Tag: Knowledge Transfer Partnerships

Knowledge Transfer Partnership Associate Spotlight: Abdulrazaq Sanni

Author Anna Jones | Posted on

Abdulrazaq is a Software Engineer as part of our Knowledge Transfer Partnership (KTP) with WASE and UWE Bristol. A KTP is a UK-wide, 3-way partnership between a business, a university and talented graduate, and aims to help businesses improve competitiveness and productivity, whilst also boosting the career prospects of the graduate.   

WASE and the College of Arts, Technology and Environment (CATE) at UWE Bristol began their KTP together in April 2025. The KTP will create a machine learning-based soft sensing platform. This platform will be integrated within WASE’s Electro-Methanogenesis Reactor (EMR) to remotely optimise system performance. The system will help expand EMR technology, allowing customers to treat wastewater on-site while generating energy, reducing carbon emissions, and producing cleaner water and nutrients for use as fertilizers.

The project aim is to develop game-changing improvements to the EMR technology by enhancing the system’s monitoring and adaptability. This will ensure minimal downtime and maximum value from the waste. The improvements will involve optimizing WASE’s industrial-scale system and improving predictive analytics in anaerobic digestion (AD). We will use feedback from microbial electrolysis cell (MEC) modules to enhance sensor accuracy.

The KTP team caught up with Abdulrazaq to hear about their experience of the KTP so far:

What attracted you to the position?

I’m drawn to the role for several reasons. Primarily, it’s the excitement around the project’s potential — what we can achieve and the path to getting there. I enjoy challenges and solving problems, and this feels like the perfect project for someone like me. I’m especially excited about helping position WASE at the forefront of innovation in the anaerobic digestion (AD) sector through the application of AI and operational automation.

Another reason is the role’s position at the intersection of academia and industry. Having previously worked in academia, I’ve been considering a transition into the industry. This opportunity allows me to bridge both worlds. Finally, the sustainability aspect is very important to me. I’ve worked on a project that was somewhat related to sustainability, and being part of an initiative that contributes to a healthier climate is truly rewarding.

What are you most looking forward to?

I’m most looking forward to realising the project’s objectives. I say “realising” because I genuinely believe they’re achievable, even though the journey might be challenging. Reaching those goals will be a testament to the work, support, and growth that come along the way. It will also reflect the level WASE will have reached — and I’m excited to be a key contributor to that progress.

How is the partnership between UWE Bristol and the company working?

It’s only my third week so far, but the partnership has been fantastic. Everyone at both the company and the university has been incredibly supportive and engaged, which is great because it shows that everyone is equally invested in the project. One thing that stands out to me is how they’ve managed to involve the right people — experts who understand exactly what we need to do. That alignment is crucial to the project’s success, and I think they’ve nailed it.

What are the major benefits/support available from UWE Bristol?

The major sources of support from UWE have been the academic team and the KTP team. The KTP team has been actively involved from the start, guiding me through key steps and helping me understand the important elements of the partnership. The academic team has also been very supportive and clearly committed to mentoring and guiding me throughout the project.

What do you enjoy most about your job?

Although it’s only my third week, it already feels like an environment where I’ll get to learn a lot — especially about anaerobic digestion, a field I hadn’t worked in before. The learning curve is steep, but that only makes it more exciting. The people here have also been amazing. They could probably list “Family” as one of their core values, because that’s exactly how they operate — with a strong sense of unity and belonging. That culture really helps drive a shared sense of purpose.

Find out more about KTPs at UWE Bristol. 

Knowledge Transfer Partnership Case Study – Taro Agric Farm

Author Anna Jones | Posted on

The Knowledge Transfer Partnership (KTP) between University of the West of England (UWE), Obafemi Awolowo University (OAU), the Taro Agric Farm (TAF) was established to harness data-enabled innovations (DEI) for the commercial poultry industry in Nigeria. The project aimed to enhance chicken production efficiency and optimise overall business operations through the strategic application of data-driven technologies and academic expertise. Kamran Munir (Professor of Data Science) led the collaborative relationship with the Nigerian partners and the project from UWE. Saidu Oseni (Professor of Animal Sciences) led the project from OAU.

