Summary

Sensor systems need to be able to sustain operation long periods of time (years) and be reliable in harsh and often remote environments, e.g. bridges, deep in forests, along vast border areas [1].

This PhD project will innovate in engineering a ‘smart’ sensor system which is highly reliable in facilitating an intelligent ‘always-on’ sensing capability; it will enable a new generation of smart always-sensing systems. The project aims to:

(1) demonstrate the autonomous detection and prediction of events e.g. environment/structure anomalies, using leading edge brain-inspired computational algorithms such as astrocyte-neuron networks [2] and

(2) demonstrate high reliability capabilities of the computational algorithms in FPGA hardware [3].

Therefore, the aim is to develop a highly novel system architecture that is ‘smart’ in processing sensory information, and self-adaptable to errors/faults over long time scales (years). Fundamentally, the research aims to prototype a smart sensor system, which integrates a novel, neural FPGA-based processor with existing sensors. The core objectives are defined as:

1. Investigate an astrocyte-neuron network (smart algorithm) which performs detection and prediction of environment/structure anomalies.

2. Benchmark the ‘smart’ algorithm performance against traditional approaches [4-6].

3. Use existing hardware blocks [3] to implement the smart algorithm in FPGAs.

4. Develop an FPGA hardware demonstrator of always-on smart sensor system, evaluate it and benchmark hardware reliability.

The successful student will be located at the Intelligent Systems Research Centre on the Magee campus of the Ulster University.

Anticipated Outcomes

The anticipated outcome of the project will be a new scalable solution to self-repair in future computing systems. A highly novel self-repairing embedded hardware architecture will be developed with wide impact on the Electronic Systems research community. Also, several published conference and journal papers on the performance of the proposed mechanisms.

Resources Access to modern Altera FPGAs and a large suite of Agilent logic analyser/oscilloscope instrumentation; existing in-house FPGA-based astrocyte-neurons [3] available; data and tools on astrocyte-neuron network modelling; and access to real-world sensor data from forest fires.


Essential criteria

  • To hold, or expect to achieve by 15 August, an Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC) in a related or cognate field.
  • Experience using research methods or other approaches relevant to the subject domain

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%
  • For VCRS Awards, Masters at 75%
  • Publications - peer-reviewed

Funding

    The University offers the following awards to support PhD study and applications are invited from UK, EU and overseas for the following levels of support:

    Vice Chancellors Research Studentship (VCRS)

    Full award (full-time PhD fees + DfE level of maintenance grant + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees and provide the recipient with £15,000 maintenance grant 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.

    Vice-Chancellor’s Research Bursary (VCRB)

    Part award (full-time PhD fees + 50% DfE level of maintenance grant + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees and provide the recipient with £7,500 maintenance grant 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.

    Vice-Chancellor’s Research Fees Bursary (VCRFB)

    Fees only award (PhD fees + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees 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.

    Department for the Economy (DFE)

    The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £15,285 per annum for three years. EU applicants will only be eligible for the fee’s component of the studentship (no maintenance award is provided). For Non-EU nationals the candidate must be "settled" in the UK. 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.

    Due consideration should be given to financing your studies; for further information on cost of living etc. please refer to: www.ulster.ac.uk/doctoralcollege/postgraduate-research/fees-and-funding/financing-your-studies


Other information


The Doctoral College at Ulster University