Coastal habitats (e.g. beach sites), lakes and rivers are used for a variety of recreational activities such as swimming, surfing, and fishing. Monitoring the quality of these recreational waters is becoming a global concern to protect human health (e.g. the EU Bathing Water Directive (BWD) in Europe). The most common approach for water quality assessment is the monitoring of Faecal Indicator Organisms (FIOs) present in samples taken from these sites. However, methods for detecting FIOs are challenging as samples need to be collected from several locations and transported to the laboratory within a short period of time, typically within 6 hours. Any delays can lead to a reduction in bacterial numbers, with the potential for under-reporting of results. Therefore, authorities responsible for these bathing waters would ideally require new tools to monitor levels of bacteria in real-time. Such environments are also used commercially for aquaculture of fish and shellfish. These waters can often be contaminated by faecal bacteria following heavy rains and floods, as polluted drainage water from agricultural or urban land run off into rivers and seas. The expansion of aquaculture practices with diversified species and higher stocking density has resulted in more frequent incidence of disease outbreaks often leading to higher fish mortalities with reduced overall production. Chemicals used in aquaculture for disinfection and to treat diseases can cause water pollution and could seriously damage ecosystems in and around aquaculture farms. These chemicals can enter natural waters causing water pollution and can pose a real danger to fish farmers through potential toxicity. Also, residues of certain chemicals may contaminate aquaculture products and present a food safety concern. This project proposes a novel miniature lab on an Autonomous Underwater Vehicle (AUV) for monitoring purposes. The system will collect and analyse samples for pathogens/diseases (e.g. E. coli, Fungi, Amoebic Gill Disease) and will send results to a server. A portfolio of several proven technologies will be considered for the integration on the AUV, including a microfluidic system (a set of microchannels etched into a material e.g. glass), embedded optical fibre sensors, mechatronic systems, image and signal processing, and on-board wireless communication system. The AUV will be used to collect samples from precise locations and measure onsite physiochemical parameters (e.g. temperature, O2 level, pH and electrical conductivity). The project will investigate the effectiveness of chosen sensors incorporated on an AUV and the performance of the communication process to devise new deployment practices and guidance for other agricultural, environmental and industrial applications. The proposed solution will reduce the costs per sample, extend sample numbers, area and density, providing a rapid pathogen detection system.


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.

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This project will reduce the footprint further by:


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.