Research project

TechOceanS

Project overview

Funded through an EU Horizon 2020 Research and Innovation grant, TechOceanS will develop nine innovative technologies and methods for deep sea sensing, sample collection and on-board analysis, and AI-driven image processing and transmission.

Our role in the project is with the development of a gold-standard labelled imaging dataset to be able to train machine learning models. These ML models will then be used in diverse marine platforms to classify benthic and pelagic images. The resulting classifications will be remotely sent to shore-based operators to inform in real-time of the discoveries being made.

For more information visit https://techoceans.eu/.

Staff

Lead researchers

Professor Hywel Morgan MBE

Professor of Bioelectronics

Research interests

  • Microfluidics
  • Bio-sensors
  • Lab-on-a-chip technologies
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Other researchers

Dr Peter Glynne-Jones

Associate Professor
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Professor Blair Thornton

Professor of Marine Autonomy

Research interests

  • Autonomous robotic platforms allow detailed observations to be made over large areas in the ocean. For these systems to be useful, it is necessary to develop advanced sensing capabilities and methods to allow the robots to safely navigate and accurately localize themselves in complex, GPS denied environments. Once observations have been made, it’s necessary to interpret the large volumes of data that are gathered in an efficient and scalable way. For more information on research activities, please visit the Ocean Perception research website.
  • Seafloor 3D visual reconstruction: Development of deep-sea imaging hardware and processing pipelines for calibration, localisation and 3D mapping of the seafloor with full-field uncertainty characterisation.
  • BioCam (NERC NE/P020887/1): Development of a deep-sea, high-altitude seafloor imaging system for monitoring seafloor ecological variables as part of the Oceanids Marine Sensor Capital program. This project is a collaboration with Sonardyne International Ltd, the National Oceanography Centre and the ACFR University of SydneyAT-SEA (NERC NE/T010592/1): 3D visual survey of decommissioned seafloor infrastructure using a shore launched Autonomous Underwater Vehicle (Boaty McBoaface) as part of the INSITE program. This project is a collaboration with the National Oceanography Centre. Automated interpretation of data: Development of AI methods for rapid scalable interpretation of seafloor imagery.
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Dr Daniel Spencer

Lecturer
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Collaborating research institutes, centres and groups

Research outputs