Log in
[text removed for publication], a developer of high-precision medical devices, have produced a new data annotation tool ([text removed for publication]) based on research in CSRI on data storage formats and activity recognition for applications within smart home environments. Within [text removed for publication] stereo-based cameras record activities in a specified environment (e.g. kitchen) which are then annotated using user-based pre-configured activity labels (e.g. prepare meal, wash dishes). [text removed for publication] is currently used by [text removed for publication] users and has yielded additional sales worth [text removed for publication]. [text removed for publication] have employed [text removed for publication] additional technical development staff to extend [text removed for publication] functionality, and through an MoU [text removed for publication] now supports automated annotation based on CSRI's research on activity recognition.
Two leading manufacturers of clothing for outdoor activities ([text removed for publication]) have produced a new range of functional clothing based on research at Ulster on wearable technologies for the active ageing. The new age-appropriate outdoor garments incorporate wearable technologies that enable self-monitoring of physiological parameters (heart rate, respiration rate) and activity levels (step-counts, distance walked) with optimal placement of sensors to improve signal-to-noise ratio. Additionally, [text removed for publication], a company producing [text removed for publication], have used feedback from Ulster's research evaluations to design a new range of [text removed for publication] that are incorporated into the garments, achieving increased levels of usability by elderly people.
An internet-based care model developed by CSRI at Ulster, facilitating all stakeholders (patients, pharmacists, carers, GPs) to dynamically manage the prescription of, and patient compliance with, medication has been incorporated into the [text removed for publication] service platform produced by [text removed for publication], a Telecare product provider. This has extended functionality of [text removed for publication], which is now being used by over 400 patients in [text removed for publication], with improved levels of medication compliance, reduction in caregiver burden, and improved workflow management for healthcare professionals. Incorporation of video-based reminders further led to a material transfer agreement between Ulster and [text removed for publication] to extend [text removed for publication]'s functionality.
Research undertaken at Strathclyde during 2006-2009 produced a decision support platform combining artificial intelligence with low power wireless sensor technology, which was capable of alerting farm staff to animal conditions requiring human intervention. ETS Ltd, a privately owned University Spin-out company was founded in 2009 to develop and market the new technology, and now employs 7 full time staff. Since 2010 more than 250 farms in the UK and Europe have adopted the technology, enabling them to reduce operating costs, maximise milk revenue, with an estimated increase of £10k per 100 cows per annum. The new technology has also improved the performance of other existing businesses and has helped retain jobs in the supply chain in Scotland.
Two Knowledge Transfer Partnership projects, carried out between 2006 and 2009, between an e-commerce marketplace provider (@UK plc) and the University of Reading, led to the development of two software tools that were launched in 2010. The tools, SpendInsight and GreenInsight, are the first of their kind to use artificial intelligence techniques to handle the extremely challenging data associated with purchasing in large organisations. Since their launch, these tools have been used by @UK plc to identify procurement savings and environmental costs of procurement activities for governments, multi-national corporations, academic institutions and healthcare providers. Over the last three years @UK plc has benefitted from the launch of these products as it has provided them with a competitive advantage over the market place, increased the quality and efficiency of their spend analyses and led to multi-million pound licensing agreements. An analysis of spending in some of the NHS Trust Foundations has led to changes in procurement behaviours that have resulted in hundreds of thousands of pounds saved to date — benefitting not only the NHS, but also taxpayers.
Visual analytics is a powerful method for understanding large and complex datasets that makes information accessible to non-statistically trained users. The Non-linearity and Complexity Research Group (NCRG) developed several fundamental algorithms and brought them to users by developing interactive software tools (e.g. Netlab pattern analysis toolbox in 2002 (more than 40,000 downloads), Data Visualisation and Modelling System (DVMS) in 2012).
Industrial products. These software tools are used by industrial partners (Pfizer, Dstl) in their business activities. The algorithms have been integrated into a commercial tool (p:IGI) used in geochemical analysis for oil and gas exploration with a 60% share of the worldwide market.
Improving business performance. As an enabling technology, visual analytics has played an important role in the data analysis that has led to the development of new products, such as the Body Volume Index, and the enhancement of existing products (Wheelright: automated vehicle tyre pressure measurement).
Impact on practitioners. The software is used to educate and train skilled people internationally in more than 6 different institutions and is also used by finance professionals.
Bradford's pioneering research into geophysical prospecting has significantly changed the approach to heritage management in the UK and internationally. Our research has influenced the development of commercial survey instruments in this field as well as changing industry guidance/practice. The changes include increased use of more sustainable, non-invasive methods for archaeological investigation and the gathering of richer data about the buried past. Our guidelines for legacy archaeological data have created standards in the archiving of this valuable information resource for public re-use. The group's involvement with Time Team has enhanced public awareness of geophysical prospecting which is demonstrated in the increased use of these techniques by community groups.
Body Sensor Networks (BSN) research developed novel sensing algorithms and technology suitable for on-body pervasive sensing suitable for healthcare, well-being and sporting applications. The main impact includes:
The need to manage, analyse and interpret the volumes of data and literature generated by modern high-throughput biology has become a major barrier to progress. Research at the University of Manchester on interoperability and advanced interfaces has resulted in innovative software (Utopia Documents) that links biomedical data with scientific literature. The software has been adopted by international publishing houses (Portland Press, Elsevier, Springer, etc.), allowing them to explore new business models, and by pharmaceutical companies (e.g. AstraZeneca, Roche), providing new opportunities to explore more efficient, cost-effective methods for exploiting and sharing in-house data and knowledge. The research also led to a spin-out company, Lost Island Labs, in 2012, which expects a profit [text removed for publication] in its first year.
Targeted Projection Pursuit (TPP) — developed at Northumbria University — is a novel method for interactive exploration of high-dimension data sets without loss of information. The TPP method performs better than current dimension-reduction methods since it finds projections that best approximate a target view enhanced by certain prior knowledge about the data. "Valley Care" provides a Telecare service to over 5,000 customers as part of Northumbria Healthcare NHS Foundation Trust, and delivers a core service for vulnerable and elderly people (receiving an estimated 129,000 calls per annum) that allows them to live independently and remain in their homes longer. The service informs a wider UK ageing community as part of the NHS Foundation Trust.
Applying our research enabled the managers of Valley Care to establish the volume, type and frequency of calls, identify users at high risk, and to inform the manufacturers of the equipment how to update the database software. This enabled Valley Care managers and staff to analyse the information quickly in order to plan efficiently the work of call operators and social care workers. Our study also provided knowledge about usage patterns of the technology and valuably identified clients at high risk of falls. This is the first time that mathematical and statistical analysis of data sets of this type has been done in the UK and Europe.
As a result of applying the TPP method to its Call Centre multivariate data, Valley Care has been able to transform the quality and efficiency of its service, while operating within the same budget.