Anaeko Blog

The War on Plastic - Is Data the solution?

Mar 20, 2019 12:08:00 PM

It's hard to miss the images of plastic waste in the media, with some of the statistics and pictures being both frightening and sickening. In 2015, the annual production of plastics increased to nearly 381 million tonnes, this is roughly equivalent to the mass of two-thirds of the world population. From a study conducted in 2010, it was estimated that 8 million tonnes of plastic entered the oceans with roughly 10,000 to 100,000s tonnes of plastic in surface waters (Our World in Data). 

According to a recent report from the World Economic Forum and PwC, Harnessing Artificial Intelligence for the Earth, the maturation of key technologies including big data and machine learning is opening up new possibilities for Earth conservation.  Big Data is key to measuring and tracking Earth's resources. Using machine learning, data visualization and big data can drive better decisions.  So how do we actually utilise Data?

 

#1 Public Awareness 

By visualising data that can be disseminated across social media, this helps to increase public awareness. It is human nature to survive, so when we as humans, see startling images of plastic killing off wildlife and hurting the environment we live in... we act. A recent new challenge has gone viral on the social media platform Reddit. This calls upon young people to post pictures of a before and after a 'clean up'. This has prompted thousands of people to go outdoors and help clear trash and litter. Another example of public awareness were the horrific images brought to us by BBC's Blue Planet which showed an albatross parent feeding plastic to their chicks, an astounding 88% of people who saw 'Blue Planet II' have now changed their lifestyle.

 

#2 Lifespan of Plastic 

By keeping track of information about certain types of plastic and the lifespan of it we can better inform the public in how to shop. There are thousands of different plastics, each with its own composition and characteristics. Some of these plastics can be recycled, remelted and reused but others cannot. By using this data, some companies have created solutions like an application programming interface (API) that can integrate with in-store consumer loyalty schemes and educate consumers on the sustainability of packaging choices. 

 

#3 Trends 

Thanks to all the public awareness around the subject, we are seeing increased trends both with social media and with web browser searches. If we look at the diagram below we can see the increase of the words 'plastic waste' on a google search over the past five years. 

plastic waste search

This is when we can use data science practices. By using cluster analysis on social media and remarketing techniques, it is possible to send continuous adverts focused around the topics of plastic waste to the relevant audiences.  These adverts can focus on different ways to reduce plastic and reinforce the destruction plastic waste is having on the environment. 

 

Plastic waste and recycling is currently at the forefront of many people's mind and companies' objectives. With supermarkets now charging for plastic bags and some retailers cutting plastic from their facilities altogether, we ask if this is enough? With plastic production and waste still increasing, can the government do more to utilise machine learning and historical data to change how we currently process. The Defra UK, have put in a huge effort on their marketing front to raise awareness about recycling and plastic waste, but if the the facilities aren't there or countless products can't be recycled, how can we expect the issue to be resolved?

 

Anaeko's mission is to enable data insights that deliver better public services to citizens. We specialise in finding insights within data and using these to improve better public services. If you want more information regarding data services, feel free to get in touch! 

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Topics: Government, Machine learning, Artificial Intelligence, Big Data, Plastic, Environment

Lucy Martin
Written by Lucy Martin