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Innovative Industrial Research group

We research the use of machine learning/AI to solve the most pressing industry challenges of tomorrow.

Within the Innovative Industrial Research Group, we're working on improving performance through the integration of AI into products and services.

The research we're doing can be applied across many different industries, from dairy processing to aviation services. We've collaborated on research projects with national and international companies and organisations – including STS Defence Ltd, Flight Data Services (FDS) Ltd, L3 ASV Ltd and Primority Ltd.

We work with our clients to identify where machine learning can have the greatest positive impact, then focus on how we can help integrate new technology into a company's existing infrastructure and culture.

Our research has been funded by major bodies – such as Innovate UK, the Engineering and Physical Sciences Research Council, the Defence Science and Technology Laboratory, and the European Union (EU) – and our work is focused on overcoming the barriers that are preventing companies from adopting machine learning, including:

  • Data - storage is becoming cheaper all the time, but it can be unclear what types of data should be collected, and how frequently
  • Staff - there is a real shortage of staff trained in data engineering and data analysis
  • Algorithms - Algorithms need to be customised for a particular task, depending on data volume and labelling, which can vary dramatically from business to business

To overcome these obstacles, we've made increasing the intelligence of our algorithms a constant pursuit. By advancing semi-supervised learning, unsupervised learning and the development of a common learning architecture, we're making it easier for businesses to adopt machine learning, especially in Small to Medium Enterprise (SMEs), where such an investment would normally be more difficult to justify.


Our research covers the following topics


  • Predicting anomalies within milk filling machines at UK dairies
  • Detecting product defects on high speed production lines
  • Identifying anomalies within the supply chains of food companies to improve food safety


  • Developing predictive maintenance algorithms for marine vessels
  • Predicting anomalies on the powertrain and battery pack of autonomous surface vessels
  • Using machine learning to minimise the impact of rail delay
  • Reinforcement learning based decision making for autonomous Systems and optimal scheduling for complex systems
  • Monitoring abnormal small vessel activity (e.g. fishing and pleasure vessels)

High-performance Computing

  • Optimising data centre server power consumption
  • Optimising data centre storage energy usage

Areas of expertise

The work we're doing in the Innovative Industrial Research Group maps to the following areas of research expertise.

Transportation and Maritime Systems

Our research focuses on developing innovative optimisation models and decision support systems, to help improve the mobility of people, goods and services.

Portsmouth Harbour with historic dockyard ships and ferries
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Research projects

Find out more about our most recent research projects – including those that are currently underway and about to begin.

We're currently working with Primority Ltd and Food Standards Scotland on a project funded by Innovate UK, using machine learning to detect anomalies within food supply chains that could lead to food safety/allergen incidents, or expensive product recalls.

We're also working with SubSea Craft Ltd to develop prognostics algorithms for their highly novel diver delivery vessel VICTA, funded via the Knowledge Transfer Project scheme.

Our Ministry of Defence-funded project with STS Defence Ltd, a Gosport based SME, aims to develop fault detection algorithms for acoustic and vibration sensors on military submarines.

We have two projects Innovate UK funded projects with Sirius Constellation Ltd, listed in Pure as "Autonomous Maritime Data Analytics" and "Small Vessel Detection And Tracking" project You could write this as ... "

We are working with Sirius Constellation Ltd on two projects funded by Innovate UK to develop machine learning algorithms that can detect and identify small vessels that are not broadcasting on AIS (automatic identification system) as well as identify any unusual activity in their pattern of life.

We recently won a double Knowledge Transfer Partnership (KTP), to work with STS Defence in developing an intelligent communications unit, to select the appropriate communications bearer for onward data transmission based on cost, data urgency and bearer availability

We've worked with Flight Data Services (FDS) Ltd, a Whiteley based SME, in developing ways to improve the analysis of commercial aviation data. Through 3 Knowledge Transfer Partnerships (KTPs) and an EPSRC Industrial CASE studentship, we helped FDS create new products and services, as well as aided in the development of a data orientated culture.

We've worked with Stork Food and Dairy Systems to develop predictive monitoring for milk filling machines. Catastrophic breakdowns can cost upwards of £300,000 per day in lost production, repairs and breach of supermarket supply contracts. We helped develop The Virtual Engineer, which uses anomaly detection algorithms to detect the first initial signs of a fault, and alert the user so that it can be addressed during normal maintenance. It's estimated to have saved at least £2 million.


Past and present research is conducted in partnership with many different organisations, including:


  • Flight Data Services Ltd
  • STS Defence Ltd
  • Primority Ltd
  • Food Standards Scotland
  • KCC Ltd
  • L3 ASV Ltd
  • Houlder Ltd
  • SeaRoc Group Ltd
  • Offshore Catapult
  • Muller Wisemann Ltd
  • Moodys Ltd
  • Britpip Ltd
  • TPG Services Limited (Polaris)
  • First MTR South West Trains Limited
  • Satellite Applications Catapult
  • BMT Argoss
  • SoftIron Ltd
  • Hyperdrive Ltd
  • Xyratex Ltd (now owned by Seagate Technology Ltd)
  • Prosig Ltd


  • University of Sheffield
  • University of Edinburgh
  • University of Southampton
  • University of Nottingham

Our members

Edward Philip Smart Portrait

Dr Edward Smart

Principal Research Fellow


School of Energy and Electronic Engineering

Faculty of Technology

PhD Supervisor

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Hongjie Ma Portrait

Dr Hongjie Ma

Senior Research Fellow


School of Energy and Electronic Engineering

Faculty of Technology

PhD Supervisor

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Mrs Farsiya Afaque Ahmed

KTP Associate (Software Engineer for Data Science Application)


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