The Company

Taro Agric Farm (TAF), is a broiler chicken production company based in Southwest Nigeria. With over a decade of experience, TAF specialises in commercial broiler farming, operating concurrent batches of 2,000 birds per cycle. The company has multiple production centres, including its main base in Ile-Ife, Osun State, and outgrower units in Ilesa (Osun State) and Ibadan (Oyo State). Beyond production, TAF is actively engaged in consulting services, capacity building, and training for poultry farmers, offering expertise across the entire broiler chicken value chain—including input supply, production, processing, distribution, and marketing. A defining characteristic of TAF is its forward-thinking approach to poultry farming. Through the African Agriculture Knowledge Transfer Partnership (AAKTP), TAF successfully integrated smart technologies such as IoT-enabled sensors, a data storage for real-time data management, and predictive analytics to enhance decision-making in poultry production. This has positioned TAF as one of the leaders in leveraging data-driven solutions for sustainable poultry farming in Nigeria.

7 people from UWE Bristol and Taro Agric Farm stood together smiling at the camera

The Challenge

The Knowledge Transfer Partnership (KTP) between Taro Agric Farm (TAF), Obafemi Awolowo University (OAU), and the University of the West of England (UWE) was initiated to apply data-enabled innovations (DEI) to commercial chicken production in Nigeria and to improve and optimise business operations. A key focus was developing a strategy for embedding DEI to create sustainable broiler chicken operations over the long term. The poultry industry in Nigeria faces multiple constraints, including high mortality rates, inefficient farm management practices, limited use of data in decision-making, and poor environmental conditions affecting broiler chicken welfare and productivity. In the past, TAF like many others in the industry, relied on conventional methods of managing poultry production, which lacked the real-time monitoring and predictive capabilities needed to optimise productivity and farm environment. Farmers and farm managers had to rely on manual data collection and experience-based intuition, making it difficult to identify early warning signs of health risks or performance inefficiencies. Without data-driven insights, farm operations were reactive rather than proactive, often leading to delayed interventions and losses. In addition, one of the biggest challenges TAF faced in the past was high mortality and morbidity rates in broiler production. Various environmental factors, such as poor ventilation, excessive heat, high humidity, and exposure to noxious gases, particularly ammonia, significantly affected bird health. Without a robust system to monitor and control these environmental conditions, broiler chickens were at risk of disease outbreaks, respiratory problems, and stress, which ultimately led to economic losses.

Tackling these constraints required innovation in both poultry management and business practices to enhance the viability and profitability of operations. The KTP project activities included setting up an IoT platform, configuring sensor nodes, and establishing a database to record and store data on various parameters such as chicken welfare, input supplies, production, processing, distribution, and marketing. The project also involved the development of dashboards for monitoring key performance indicators (KPIs), the use of predictive analytics, and conducting performance comparisons across production batches. Additional activities included stakeholder engagement through workshops to build and embed capacity. The key accomplishments of KTP project include the successful setup, testing, and deployment of a IoT platform in a broiler chicken unit in southwest Nigeria, where key variables related to chicken welfare and performance were captured and monitored. Company data was archived in a database, and a dashboard was developed to track temperature, relative humidity, air quality and noxious gas parameters. An end of project Stakeholders’ Engagement Workshop aiming towards widening participation and sustainability with approximately ~100 participants, including poultry farmers and industry professionals, was also successfully conducted.

“This project equipped TAF staff with advanced digital farming skills, enhanced OAU’s research capacity and curriculum, and strengthened international collaboration—demonstrating how innovation and partnership can drive sustainable agricultural development.”

Prof. Kamran Munir (Professor of Data Science, University of the West of England, UWE Bristol)

Benefits and Changes

The Knowledge Transfer Partnership (KTP) between Taro Agric Farm (TAF), Obafemi Awolowo University (OAU), and the University of the West of England (UWE) has led to significant improvements in broiler chicken production, farm efficiency, and data-driven decision-making at TAF. As a result of the KTP, Taro Agric Farm and its staff have acquired several new knowledge areas and capabilities. These include (but not limited to):

