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- Most marine fish hatch from mm-size eggs irrespective of adult size,
and suffer prodigious mortality (rates of 70-90% of the brood) in the
first weeks of their lives;
- This mortality makes the rearing of larval (very young) fish costly, and
an impediment for introducing new species to the growth cycle;
- While it is possible to measure the conditions in the growth tank (temp,
oxygen, etc.), growth protocols are “blind” to the cohort’s response.
Today there is no way of tracking the animals’ development, activity and well-being.

The technology / the solution
- The first automated system capable of providing large-scale, on-site
characterization of the main parameters that indicate larval quality;
- The system uses machine vision to provide reports of larval
development, detecting the occurrence of morphologic aberrations,
while quantifying feeding performance and activity levels of larval fish
in rearing tanks in real-time;
- This system will enable growers to make informed decision on feeding
regimes and quantities, terminate failing cohorts sooner rather than later, and help develop ways for
efficient feeding and quality control.

Stage of Development
- A dedicated hardware prototype was developed;
- Proprietary big data was collected (hours of underwater high-speed videos);
- A novel machine learning analysis tool, relying on anomaly detection, is in development.
Intellectual Property
- Unique know-how in-house for utilizing and analyzing the collected proprietary big data.
- Provisional patent application “A MACHINE VISION SYSTEM FOR LARVAL FISH REARING” was filled