-out and then to maintain them beyond the period of the grant.

UEA School of Computing Sciences (CMP)
We have a track record or organising various platforms to promote wider collaboration and knowledge of our research. Going beyond the traditional, CMP (GP) has organised "Birds of a Feather"(BoF) meetings with scientists on the Norwich Research Park who are engaged with large-scale experiments for BBSRC and NERC that generate significant amounts of multi-faceted research data linked to animal, plant and human health. Once our new equipment has been commissioned and becomes operational, we will seek to hold bi-annual BoF meetings to highlight our joint research and also seek news opportunities for further collaboration.

Knowledge, People, and Skills:
Key skills and insights will be linked to the design of algorithms and ensembles that will be able to cope with increased computational complexity and increased data payloads in real-time. Such insights will also impact on the compute/storage/networking resources required, but they will also include improved understanding of the energy-requirements of such systems.

A direct impact of the cohort's research to date is the training of PhD and PDRAs as the next generation of scientific researchers. Of these, several have already gone on to hold either academic or industrial research positions in companies such as BT, IBM, and Apple, benefitting the UK's knowledge economy and the ICT skills base for our Connected Nation. With enhanced equipment facilities, the cohort can continue to train our future scientists in a broader contact to address key scientific and engineering challenges such as providing trustworthy systems for low-cost and low power universal services provision for Connected-UK, taking into account the need for scalable solutions that are robust to attack and failure. In support of ECRs we will also explore development of specific training courses within the School for Data Science and AI tools that will support PhD and MSc researchers. These will be developed and organised during our operational phase. In particular, students our DTPs and new EPSRC CDT in Agri-Robotics and our new MSc in Cyber Security (developed in collaboration with BT Adastral Park, IBM and the Police) will benefit.
We will also provide Mentoring to our PDRAs and ECRs to assist with preparing new grant proposals that can leverage the equipment from this award to support industry-relevant research. By introducing such initiatives we will address ICT priorities for the future skills pipeline in areas linked to the needs UK economy that have been identified in the UK Industrial Strategy, e.g. AI Tools and systems, Mobility, 5G, robust software engineering and data science.


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