  1. The staff gained expertise in deploying sensor nodes to monitor key health and welfare indicators of broiler chickens. This application of digital technology is directly contributing to improved productivity and profit margins by enabling real-time data collection and analysis of poultry welfare to guide operations at the unit.
  2. TAF implemented a smart farm infrastructure, incorporating WiFi, inverters, and clusters of sensor nodes, along with smart cameras to monitor the comfort, welfare, and performance of chickens. This integration allows for continuous, remote monitoring, improving operational control and decision-making.
  3. The business acquired the capability to track, manage, and analyse its data assets—spanning performance, ambient conditions, costs, and returns—via a MySQL database. This centralised data storage allows for enhanced data organisation, retrieval, and long-term analysis.
  4. A key capability gained was the deployment of a real-time dashboard that tracks health and welfare indicators of broiler chickens. This dashboard offers a user-friendly interface for staff to monitor key variables and make informed decisions regarding poultry welfare and management.
  5. The staff were trained to track and monitor key performance indicators (KPIs) across production batches and historical data. This has allowed TAF to benchmark performance, identify trends, and adjust improve the consistency and quality of production, while also enabling more accurate forecasting and strategic planning
  6. TAF’s adoption of data-enabled innovations (DEI) and IoT technologies positioned it as a leader in digital poultry farming in Nigeria. Sales turnover is expected to increase by 30%-40% within three years, due to improved efficiency and scalability. Profit before tax is projected to grow by 20%, within the next three years. Increased demand for TAF’s consulting services, as other poultry farms seek to implement similar digital solutions.

Obafemi Awolowo University (OAU) updated its Animal Sciences curriculum to incorporate digital technologies. The project also strengthened ties between OAU and UWE, fostering international collaboration in poultry technology research. The project research outcomes are being published as open access where possible which cover the use of digital technologies and data-enabled innovations for the enhancement of the welfare and performance of broiler chickens – as a case study in Nigeria.

“The KTP was an excellent opportunity to blend academic research with industry application. At OAU, we have always been committed to advancing precision livestock farming, and this project allowed us to practically demonstrate the power of digital transformation in poultry production.”

Prof. Saidu Oseni (Professor of Animal Sciences, Obafemi Awolowo University, OAU, Nigeria)

Key Facts

  • To best of our knowledge, TAF is the first poultry farm in Nigeria to integrate IoT and digital technologies into broiler production to this scale.
  • IoT-enabled sensors deployed to monitor temperature, humidity, air quality, and toxic gases in real-time.
  • A database established for real-time data collection and performance tracking
  • Decision Support Dashboard developed, allowing farmers to make data-driven decisions
  • Sales turnover expected to grow by 30 – 40%within three years
  • Profit before tax projected to increase by 20%
  • 100+ poultry farmers and industry professionals trained on smart poultry farming
  • 19 undergraduate & 2 MSc projects initiated on digital poultry farming at OAU
  • Presented findings at the Nigerian Poultry Show (NPS) 2024, reinforcing industry leadership
  • OAU integrated digital technologies into its Animal Sciences curriculum, influencing future research.

Find out more about the Knowledge Transfer Partnership in the Case Study below.

Knowledge Transfer Partnership – Case Study – TaroDownload

This partnership received financial support from the Knowledge Transfer Partnerships programme (KTP).  KTP aims to help businesses to improve their competitiveness and productivity through the better use of knowledge, technology and skills that reside within the UK knowledge base.  This successful Knowledge Transfer Partnership project, funded by UK Research and Innovation through Innovate UK, is part of the government’s Industrial Strategy.

Knowledge Transfer Partnership Associate Spotlight: Taabish Khan 

Author Anna Jones | Posted on

Taabish is a Commercialisation Manager for Duku as part of our Knowledge Transfer Partnership (KTP) with Duku and UWE Bristol. A KTP is a UK-wide, 3-way partnership between a business, a university and talented graduate, and aims to help businesses improve competitiveness and productivity, whilst also boosting the career prospects of the graduate.  

Duku is an innovative and entrepreneurial engineering design consultancy that take client ideas and develop them into full marketable designs. They have recently added an in-house EV charging technology division, developing new and unique electric vehicle (EV) charging infrastructure, which has considerable potential as the only fully-accessible charging tech available, which conforms to the new BSI standard for accessible EV charging products.

The project aim is to embed a full commercialisation capability within the business and to exploit innovative in-house designed products. This will enable Duku to directly market their own products and offer a full-service idea-to-market capability for new and existing design consultancy clients. 

The KTP team caught up with Taabish to hear about their experiences of the KTP so far:  

What attracted you to the position? 

There are a few reasons why I was drawn to this role. First, it offered the opportunity to develop the commercialisation strategy for a product within the UK’s sophisticated automotive sector, which has been a medium-term career goal of mine. The second is the unique nature of the role. Being a management KTP, the role has allowed me to upskill as an industry consultant while collaborating with an academic institution like UWE Bristol. This partnership provided an added layer of research-driven insight and strategy formulation. Thirdly – working with Duku, a company innovating in the EV charging space and enabling users from all walks of life to access electric vehicles, also gives me a sense of purpose – knowing that my commercialisation efforts have a direct, positive impact on both the community and the planet. 

