Smart Technology Research Projects
Research projects:
Current projects
Description: The INFER project investigates adaptive software systems for the development of an open, modular software platform for predictive modelling applicable in different industries and a next generation of adaptive soft sensors for on-line prediction, monitoring and control in the process industry.
Funded by: European Commission within Marie Curie Industry and Academia Partnerships & Pathways (IAPP) programme
STRC role: Project leader coordinator
Contact person: Bogdan Gabrys
Staff involved: Bogdan Gabrys, Petr Kadlec, Marcin Budka, Katarzyna Musial, Christiane Lemke, Christos Gatzidis
Development of a Epidural Simulator for virtual training and administration
in collaboration with
Poole Hospital
Jan. 2010 - Dec. 2012
Description: The project investigates the development of a virtual and physical model which can interpret the ultrasound images and tactile feedback similar to that of a human body in order to assist the training of anaesthetists and epiduralists in this procedure, thereby reducing morbidity in patients.
Funded by: Poole Hospital & Bournemouth University
STRC role: Project leader
Contact person: Neil Vaughan
Staff involved: Neil Vaughan, Venky Dubey, Bogdan Gabrys
Description: In the treatment of stroke, there has recently been a greater emphasis placed on rehabilitation of the hand and arm and a number of new techniques developed. This programme of research seeks to improve significantly the rehabilitation of the hand and arm following a stroke by investigating the use of assistive technologies to maximise function.
Funded by: NIHR Programme Grant for Applied Research
STRC role: Co-Investigator
Contact person: Ian Swain
Staff involved: Ian Swain and Duncan Wood
Probabilistic modelling of customer behaviour using nature-inspired hybrid optimisation techniques
in collaboration with
Bristol University and
British Telecom
Nov. 2009 - Nov. 2012
Description: The ability to predict and deliver the best interaction with respect to every single customer is important to the business of a company. It is also important with respect to the predicted various business processes and their execution. Gaussian processes coupled with nature-inspired learning approaches are studied for tracing and predicting temporal sequences in data based on customer interaction with service providers and business related processes resulting from such interactions and requests.
Funded by: Great Western Research, British Telecommunications plc.
STRC role: Project leader
Contact person: Bogdan Gabrys
Staff involved: Mai Le, Bogdan Gabrys, Petr Kadlec
Description: GRASP# investigates and analyses the social connections and characteristics of people accused and suspected of committing a crime.
Funded by: Polish Ministry of Science and Higher Education
STRC role: Co-investigator
Contact person: Katarzyna Musial
Staff involved: Katarzyna Musial
Description: Peripheral neuropathy, the damage of the peripheral nerve system, can be a result of a different disease such as diabetes, serious infections or occur after chemotherapy for cancer. Patients that suffer from this disability have limitations in their daily life because of the problem of having no sensing feedback from their extremities, which can result in gait or balancing problems and tissue damage. The aim of the project is to improve life of those patients by developing an electrocutaneous feedback system which uses force sensors to detect the pressure that is applied to the foot. The sensor feedback is processed in an intelligent way and is redirected through electrical pulses to areas of the skin that are not affected by sensing loss, creating artificial sensation.
Funded by: Bournemouth University, NHS foundation trust
STRC role: Project Leader
Contact person: Venky Dubey
Staff involved: Jan-Walter Schroeder, Venky Dubey
Description: This project investigates wireless technologies that can be used for Functional Electrical Stimulation (FES) systems and build and test a multi-channel FES system. The system consists of a wireless network of multiple stimulators and intelligent sensors, which will facilitate the use and improve multi-channel FES systems.
STRC role: Co-Investigator
Contact person: Jon Cobb
Staff involved: Choukri Mecheraoui, Jon Cobb, Ian Swain
Description: This project focuses on development of adaptive, scalable algorighms that can be used directly on databases without a need for exporting data outside the database. It investigates the application of classical and relational data mining techniques in the retail industry.
