OceanMind’s Advanced Technology
OceanMind began developing advanced technology to understand human activity on the ocean in 2013 as part of a collaboration between the UK’s Satellite Applications Catapult and the Pew Charitable Trusts.
Using satellites, remote sensing, big data techniques, and artificial intelligence we bring together and analyse all of the data needed to understand vessel behaviour, such as fishing. By comparing this activity to the complex web of applicable rules and regulations, our algorithms highlight suspected non-compliance.
Examples of data sources include:
- Vessel tracking data such as Automatic Identification System (AIS) data, Vessel Monitoring System (VMS), and low-cost tracking devices such as cell phone-based systems
- Satellite remote sensing observations such as synthetic aperture radar (SAR), electro-optical (EO) imagery, near infrared sensors such as VIIRS, and a range of other satellite-based sensors
- Unmanned remote sensing platforms such as UAVs, USVs, and USSVs
- In-situ sensors such as buoys and tethered sensors
- Crowdsourced and open data from vessels, ports, and individuals
- Catch documentation and vessel logbook data
- Vessel registry and identity databases
- Vessel licences and authorised vessel lists from countries and regional management organisations
- Ocean features, charts, and maps including marine spatial boundaries, oceanographic conditions, and fishing forecasts
- Specialist and proprietary enforcement databases maintained by enforcement analysts
All data is collected and aggregated in confidential secure-by-design systems with rigorous access control, security, and privacy processes. OceanMind’s solution is designed around analyst workflow, delivering actionable alerts to expert analysts and facilitating investigation and intelligence production.
OceanMind’s data science research department pushes the boundaries of vessel behaviour analysis, developing new signal processing, feature extraction, pattern matching approaches to improve accuracy and granularity of detected activities. OceanMind’s AI understands many different types of fishing with a wide range of gear, right down to the differences between setting, soaking, or retrieving gear. This level of accuracy allows for high confidence in compliance assessment. Our research focus has been vital to extending fishing algorithms to begin understanding the implications for crew work periods and the adherence to labour laws. It also has permitted tangential developments such as the detection of unauthorised salvage activity.
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