The aim of this project is to propose an Autonomous Underwater Vehicle
(AUV) for pathogen detection, equipped with an innovative solution for sample
collection and analyses. In addition, the results of the on-board pathogen
detection system would be communicated wirelessly to a ‘Cloud’ based server.
The proposed system would enhance the ability to monitor and detect the
presence of chemical compounds and pathogens allowing authorities to act prompt
and ensure public safety.
The innovative thrust of this project is to use a microfluidic
chip to separate the target organism from other species by using passive
hydrodynamic separation techniques, and apply a new approach to improve the
image quality of a digital microscopic camera by integrating a light source
near to the sample. The proposed system incorporates an optical fibre inside
the channel and use an image analysis tool coupled
with novel artificial intelligence (AI) algorithms, for autonomous, underwater and
real-time chemical compounds detection.
In addition, the AUV
will exploit the use of embedded electrochemical biosensors for molecular
fingerprinting detection. The
prototype system is fully automated using a microcontroller connected to
pumping components such as pumps, valves, and tubing and packaged as a portable
format for the operation in marine environments. The sensing platform can be
adapted to the detection of a wide range of microorganisms at the same time.
The miniaturised lab on
an AUV system could change monitoring strategies for diseases related to
pathogens by providing on-site analysis capability, without the need for
subjective microscopy for identification, subsequently reducing costs and
process time significantly. This will have a direct commercialisation route
towards sustainable exploitation (e.g. fish farming and aquaculture).
Furthermore, this project will directly impact public health emergencies by
providing a rapid early warning system. It would also have a huge international
potential for e.g. third world countries, when sourcing for clean water and
detecting chemical spills.
Social benefits:
• Global
food security: More fish protein will be available for the growing population.
• General
employment levels will be stabilised due to consistently fewer fish health
problems.
• Smart
technologies will increase in higher value jobs.
• Important
cross-sectoral linkages will be made between sectors (e.g. academia and
industry). This will enhance knowledge and technology exchange, and maximise
growth opportunities.
Environmental benefits:
This project will reduce the footprint
further by:
• Decreasing
emissions of CO2 due to sample collection. This will improve local
air quality.
• Reduce
the air pollution related to diseases.
• Reduced
use of medicines, and dispersal into the marine environment.
DeepSeaLab is a start-up Business at Edinburgh Napier
University, Scotland, UK and winner of Business of the Year, 2021 Bright Red Sparks
entrepreneurial competition.
The aim of this business
is to propose an Autonomous Robot to be used for underwater survey missions in
maritime waters such as mapping and collecting data related to water and fish. The
robot will do inspection tasks which are very expensive with the current
conventional methods. The novelty of this idea is to introduce a prototype
system for sample collection and pathogen detection. This solution could change
monitoring strategies for toxic molecules in water and diseases related to
pathogens by providing on-site analysis capability, without the need for
subjective microscopy for identification, subsequently reducing costs and
processing time significantly.