What are you most looking forward to? 

Six months into the KTP, we are transitioning from the planning into the action phase, which is something I’m particularly excited about. I’m looking forward to collaborating with industry leaders, academic researchers, and automotive OEMs to further advance our accessible charging solution. The goal is to make Duku’s products the gold standard for EV charging infrastructure while cementing our position as a thought leader in the space. The chance to see this project evolve from strategy formulation to commercial success is something I look most forward to. 

How is the partnership between UWE Bristol and the company working? 

The partnership between UWE and Duku has been highly synergistic. The academic team at UWE brings a strong research foundation, combining both academic and industry perspectives, which has accelerated the strategy development process. This collaboration has also created a feedback loop that allows for continuous validation of my deliverables, making the entire process more dynamic, accurate, and responsive. This partnership has also opened new doors for Duku, offering potential collaborations and expanding our contacts in areas such as accessibility and sustainability in EV infrastructure. 

What are the major benefits/support available from UWE Bristol ? 

The major benefits for me personally have been access to UWE’s resources, research capabilities, and academic expertise. Positioned in the middle, I bridge the gap between academia and industry, benefiting from both perspectives. This has allowed me to develop a holistic commercialisation strategy that considers both academic rigor and practical, real-world insights. Beyond the scope of the project, this experience has been transformative. Having recently completed my MBA, I am transitioning from execution roles to more strategic, planning-focused positions. The variety of perspectives I’ve been exposed to through this partnership is helping me upskill rapidly, and I’m confident I’ll emerge a more capable professional by the end of this KTP project. 

What do you enjoy most about your job? 

What I enjoy most about my role is the tangible impact my work has on Duku’s overall strategy. Taking complex data, reports, and insights and distilling them into actionable strategies is something I find highly fulfilling. Being in a management KTP role, I frequently get the opportunity to engage in activities like design thinking, competitive analysis, branding, marketing, and even sales leadership. These are skills that will serve me well throughout my career, and the diversity of the work keeps me constantly challenged and engaged. 

Find out more about KTPs at UWE Bristol.  

UWE Bristol announce new Knowledge Transfer Partnership with WASE Limited

Author Anna Jones | Posted on

UWE Bristol is excited to announce a new three-year Knowledge Transfer Partnership (KTP) with WASE Limited, funded by Innovate UK. A KTP is a unique collaboration between a business, a university, and an associate. It aims to create a positive commercial impact, enable transformational improvements, and drive innovation.

WASE provides their customers with decentralised, next-generation technology that converts wastewater and organic waste into energy (methane-rich biogas). Their services help clients reduce energy costs, shielding themselves from market volatility and lowering waste treatment costs. This is all achieved, whilst decreasing carbon impact through an enhanced local circular economy.

They currently support SMEs in food and beverage manufacturing and agriculture. Their direct sales team offers a Waste and Sustainable Energy as a Service (WASEaaS) model that requires no CAPEX for instant low-cost renewable energy. They also provide an ownership model with remote operation and maintenance support.

The KTP will create a machine learning-based soft sensing platform. This platform will be integrated within WASE’s Electro-Methanogenesis Reactor (EMR) to remotely optimise system performance. The system will help expand EMR technology, allowing customers to treat wastewater on-site while generating energy, reducing carbon emissions, and producing cleaner water and nutrients for use as fertilizers.

The project aims to develop game-changing improvements to the EMR technology by enhancing the system’s monitoring and adaptability. This will ensure minimal downtime and maximum value from the waste. The improvements will involve optimizing WASE’s industrial-scale system and improving predictive analytics in anaerobic digestion (AD). We will use feedback from microbial electrolysis cell (MEC) modules to enhance sensor accuracy.

If you would like to find out more about WASE’s next generation anaerobic digestion system and the novel machine learning biosensing, reach out to the team at WASE: Get in touch – WASE.

Will Gambier, Head of Science from WASE commented:

“We’re delighted to partner with UWE Bristol on this exciting Knowledge Transfer Partnership. This collaboration is an important opportunity to take our waste-to-energy solutions to the next level, combining our industry expertise with the University’s innovative research capabilities. 

