EasySort is the AI-based waste sorting complex that identifies unwanted goods and waste products as either paper, plastic or mixed type rubbish. We propose this business idea as a great way to address an important world issue - an increased volume of unrecycled waste products due to the inefficiency of modern sorting systems. With our technology, we look forward to increasing the rate of the waste sorting process, thereby lessening a negative impact on our precious nature.

The modern world is obsessed with consuming more and more products. Lots of recycling factories don’t manage to recycle properly this supply of garbage because of inefficient manual labor. By hiring large number of waste disposal workers whose recycling efficiency is low, waste management companies put both their workers and our climate at huge risk. Thus, our main clientele is recycling centers.

In order to keep recycling pace high, we suggest automatized system of garbage sorting using neural networks and object recognition. This solution is supposed to increase efficiency of factories, consequently lessening negative impact on climate and environment.

First of all, the proper sorting of the garbage directly reduces the burning of the waste, which is the last measure that today’s ecologists resort to. If all types of waste could be separated, much less garbage will be left for burning. Secondly, the number of plastic products in dump exposed by sun will be reduced as well as the non-degradable waste inhibiting river flow, thus toxic emissions to the environment will decrease. Thirdly, the efficient sorting contributes to the production of the recycled eco-materials that support green movement by concentrating customer’s attention on care for the climate and environment.

As part of our discussion, we found some ways in which our product would yield profit. We have decided to engage in the most direct B2B interaction by offering our technology and maintenance service to waste management companies/centers all over Kazakhstan. In case of successful experience, we want to expand the borders of our business to developed countries, where the volume of investments and interest in innovations is signified.

Yet, we hope to search for even better business strategies and models as participants of Create the Future Contest.

Our business idea's technical part includes the usage of Artificial Intelligence technology, the neural networks in particular. While the most advanced sorting systems use X-rays to filtrate waste by their density, EasySort identifies the type of waste based on its physical features by using the image from the camera. We have trained our program, neural network, to recognize objects by comparing them to images from the existing dataset. The system is already able to distinguish between paper, plastic, and mixed products.

As of today, we are working on expanding the range of wastes that can be recognized by our system