📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

BactiQuick: A validation study of an innovative AI-based early warning system for river contamination utilising continuous monitoring data including a novel rapid bacterial screening device.

Lead Participant: MOLENDOTECH LIMITED

Abstract

UK waterways face significant pollution with one key contributor being untreated sewage discharges often through storm overflows. This can lead to serious health issues for local swimmers, environmental damage to the ecosystem and losses for the economy via closed bathing spots and fisheries.

While new regulation mandates all discharge points to be continuously monitored, current water quality testing methods for faecal pathogens rely on laboratory analysis via bacteria cultures which requires highly trained technicians and takes several days until results are available. Furthermore, not all pathogens can be detected leading to potential health risks.

This project aims to use the Bidwell Brook in the River Dart catchment as a 'living laboratory' to develop and validate BactiQuick: a novel comprehensive and portable pathogen test device for rapid on-site bacterial water analysis giving results within 15 minutes.

Furthermore, the project develops a smartphone app augmenting the test results with GPS data and pictures. Combined with the high-resolution flow and chemical analysis data to be collected in this project this allows the development and validation of a predictive model providing the local community with an early warning system.

This AI-based sysem could be developed into a UK-wide early warning system for river catchment pollution. This will not only allow water utilities to comply with regulation and react quickly but with affordable cost/test it also allows citizen scientist and community interest groups to draw and analyse samples and contribute to the overall dataset.

Lead Participant

Project Cost

Grant Offer

MOLENDOTECH LIMITED £225,651 £ 157,956
 

Participant

UNIVERSITY OF PLYMOUTH £223,838 £ 223,838

Publications

10 25 50