Data science and its role in recycling and managing waste
This article is originally published at https://www.mango-solutions.com
It’s Global Recycling Day today and a day to raise awareness of the importance of recycling and how crucial and lasting change can help preserve the future of our planet. Recognised in the UN’s Sustainable Development Goals 2030, we are already seeing many individuals, governments and organisations taking direct action to support the global green agenda.
Founded by the Global Recycling Foundation, this year’s theme is #recyclingheros and recognises people, places and organisations that inspire us – demonstrating positive action.
From plastic pledges and recycling, to waste targets, businesses are positively impacting the environment, and data science is being used positively to reduce environmental impact and financial costs – aligned to their corporate responsibility. There are many examples of data analytics applications that can play just a small part in decelerating the process of climate change – the more focus that organisations place on this, the brighter the outlook for our planet. We decided to take a look at some of the positive use cases.
Food waste
Think about the waste problem in supermarket fresh food sales. Many businesses are using data science to help the UK meet its target of eliminating food waste to landfill by 2030. Analytics of weather patterns can help supermarkets ensure they have the right amount of seasonal produce to meet demand for a particular weather period without wastage; and enhanced analytics of customer weekly shopping habits would mean the store could ensure it has met demand without having surplus fresh food.
Gousto, a British meal kit retailer, implemented forecasting algorithms in an effort to reduce their food waste. They were able to predict demand and analyse seasonal trends to better manage their fresh food stock. Forecast modelling allowed the business to not only predict with a high degree of confidence the number of orders they would receive in future weeks, but also predict the performance of existing and new recipes.
Plastic waste
Plastic waste posing a considerable threat to our planet, with 8 million metric tons of plastic being added annually to the world’s oceans. That is why many businesses in the UK have come together to work towards having all plastic packaging recyclable, reusable or compostable by 2025. One such company is Tesco who are rolling out collection points for soft plastic packaging in their stores. Tesco’s efforts should help the public in their efforts to recycle as well their own.
Outside of the UK, many companies are also reducing their plastic waste and increasing their recycling, with many also helping the public do so. The Gringgo Indonesia Foundation, with the help of Google, have used AI and machine learning to create an app to help better classify waste items. It can be used by businesses and the public to help improve their recycling. With the use of data science, within a year of launching the app, recycling rates were increased by 35% in their first pilot village.
Space junk
Space junk poses a danger to astronauts in orbit, the world’s network of communication and weather satellites. Luckily, data science is here to help. NASA have been developing technology to remove space junk. Using machine learning algorithms, NASA are working towards improving the detection of space junk for removal.
Clinical waste
Since the start of the COVID-19 pandemic, there has been an increase in single use plastics and clinical waste. With only 15% of clinical waste being hazardous, there is a massive opportunity to reduce and properly manage clinical waste using data science. From reducing the number of unnecessary hospital appointments to the size of some healthcare equipment, a positive change can be made.
Reducing waste and recycling is vital for the future of our world. Data science provides many tools for creating and implementing solutions, and with data-driven businesses striving to reduce their waste, the future looks bright.
To discuss any use cases to align your recycling goals, contact us.
Author: Elizabeth Brown, Professional Placement Student at Mango
The post Data science and its role in recycling and managing waste appeared first on Mango Solutions.
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This article is originally published at https://www.mango-solutions.com
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