Aston University partners with PrecisionLife Ltd to develop app for secure monitoring of vulnerable patients.

The Company

PrecisionLife Ltd is an innovative AI software business with headquarters in Oxford and subsidiaries in the US, Denmark and Poland that sell high-value data analytics software for the development of a novel Internet of Things (IoT) analytics platform for recording human and animal activity. This requires the use of complex analytics to interpret data to provide real-time responses for secure and personalised monitoring of vulnerable patients.

The Challenge

The company is looking to develop an application of advanced AI that will deliver the most responsive and accurate applications for human and animal health. However, PrecisionLife has limited expertise in cutting-edge machine learning techniques and also lacks an understanding of applying robust machine learning methods to extract data.  

The Solution

Aston University’s expertise in state-of-the-art AI and machine learning will be imperative to the success of developing a novel edge analytics platform for recording data and providing real-time contextualised responses and securing personalised monitoring of vulnerable patients.  

Future benefits of the KTP include the creation of almost 60 new jobs in engineering, product management, sales and marketing and user support. PrecisionLife will also be able to use the technology generated in this KTP in other projects, including further academic research and disease charity projects.

Team Aston

The Lead Academic on the KTP will be Dr Maria Chli, whose core research surrounds modelling and optimising complex systems from the fields of multi-agent systems and machine learning (ML). She has worked on optimising decision-making of intelligent agents through online/reinforcement learning as well as more general probabilistic, ML techniques; successfully applying these in single-agent and multi-agent contexts (for example, dynamic and decentralised orchestration of agents in a supply chain). Her work on trust and reputation in multi-agent interaction settings using Hidden Markov Models is particularly relevant to this KTP.

Dr Chli will be assisted by Professor David Lowe, who has experience in machine learning and statistical pattern processing, having invented the Radial Basis Function network (RBF) and the Neuroscale topographic visualisation model. He has recent experience on the implementation of real-time predictive health analysis of wireless sensor data from sick children in high dependency wards, which is highly relevant to this KTP.

Next steps

The KTP is expected to complete in early 2022 – look out for more updates by following us on Twitter and checking our webpage

For more information about Knowledge Transfer Partnerships or an informal chat, email or call 0121 204 4242.