Funded by: Great Western Research, Screwfix Direct ltd
STRC role: Project leader
Contact person: Bogdan Gabrys
Staff involved: Edward Apeh, Amanda Schierz, Bogdan Gabrys
Physically Inspired Artificial Learning Models
in collaboration with
British Telecom
Oct. 2007 - Oct. 2010
Description: The main aim of this research project is to explore and investigate the similarities between physical world and artificial intelligence in the context of machine learning in order to find inspirations and design new nature-inspired classification, clustering and regression techniques that would be capable of learning more efficiently from large sources of uncertain multi-type data and information.
Funded by: Bournemouth University
STRC role: Project leader
Contact person: Bogdan Gabrys
Staff involved: Marcin Budka, Bogdan Gabrys
Recently completed projects
The development of laser Doppler blood flow sensors
in collaboration with
Moor Instruments
2009 - 2010
Description: This work applies advances in laser technology, fibre optics and spectroscopy to obtain clinically useful measures of physiological function by making non-invasive measurements on the skin. Skin blood flow is a useful indicator of the risk of pressure sores. In order to reduce the risk of pressure sores, developing the detection of at risk tissue is required, and can be achieved using techniques such as laser Doppler flowmetry. However, at present the sensing heads of these systems are typically a few millimetres thick, which can aggravate the local pressure problem. Therefore the wider use of this technology in the NHS relies upon reducing the sensing head to around 1mm.
Funded by: South West Regional Development Agency "Proof of Concept"
STRC role: Project Leader
Contact person: Jon Cobb
Staff involved: Jon Cobb
Design of a Gravity-balancing Upper-arm Orthosis for Older People
in collaboration with
University of Delaware
2007 - 2009
Description: This project investigated the creation of a gravity-balancing orthosis to help older people regain or enhance the use of their upper arms during post-stroke rehabilitation.
Funded by: Royal Academy of Engineering, "Engineers in Research and Development" scheme
STRC role: Project Leader
Contact person: Venky Dubey
Staff involved: Venky Dubey
Description: Remote controlled road signs take away the need for men to cross live carriageways to activate and de-activate the signs. This project focuses on the development of the Smart Flow System, which will use GRPS traffic signs and AI to control traffic flow automatically. Benefits of the system will be lower carbon emissions, as workmen will not need to travel to the signs, as well as safer and more efficient travel.
Funded by: South West Regional Development Agency "Proof of Concept"
STRC role: Project Leader
Contact Person: Martin K. Teal
Staff involved: Martin K. Teal
The instrumented swimmer: "Measurement of Performance Analysis Factors of Front Crawl Swimming using Microelectronics"
Oct. 2006 - Sept. 2009
Description: This project investigates the design of hermetically sealed microelectronics placed at strategic locations over a swimmers body for measurement of performance factors of the swimmers technique. Using this approach the coach can track a swimmers progress over time and also provide feedback to the swimmer that cannot always be offered with expensive camera systems.
Funded by: Bournemouth University
STRC role: Project leader
Contact person: Jon Cobb
Staff involved: Andrew Callaway, Jon Cobb, Ian Jones
Self-adapting and Monitoring Soft Sensors for Process Industry
in collaboration with
Evonik Industries
Oct. 2006 - Oct. 2009
Description: This project proposed a conceptual architecture for development of robust and adaptive soft sensing algorithms for process industry. The architecture is organised in a three-level hierarchy, with actual prediction-making models operating at the base level. Predictions are flexibly merged by applying ensemble methods at the next higher level before the underlying algorithms are managed by means of metalearning methods on the top level.