We see great potential in using data-driven insights to help our customers treat wastewater more effectively, generate clean energy, and support sustainability goals.”

KTPs integrate academic research into companies, to promote innovation and growth. The unique three-way collaboration between a business, a university and a graduate help businesses  improve competitiveness and productivity.

Find out more about KTPs.

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Knowledge Transfer Partnership Associate Spotlight: Louis Aberdeen

Author Anna Jones | Posted on

In the below spotlight, we meet Louis Aberdeen, Knowledge Transfer Partnership (KTP) Associate for Metrea.

Metrea Mission Data Limited and the Centre for Machine Vision (CMV) at UWE Bristol began their KTP together in October 2023. The KTP is developing unique software solutions that process telescopic images of objects in Low Earth Orbit to detect, track, image and categorise Resident Space Objects. The KTP will embed machine learning principles to allow autonomous detection and categorisation of space objects to provide essential data to clients. Metrea sought a partnership with CMV in order to utilise their extensive experience and expertise in employing state-of-the-art machine learning for complex image processing and feature recognition.

 What attracted you to the position?

At the time I was searching for Data Analysis roles and was immediately drawn in by the title “Space Data Analyst” because what’s cooler than space. Initially I assumed I would be underqualified as I had only done a degree in mathematics. However, as I read the job description, I could see how I matched more and more of the requirements and this really excited me. Because of the nature of work the details of the job description were vague which just made me more interested. Space debris is a very serious problem and there aren’t enough cost-effective approaches to dealing with this, this project will take a step forward in this regard.

“I’m looking forward to when the work I have done makes a real impact on the Space Domain Awareness (SDA) system and contributes to the field of SDA”

How is the partnership between UWE Bristol and the company working?

The partnership between UWE Bristol and Metrea is really productive for both parties. The guidance and technical background of UWE Bristol and specifically the Centre for Machine Vision has been critical to the progress of the project and I’d especially give credit to Lyndon and Mark for their mentorship as I follow down this pathway.  Metrea have the unique capability to capture imagery of objects in Low Earth Orbit (LEO) and the opportunity to work on this project is only possible because of the hard work Metrea has done to develop this system. In particular I would like to highlight Chris and Ryan for their stewardship of the project and for giving me invaluable direction as I develop professionally.

“The benefits are that UWE Bristol are able to produce novel research in an area of study new to the CMV and that Metrea have access to the resources and expertise at the CMV to develop their SDA system.”

What do you enjoy most about your job?

I really love the variety of the work. The project encompasses so many different areas, machine learning, optical systems, signal processing, workflow optimisation, customer engagement, project management. The research is really enjoyable, the processes of working through a problem and experimenting with different approaches is very rewarding. I have a lot of work ahead of me but I’m excited to tackle it head on.

What do you think about the support available from UWE and the Company – give examples if you can

Thanks to Metrea and UWE Bristol’s support I have been able to take a course in video and image processing which has been instrumental in the progress of the project, inspiring a promising direction of study. I have attended serval conferences including the Farnborough air show and SPAICE hosted by ESA on using AI in space. These gave me a really great insight into the wider Space Domain Awareness business as well as modern reinforcement learning, and AI techniques being applied in the space domain. I learned how these trends will only continue to grow which is why it is so important to become knowledgeable.

I have also had many discussions with the academics at UWE Bristol in the CMV guiding me towards writing my first paper. The process of writing a good literature or abstract were very new to me and their expertise was really helpful.

Additionally, I am working with UWE Bristol and Metrea to use the KTP budget on a machine learning/development computer. As a part of this I consulted with many stake holders at UWE and within Metrea to determine the correct allocation of the money. UWE have a lot of experience with purchasing workstations for researchers, so their input was invaluable. Metrea’s IT department were very knowledgeable and knew how they wanted the workstation to be integrated within the wider IT system.

UWE Bristol logo

KTPs integrate academic research into companies, to promote innovation and growth. The unique three-way collaboration between a business, a university and a graduate help businesses  improve competitiveness and productivity.

Find out more about KTPs.

UWE Bristol announce new Knowledge Transfer Partnership with BPM Contracting Services

Author Lynn Goh | Posted on

UWE Bristol and BPM Contracting Services are thrilled to announce their 24-month Knowledge Transfer Partnership (KTP), funded by Innovate UK. KTPs consist of a unique three-way collaboration between a business, a university and a graduate with the aim of creating positive impact, enabling transformational improvements, and driving innovation.

