Opinion: Can technology address plastic pollution crisis

Today, grass roots campaigners like Extinction Rebellion, Greta Thunberg, and British national treasure – David Attenborough – are collectively raising the profile of environmental sustainability, making us more passionate than ever. However, one of the worst hit natural resources remains our oceans.  Earlier this year, American explorer Victor Vescovo dived the Mariana Trench in the Pacific Ocean at a depth of almost seven miles. Along the way, Vescovo found a variety of sea creatures and rare wildlife– as well as a plastic bag and sweet wrappers. 

Sadly, this is indicative of a much wider issue. Consider the so called Great Pacific Garbage Patch (GPGP), which the largest of five offshore plastic accumulation zones in the world’s oceans, providing a stark manifestation of global plastic pollution and the urgent challenges that we face.  It was recently estimated that there are 1.8 trillion pieces of plastic floating around the patch, measuring approximately 1.6 million square kilometres1. Recognising the urgency of this issue, the United Nations recently announced that 186 countries have reached an agreement to monitor and track movements of plastic waste outside their borders. This is to create a better-regulated global trade in plastic, and each country will have to work out the most appropriate way to adhere to the agreement. However, one of the biggest challenges is effectively tracking and locating plastic in our oceans.           

 

As technology advances, we are seeing the emergence of new and collaborative methods of addressing this challenge. The process of properly quantifying the mass of disintegrating plastics in the ocean requires taking spatially distributed measurements of all sizes and classes of debris on a global scale, as well as the plastic beneath the surface. Clearly, this is not a problem that any single technology or nation can solve. Scientists must focus on the acquisition of data from multiple sources – such as satellite imaging mixed with global and local observations – to create models of surface current circulation and give indicators of the levels of plastic presence.  
                
Our means of data collection and analysis poses another challenge.  To get meaningful output from such a diverse dataset, and to improve their decision-making ability, scientists must fully and thoroughly analyse the data. Given the sheer volume of data, there is a definite need to implement artificial intelligence (AI) in some capacity – via a machine learning or deep learning-based approach – to make sense of what is collected.
                
AI can be used throughout the process of data collection and analysis. First, partners must create and maintain a repository where they can access and store their data easily, one which will be able to cope with demands of such huge amounts of data. Additionally, these emerging technologies will help with the development of general tools for learning the prescribed plastic detection and tracking processes. An example is the use of drones, which are being mounted with cameras and flown locally across coastal regions of oceans.  To improve positive detection rates, AI is being trained to recognise the difference between shells, jellyfish and plastic products. 
                 
Finally, to be effective, AI must be able to perform automatic browsing and processing to deliver the expected monitoring and tracking services. If the technology is not able to continually update its results based on incoming data, then we would not have a real-time view of the issue. 

As the world continues to come together in a bid to expose and address this growing problem, we must continually look at the ways in which technology is enabling the ongoing monitoring, tracking and clean-up of the plastic that has already blighted such a large segment of the world’s oceans.