Funded by: Degussa AG, Bournemouth University
STRC role: Project leader
Contact person: Bogdan Gabrys
Staff involved: Petr Kadlec, Bogdan Gabrys
Data Mining and Multi Level Combination for Cancellation Forecasting
in collaboration with
Lufthansa Systems Berlin
Oct. 2006 - Oct. 2009
Description: In airline revenue management, a key task is to determine the time when a lower fare booking class should be closed in order to leave seats for later arriving high fare bookings. This project investigated forecast combination and meta-learning methods with the goal to improve cancellation forecasting in the industry partner's forecasting system.
Funded by: Lufthansa Systems GmbH, Bournemouth University
STRC role: Project leader
Contact person: Bogdan Gabrys
Staff involved: Christiane Lemke, Bogdan Gabrys,
A method for analysis of node position in the network of internet users
Sept. 2008 - Nov. 2009
Description: This project assessed a position of individuals in networked systems. The position was calculated based on the users activities and their interactions.
Funded by: Polish Ministry of Science and Higher Education
Contact Person: Katarzyna Musial
Staff involved: Katarzyna Musial
Development of Robust Dynamically Adaptable Classification Systems using Hybrid Intelligent Techniques
Nov. 2005 - Oct. 2009
Description: The aim of this research project was to investigate various strategies and approaches for dynamical adaptation of classification systems in response to changing environments and user feedback.
Funded by: Algerian Ministy for Higher Education and Scientific Research
STRC role: Project leader
Contact person: Bogdan Gabrys
Staff involved: Zizou Sahel, Bogdan Gabrys
High Performance Fusion Systems
in collaboration with
British Telecom
Oct. 2005 - Oct. 2008
Description: The aim of this project was to: (1) Identify properties of an ensemble (collection) of classifiers which enable combination of those classifiers to result in a well perfoming multiple classifier system, and (2) To explore methods to effectively generate ensembles with these properties. Two combination paradigms are considered in relation to this - a very general model-insensitive decision level combination paradigm, and a more interpretable model level combination paradigm.
Funded by: EPSRC and British Telecommunications plc
STRC role: Project leader
Contact person: Bogdan Gabrys
Staff involved: Mark Eastwood, Bogdan Gabrys
Nature-inspired Smart Information Systems (NiSIS)
Feb. 2005 - Jan. 2008
Description: The EU coordinated Action project had the following overall mission aims: (1) to co-ordinate multi-disciplinary studies and research endeavours into the development and utilisation of intelligent paradigms in advanced information systems design and (2) to extend investigations into emerging new areas inspired by nature, both at biological (i.e. micro) and behavioural (i.e. macro) levels for visionary concepts of information processing and architectures.
Funded by: European Commision within Future & Emerging Technologies (FET) programme as co-ordinatiod Action (CA) project
STRC role: Co-chairing of the Nature-inspired Data Technology (NiDT) focus group
Contact person: Bogdan Gabrys
Staff involved: Bogdan Gabrys, Mark Eastwood, Petr Kadlec, Christiane Lemke
Archive (pre-2008 summary of projects)
- Physically Inspired Artificial Learning Models. Co-leader (Bogdan Gabrys). EU funded Task Force within NiSIS, Oct. 2006 - Oct. 2007.
- Application of computational intelligence techniques for ensuring high quality of data in information systems. Project coordinator/academic supervisor (Bogdan Gabrys). KTP project co-funded by QGate Software Ltd., Jun. 2005 - May 2007.
- Combining Predictors. Project leader (Bogdan Gabrys). Funded by Lufthansa Systems Berlin GmbH and School of DEC, Aug. 2002 - Dec. 2006.
- Placement and Routing For Reconfigurable Systems. Project leader (John Cobb). Funded by Bournemouth University, Sept. 2002 - Sept. 2005.
- The European Network on Intelligent Technologies for Smart Adaptive Systems EUNITE. A corresponding person of a Key Node and a co-chairman of the Research Theory and Development Group on Integration of Methods (Bogdan Gabrys). Funded by European Commission within Future & Emerging Technologies (FET) programme as Network of Excellence (NoE) Project, Jan. 2001 - June 2004.
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