Applying Machine Learning for Analyzing and Predicting Illegal Dumpsites

How AI can contribute to a cleaner world. In this article, we discuss our analysis of illegal dumpsites across the world, both in local and global scales.

This article is part of the Omdena series of articles ‘The Trash We Make’, which summarizes the work carried out in the [Omdena Challenge in partnership with TrashOut_](https://omdena.com/projects/ai-illegal-dumping/). You can find the first articles in the series [here_](https://medium.com/omdena/the-trash-we-make-ai-solutions-for-a-cleaner-world-18caeeb95e85). This article was written by Ramansh Sharma, Rosana de Oliveira Gomes, Simone Vaccari, Emma Roscow, and Prejith Premkumar.

Just like any other day, we start our morning with a coffee and a snack to go from our favorite bakery. Later on the same day, we check out our mail where we find letters, newspapers, magazines, and possibly a package that just arrived. Finally at night, after a rough week, we decide to go out to have drinks with friends. Sounds like a pretty uneventful day, right?

Except that we produced lots of trash in the form of plastic, glass, paper, ad more.

_According to _eurostat, it is estimated that an average person in Europe produces more than 1.3 kg of waste per day (in Canada and the USA, it can go up to more than 2 kg). This is equivalent to a person producing 800 kg of trash per year. Now imagine millions of… billions of people doing the same. Every day!

To give you an even clearer perspective: less than 40% of all the waste produced in Europe is recycled — and it is even less across the other continents. Even further, it is estimated that 20% of all generated waste ends up on illegal dumpsites in Europe, and 50% in Africa.

TrashOut is an environmental project which aims to map and monitor all illegal dumps around the world and to reduce waste generation by helping citizens to recycle more. This is done through a mobile and web application that helps users with locating and monitoring illegal dumpsites, finding the nearest recycling center or bin, joining local green organizations, reading sustainability-related news, and notifying users about updates on their reports.

In this article, we discuss our analysis of illegal dumpsites across the world, both in local and global scales.

geospatial-analytics machine-learning waste artificial-intelligence unsupervised-learning

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