BPM Contracting Services has been operating for seventeen years and is one of the South West’s fastest growing building maintenance firms. Working with housing associations, local governments, healthcare providers and domestic clientele, they aim to deliver the highest quality of service to customers. BPM also has a commitment to supporting the local construction industry and community, providing training and apprenticeships, and a long-standing commitment to sustainable practices. They have held ISO14001 certification for 10 years with the aim of minimising harmful impacts on the environment through sustainable practices.

The project aim is to develop and implement a novel organisation-wide quality management system, through distributed leadership development, customer relationship metrics, digital integration of systems, performance benchmarking, and employee training for retention and continuous improvement.

UWE Bristol academics, Dr Kyle Alves, Dr Anabela Soares and Gareth Edwards will be working on the project. Dr Kyle Alves will be the lead, and is a Senior Lecturer of Information Systems and Operations Management. Dr Anabela Soares is a Senior Lecturer in Strategy and Operations Management and Gareth Edwards is a Professor of Leadership and Community Studies and Director of Research and Enterprise.

With support from the academic team, the project will innovate BPM’s approach through developing new digital capabilities, improving customer relationships supported by new technologies and increasing the competitiveness of BPM against larger competition in public tenders.

The Associate will work with the Senior Management Team, maintaining full visibility of areas being developed within the project.

Find out more about Knowledge Transfer Partnerships at UWE Bristol.

UWE Bristol logo

Knowledge Transfer Partnership Associate Spotlight: Jan Klimaszewski

Author Anna Jones | Posted on

Jan is a Machine Learning Engineer Knowledge Transfer Partnership (KTP) Associate with Lyons Davidson Solicitors and UWE Bristol. A KTP is a UK-wide, 3-way partnership between a business, a university and talented graduate, and aims to help businesses improve competitiveness and productivity, whilst also boosting the career prospects of the Associate.

Based in Bristol, Lyons Davidson is a national law firm providing legal services to businesses and individuals. Innovation has been fundamental to their success, and they have developed their own technology including an online client portal and client document application.  Lyons Davidson are a responsible business with certification for the quality of their approach to the impact on the environment, the security of their systems and the investment they make in their people. They strive to deliver a service and outcome that meets their clients’ needs.

This 24-month KTP aims to create a new AI/Machine Learning system, which will predict likely claim settlement value, to help advise customers on compensation offers. Almost a year into the project, UWE KTP team asked Jan about his experience so far.

Jan tells us that he is passionate about AI and Machine Learning, and he utilised these ideas during his studies. He chose to join KTP because he wanted to be part of an innovative project developing automation tools for a highly regarded law firm. He enjoys problem-solving and the intriguing challenges he faces in the job.

Jan commented on the positive aspects within his role. “Firstly, it offers extensive learning opportunities in AI, Data Science, and Data Analytics. The combined influence of academic knowledge and team support, guides me towards effective approaches and methods, while the project itself helps to consolidate, test, and verify my understanding. Secondly, interacting with people who have similar experiences to mine, reminding me that we all make mistakes, which significantly reduces stress.”

When asked about the experience of working as a KTP Associate, Jan stated that “the unique aspect of being an associate lies in simultaneously working for both a company and a university. It’s a special position that allows one to witness and learn from both academic and industry approaches, to problem-solving and find a balanced solution that fits both perspectives.”

Jan also explained his personal challenge as an Associate. “As the leader, I had to trust my ideas and take initiative, rather than waiting for advice from the academic and industry sides. In essence, gaining confidence was the key to overcoming this barrier.”

Lastly, we asked Jan whether he would recommend the KTP Associate role, and he replied that he would strongly recommend it, “KTP demonstrates that everyone starts from a similar place, and the skills you’ve acquired during your studies provide a solid foundation for further professional development.” KTP offers a unique opportunity to gain invaluable industry experience, enhancing skills and employability, and comes with a dedicated training budget, allowing graduates to access additional learning resources and professional development opportunities.

UWE Bristol announce Knowledge Transfer Partnership with a pioneering nurse call systems business

Author Anna Jones | Posted on

UWE Bristol has been successful in securing grant funding from Innovate UK to form a new 36-month Knowledge Transfer Partnership (KTP) with a pioneering nurse call systems business.

