The world’s oceans are burdened with unnecessary plastic waste, with estimates of between 75 and 199 million tons [68 – 188M tonnes] already polluting marine ecosystems today. And to make things worse, without intervention, plastic waste entering aquatic environments could nearly triple—from 9–14 million tonnes per year in 2016 to a projected 23–37 million tonnes per year by 2040.
The Ocean Cleanup, a nonprofit foundation dedicated to ridding the oceans of plastic, is leveraging AI-powered computer vision to enhance debris detection, modelling, and collection. But deploying and scaling intelligence at the edge presents unique challenges—how do you train and deploy an AI model, process real-time data on moving vessels, in extreme environmental conditions, with limited connectivity and power constraints?
This Blueprint presentation showcases the collaboration between Au-Zone and The Ocean Cleanup to develop and deploy an edge-optimized AI pipeline for The Ocean Cleanup’s Automated Ocean Debris Imaging System (ADIS). We will discuss the challenges and break down the development of an embedded machine learning model for real-time plastic density monitoring—from data collection and model optimization to deployments and scaling up.
Attendees will gain insights into how the system was developed and how the data collected will be used to improve modelling of the marine systems to further optimize recovery of the debris. Join us for this presentation on AI for good, as we chart a course for scalable, AI-driven ocean conservation—transforming innovation into real-world impact.