Projects

Take a look at all the projects we are and have been working on over the years.

Past projects

Start date:

End date:

Start date: October 2018

End date: December 2019

Start date: 2017

End date: 2018

Start date: November 2016

End date: October 2019

Start date: October 2016

End date: September 2019

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Start date:

End date:

Partnership projects

Explore the partnerships we have had over the years.

Knowledge to action partnerships

  • Dates: 14 March 2011 - 12 August 2011
  • Funder: EPSRC (EP/H500189/1)
  • Funding amount: £21,094
  • Investigator: Antony Browne.

Summary

With the emergence of consumer devices capable of generating sensor data in real-time, there is a need for data mining techniques to make use of this data. One such area is the use of portable electroencephalograph (EEG) which can indicate different states of brain activity, such as sleep or concentration.

Alpha-Active Ltd is an SME specialising in the development of EEG products which are used by customers to monitor EEG in real-time. Example customers include cognitive therapists, where EEG is used in therapies for addiction and chronic pain, and elite sports coaching, such as for archery and motorsport. However, one of the areas that Alpha-Active would like to develop is the use of real-time user feedback. The aim is to give the sports person feedback that is indicative of a figure of merit derived from the EEG data recorded during optimum performance. This may also be used to help patients in managing long term illness. While Alpha-Active can record and play back EEG signals, they lack the classification techniques needed to provide useful feedback for users.

Objectives

In this project, we propose to apply Surrey’s research on data mining in Alpha-Active’s product. We will develop a proof-of-concept plug-in for their HeadCoach product to classify EEG signals in real-time.

Impacts

The key outcome is to evaluate whether neural network techniques can be applied to the real-time analysis of EEG signals in Alpha-Active’s product. This will be achieved through the development of a proof-of-concept. If successful, the potential is for development into a customer product for Alpha-Active.

    • Dates: 1 July 2010 - 30 September 2012
    • Funder: EPSRC (EP/H500189/1)
    • Funding amount: £65,171
    • Investigator: H Lilian Tang.

    • Dates: 7 June 2010 - 6 December 2010
    • Funder: EPSRC (EP/H500189/1)
    • Funding amount: £40,000
    • Investigator: Paul Krause.

    Summary

    Over the last two years we have developed Bayesian Network (BN) models for the estimation of Greenhouse Gas (GHG) emissions in the agricultural sector. These capture a corpus of experience on the impact that farm management processes have on GHG emissions, in compliance with the IPCC guidelines. The models' predictions of the farm's total annual CO2 emissions validate well against the total emissions attributed to the UK agricultural sector according to the NAEI records. So far, however, it has not been possible to carry out a more thorough analysis on the reliability of these results given the absence of actual emissions figures at farm level in the UK Agricultural sector.

    Aims and objectives

    These preliminary results show that access to UK or, ideally, Europe wide data on emission figures would enable us to refine the models into a usable tool that would have significant value in aiding the agriculture sector to identifying recommendations for individual farms to optimise their businesses with regard to GHG emissions. Currently the only tool available is CALM provided (FoC) by the Country Land & Business Association (CLA), with support from EEDA and Crown Estates. This assists land managers identify the scale and source of land emissions as part of their corporate and social responsibility. It has been well received as "an excellent first step". However, our BN models can extend this in a number of important ways, such as adding a measure of the potential for carbon sequestration in the farm, and a measure of the costs to the farmer that result from the volumes of GHG emitted as a result of their farming practices.

    This six month project will involve collection of data, evaluation and refinement of the BN models. Support will come from Simon Ward of the CLA and Profs Norman Fenton and Martin Neil of Agena Ltd. Simon Ward will be involved in the user evaluation of the models and data collection. He will facilitate contact with additional agricultural consultants. Agena Ltd will evaluate the models from the perspective of best practice in developing BNs, and advise on their optimization.

      • End date: 3 November 2011
      • Funder: EPSRC (EP/H500189/1)
      • Funding amount: £20,000
      • Investigator: Paul Krause
      • Co-investigator: Sotiris Moschoyiannis
      • Collaborators: Rulemotion and the Institute for Animal Health.

      • Funder: EPSRC (EP/H500189/1)
      • Funding amount: £20,000
      • Investigator: Paul Krause.

      • Dates: 1 February 2011 - 30 June 2011
      • Funder: EPSRC (EP/H500189/1)
      • Funding amount: £20,000 (approx)
      • Investigator: Lee Gillam.

      • Dates: 1 September 2011 - 31 August 2012
      • Funder: EPSRC Knowledge Transfer Account (GR/T10101/01)
      • Funding amount: £51,112
      • Investigators: Yaochu Jin and Andrew Crocombe
      • Collaborators: Industrial partner: Aero Optimal Ltd.

      Summary

      Design of weight efficient Carbon Fibre Reinforced Plastics (CFRP) aero structures is a challenging task due to the following reasons. First, panel design involves in multi-disciplinary criteria such as stress, fatigue, buckling, control surface effectiveness, weight and cost. Second, the complexity of panel design is very high and a large number of parameters need to be optimised. Third, panel design is conducted in the presence of a large number of uncertainties, including changes in loading condition. Finally, the market is increasingly competitive and therefore, the allowed time for design becomes shorter. All these challenges require a generic tool and efficient design tool for panel design.

      The aim of this project is to develop a user-friendly and powerful software tool for CTRP panel design. The software consists in a number of the state-of-the-art optimisation algorithms that can be chosen by the user. In addition, different criteria can also be specified for different purpose. The choice of optimisation algorithms, optimisation criteria as well as the constraints for optimisation can be made using a graphic user interface.

        • Dates: 1 October 2010 - 31 May 2011
        • Funder: EPSRC (EP/H500189/1)
        • Funding amount: £19,500
        • Investigator: Paul Krause.

        • Dates: 21 December 2009 - 2 July 2010
        • Funder: EPSRC (EP/H500189/1)
        • Funding amount: £17,194.

        Summary

        Understanding how neurobiological systems can process sensory information rapidly is an area of research which would benefit from exploitation. At Surrey, research into sensory systems has focused on the importance of low-level processing.

        For example, the superior colliculus is a small structure in the midbrain of humans that automatically orients our eyes to a movement, sound or touch that occurs around us. This automatic orientation is an important function that allows us to prioritise resources sub-consciously.

        Research into these low-level structures has taken place at Surrey as a result of an EPSRC funded workshop. The workshop brought together an interdisciplinary team to share expertise on how to combine sensory stimuli. The knowledge and collaborators gained from this workshop resulted in models of low-level sensory structures that have proven effective. The novelty of the developed technique is its ability to adapt its behaviour in response to arbitrary target stimuli. Nobody else has achieved this for multi-sensory inputs.

        Objectives

        In this project, we propose to apply Surrey’s model of adaptive low-level sensory processing to imagery systems from Waterfall Solutions. With a proof-of-concept, we hope to demonstrate that Surrey’s adaptive techniques can be applied to real-world tasks.

        Impacts

        The key outcome is to evaluate whether Surrey’s technique can be exploited. This will be achieved through the development of a proof-of-concept.  Further exploitation will be evaluated during the project.

        • Dates: 1 July 2010 - 31 December 2010
        • Funder: EPSRC (EP/H500189/1)
        • Funding amount: £20,000.