Dell Technologies Deep Learning Empowers Volunteers Worldwide to Protect the Great Barrier Reef

August 22, 2022
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Dell Technologies announced today a new deep learning technology model, launched in partnership with Australia-based conservation organisation Citizens of The Great Barrier Reef, which will allow global citizen scientists to more quickly and accurately analyse reconnaissance images collected from the Great Barrier Reef during the next phase of the Great Reef Census (GRC).

 

The new Dell deep learning model will better inform conservation efforts for the Great Barrier Reef, one of the world’s greatest natural wonders. A previously implemented Dell edge solution deployed on watercraft automatically uploads data directly to the deep learning model via a mobile network for real-time image capture. This will enhance the capabilities of the GRC by speeding image analysis that previously solely relied on human volunteers – allowing citizen scientists to support prompt recovery efforts in areas that need it the most and during critical times of the year, such as the annual spawning season.

 

The deep learning analysis now takes less than one minute per photo, compared to seven or eight minutes in previous census phases. While it took 1,516 hours to review 13,000 images in the first GRC, the new model can analyse the same data set in less than 200 hours.

 

The initiative aligns to Dell Technologies’ environmental, social and governance (ESG) ambitions to advance sustainability, by creating technology that drives progress and working with customers, partners, suppliers and communities to enable climate action. The GRC is a true partnership across Asia Pacific and Japan (APJ) combining the expertise of the Citizens of the Great Barrier Reef team, Dell, researchers from University of Queensland (UQ) and James Cook University (JCU), Sahaj Software Solutions and citizen scientists. Dell also worked with its data science team in Singapore to continually refine and carry out extensive community testing of the selected deep learning model to ensure that benchmarking standards were met.

 

Looking ahead, Citizens of the Great Barrier Reef founder Andy Ridley hopes to expand the GRC, powered by the Dell’s repeatable and scalable edge solution and deep learning model, to other reef sites globally – with the first trial sites outside Australia to begin in Indonesia.

 

Amit Midha, President, APJ and Global Digital Cities, Dell Technologies, said, “Dell Technologies collaborates with like-minded organisations on ground to enable climate-positive societal impact. With the Citizens of the Great Barrier Reef, our support for research using technology has come a long way since the first Great Reef Census to today, where the power of deep learning will scale the team’s conservation efforts to quick access of quality data and drive a successful collaboration between all involved. We believe such innovations can help our partners make progress on their sustainability ambitions and conservation efforts like these can be replicated both in APJ and globally.”

 

 

Key takeaways:

  • The ongoing collaboration with Citizens of the Great Barrier Reef supports Dell Technologies’ commitment to advancing sustainability and putting its purpose into action in APJ.
  • The new deep learning model by Dell enhances Great Barrier Reef conservation efforts by reducing the time it takes to analyse reef images – volunteers can review 13,000 images in just over a week with the new model; during the first Great Reef Census, this process took more than two months.
  • In this year’s campaign, volunteers will analyse 42,000 images collected from 315 reefs along the 2,300 km length of the reef marine park.
  • The deep learning semantic segmentation model is powered by a Dell high performance computing (HPC) graphics processing unit (GPU) accelerated system to train the model and a Dell PowerScale system to store the data. The onshore compute platform includes Dell PowerEdge servers that support an AI training cluster and multiple AI inference engines.

 

For high-res images, videos and additional background on the GRC, please download our press pack here.