MAKE NEW DISCOVERIES
Ocean Diagnostics is the first company to design technology specifically with microplastics researchers in mind. We use mechanical and computer engineering, machine learning and data science to break barriers to collecting better data. Our technologies enable scientists to make new discoveries about microplastic pollution.
INNOVATIVE. RELIABLE. SMART.
MICROPLASTICS IMAGING TECHNOLOGY
RAPID. COMPREHENSIVE. STANDARDIZED.
Use in the field or the lab to image surface-level microplastic samples (> ~400μm) like those collected from Manta Trawls or Neuston Nets
Receive quantitative size, colour and categorical calculations based on our automated machine learning model
Pattern recognition algorithms calculate 10 discrete size calculations for every particle including maximum width, perimeter, surface area, convexity, circularity, aspect ratio, solidity and more
Predictive colour models calculate repeatable and standardized average colour calculations for each particle
Machine learning models automatically classify particles into common categories such as films, fragments, pellets, and lines
Gather 12 times the data typically collected and fill the knowledge gaps in microplastics fragmentation, longevity and distribution
MICROPLASTICS SAMPLING TECHNOLOGY
PORTABLE. RELIABLE. EASY-TO-DEPLOY
Easily deployed from any vessel without the need for heavy winch infrastructure (e.g. small RIB, sailboat, powerboat, or research vessel)
Use in fresh water, salt water, lakes or oceans
Collect filtered samples through the water column to increase data collection capabilities and gain further insight into microplastic pollution below the surface
Designed for real time and autonomous deployments
Rated to 400m depths
MICROPLASTICS SENSOR TECHNOLOGY
IN SITU. AUTOMATED. REAL TIME.
Quantify and characterize small microplastic particles directly in situ
Analyze water samples for microplastic particles in real-time
Reduce inconsistent and labour-intensive methods to maximize research time
Benefit from strict contamination reduction protocols by sampling in situ