They are trusted by leading healthcare trusts, hospitals, and care home operators to deliver dependable 24/7 nurse care systems that make life better for patient and residents, and for those charged with protecting them.

The project aim is to accelerate the businesses in house capability to revolutionise and innovate the quality of care provided for residents in social and health care settings using cutting-edge AI, machine vision and machine learning techniques.

The project is in collaboration with UWE Bristol academics Wenhao Zhang, Mel Smith and Lyndon Smith.  Wenhao Zhang is Associate Professor of Computer Vision and Machine Learning, Mel Smith is Professor of Machine Vision and Lyndon Smith is a Professor in Computer Simulation and Machine Vision.

Lyons Davidson Solicitors and UWE Bristol Knowledge Transfer Partnership project update

Author Anna Jones | Posted on

Lyons Davidson Solicitors and UWE Bristol are nearing completion of their 2nd Knowledge Transfer Partnership (KTP), focussing on emerging technology to develop an AI/Machine Learning system which will streamline their business.

The provision of legal services is in a period of rapid transition and the project is responding to a business challenge created by new legislation that will be critical in future proofing Lyons Davidson.

The company embraces innovation and technology, to deliver efficient and effective legal solutions with a client-centric approach, and their goal is to work toward an automated claims process putting client experience at its core.

The projects’ emphasis on fusing Machine Learning and other learning paradigms to create useful predictive models is complementary to the previous, successfully completed KTP, which embedded expertise in a different form of AI.

The project aims to create a new AI/Machine Learning system, which will predict likely settlement values and help to advise customers on compensation offers. The ability to automate settlement of claims will improve and shorten the decision-making process, giving Lyons Davidson a competitive edge.

UWE Bristol Academics working in this partnership are Jim Smith, Professor of Interactive Artificial Intelligence and Deputy Director of the Computer Science Research Centre, and Dr Mehmet Aydin, Senior Lecturer in Computer Science.

Professor Jim Smith tells us that “the project is addressing how to build and deploy explainable AI systems that can learn predictive models from historical records, such as likely settlement values for a range of insurance claims. A key part of the project is to make these systems interactive, so that company staff can query and recommend changes, so that the models can rapidly adapt in response to human expertise.”

The KTP office team at UWE caught up with Jan Klimaszewski, who is working on the project as associate and Software Engineer in Artificial Intelligence.

What type of AI / Machine Learning is being used within this Knowledge Transfer Partnership project?

We use a Pieciewiese linear regression tree (PL Tree). It is made up of two models a decision tree which provides a set of rules and linear regression) but is also a model in itself. It is a set of rules where the output is a mathematical equation. In general, every decision tree regressor is a set of rules with an output as a mean of some values, but for a PL tree the value is a mathematical equation.

We use active learning that includes human involvement, Case Handlers provide data over time and will be able to flag incorrect predictions as they arise. The model will then adapt a pattern, noticing that something has changed and will try to correct itself to make the right prediction.

How does this model work?

The architecture of the model includes input of parameters including injury types, accident types, general damages (tariff injuries, tariff and non-tariff costs) and special damages. It considers prognosis, length of injury and tariff type.

When a Case Handler uses the model, they input the case details using drop down menus and text boxes. They then click predict and the model will return a mathematical equation. It works out each section of the claim, so there could be a final calculation made up of several equations depending on the rule set.

How has AI / Machine Learning been developed within this project?

We analysed data using various statistical methods. After this we tested against various Machine Learning models; Random Forest and a simple decision tree. We used Machine Learning techniques such as cross validation to evaluate the model and to find the best possible parameters and performance. We used a technique called Gridsearch which allowed us to find the best possible set up and to see if the model had improved or not. These steps were repeated until we had a model that was not over or under fitting.

It is essential to have low error rates in the decision tree, so we used 4 different types of metrics to assess the model (mean absolute error, mean squared error, root mean squared error and r squared error).

We decided to use the PL tree because simple trees and Random forest were too simplistic and performing with low accuracy.

The team got to the point where we had everything, but the model was stopping us progressing further. Research was carried out on other Machine Learning models, one of which used genetic trees, but this was too complex for the solution. We decided to use a PL Tree which provides us with everything required.

The entire journey was about training, testing, comparing models and trying different approaches with data. The team are currently focussing on data preprocessing. Data preprocessing refers to the technique of preparing raw data to make it suitable for building and training Machine Learning models. – Right now we are in the testing phase

What will this mean for Lyons Davidson going forward?

This will make the the negotiation process more efficient. The system will provide guidance to the case handler and allow offers and counteroffers to be made quicker and more consistently.  It will also provide a framework to provide more automation within the offer process and help reduce touchpoints on the claim for case handlers.

Is there anything else that you would like to tell us about the project?

The relationship between the business and the academic team has strengthened the project and made it possible to execute.

UWE Bristol logo

In summary, the first stage of this knowledge transfer partnership has established a software development framework, creating data tools to present the initial idea of the project. It was then ensured that data is pre-processed without concerns and Case Handlers can generate their own unique rules as needed. A generic re-useable ‘data-dictionary’ framework was created for storing meta-data that allows users to explore and edit.Ongoing knowledge exchange with case handlers will ensure that the data is utilised correctly, and that the input process is designed in the most efficient manner.

A functional model has been created, capable of predicting settlement value ranges. The overall aim is to accurately predict insurer behaviour and achieve the best result for clients in the quickest time.

Knowledge Transfer Partnership Associate Spotlight: Rasheed Lawal

Author Anna Jones | Posted on

In this Knowledge Transfer Partnership (KTP) spotlight, Rasheed Lawal shares his experiences as our KTP associate for our African Agricultural KTP (AAKTP) with Obafemi Awolowo University and Taro Agric Farm.

An AAKTP is a four-way collaboration between a university in the UK, a university in Nigeria, a business and a recent graduate, known as the associate. The AA KTP aims to solve a particular challenge or problem which will help an agricultural business innovate and grow.

Our African Agricultural KTP with Obafemi Awolowo University (OAU) and Taro Agric Farm looks at the application of data-enabled innovations to commercial chicken production in Nigeria:

My family are in the poultry business, and I did my undergraduate thesis on analysing livestock data to view trends and generate insights. The opportunity to develop my career further, and learn more about Data Science & Analytics and implement that into the livestock industry attracted me to the role.

The role excites me as I’m keen to know about leveraging IoT devices and data analytics to monitor and optimize various aspects of chicken farming including environmental conditions, feed and water consumption, health conditions, enhancing growth rates, feed efficiency, promoting animal welfare and overall profitability for poultry farmers in Nigeria. Whilst also undertaking knowledge-sharing activities, such as seminars and training sessions, to disseminate best practices and build capacity among stakeholders in the production value chain.

The partnership between UWE, OAU and Taro Agric involves a collaborative effort to conduct research aimed at enhancing broiler productivity and chicken welfare in Nigeria through data-enabled innovations and IoT applications. UWE provides expertise in data analytics and the possibility of IoT technologies, while OAU and Taro Agric contribute industry knowledge, resources, agricultural research, and on-the-ground implementation support. The Innovate UK funding has allowed for the acquisition of necessary infrastructures, data collection tools and personnel to support research activities, as well as capacity building and skill development which will contribute to the sustainability and long-term impact of the project. So, I can say that the partnership is working well so far!

So far there are numerous benefits of the project:

The valuable hands-on experience in implementing data-enabled innovations and IoT applications in broiler production, which enhances

  • Skill sets and prepares one for future roles in agricultural technology and related fields.
  • The exposure to an interdisciplinary learning approach that combines expertise in data analytics, IoT technologies and livestock.
  • The project provides opportunities for professional development and capacity building, including training in data analytics tools, IoT device integration, project management and communication skills which are transferable and valuable for career advancements in various sectors.
  • Networking opportunities, contribution to impactful research, and exposure to global challenges and opportunities facing the livestock sector.

I am really enjoying working on the project so far. Some highlights and achievements include:

  • Being part of a project that explores innovative solutions in the broiler industry through technology.
  • Working alongside a diverse team of collaborators where ideas are shared and expertise is leveraged to achieve common goals.
  • Opportunities for learning and personal growth including capacity building/development.
  • Problem-solving and contributing positively to the welfare, sustainability and productivity of broiler production in the industry.
  • Networking opportunities and access to industry contacts, conferences and events.

I appreciate the extensive expertise and resources that UWE brings to the project, particularly in the areas of data analytics and IoT technologies, as well as the industry insight and practical support by OAU and Taro Agric; the open communication, mutual respect and willingness to work together towards a common goal, the financial and logistical support from everyone including funding for equipment, travel expenses and fieldwork activities which demonstrates a strong commitment to the success of the project.

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