AI Technology for Waste Management
Leanest “Waste Sorting Robot” project with EAS and EU funding.
AI technology can be integrated into waste management and sorting processes for achieving efficiency and optimization.
Leanest has set the ambition to contribute to a cleaner environmental future. With the help of EAS and European funding, we design and develop a waste sorting robot that will be operating on AI-based algorithms. This project is funded as part of the Union’s response to the Covid-19 pandemic.
The project develops robotic arms for waste sorting that can be installed to the existing manual sorting lines and ensure 60% more sorting efficiency and at the same time to reduce the amount of waste sent to incineration.
Manufacturing Optimization
AI Solutions in Industry
Workforce Planning
About the Project
The purpose of the project is the more accurate and also faster sorting of packaging that has been collected by type. The goal is to send at least 60% more packaging for recycling compared to the current situation and avoid burning them.
In Estonia, as an example, the bulk of waste is manually sorted. This is also how the majority of smaller sorting centers in Europe work. When sorting by hand, it is enough to pick out about half of what is being sorted. The focus is on larger pieces or on items that can be sold and give more value.
The goal of the project and as a solution to this, Leanest will develop a sorting robot as a replacement for one person on the existing manual sorting lines of the collected packages. The first tests gave the result, that with the developed robotic arm operating on the artificial intelligence, it is possible to sort 60% more materials, which increases recycling and reduces waste incineration.
This project is being supported by EU European Regional Development Fund by 125 354 euros.
About Technology
Artificial Intelligence can contribute significantly to waste management, especially in regards to automated waste sorting at waste collecting and sorting mills. Once the waste is collected and on the conveyor belt, it will be scanned via cameras, and information will be processed by AI based software. The analysis will be performed from deep learning algorithms and categorization for sorting is being completed – different items on the conveyer belt will be addressed to the appropriate sorting or recycling method, consequently ensuring efficient and sustainable waste management.
In addition to the automated sorting decision making process also AI-operated robots can efficiently sort the items instead of human labor. Robots and relevant technology can pull off the sorted items from the belt for further processing. Essentially, AI speeds up the whole process as human labor can sort approximately 35 items per minute while the same number reaches about 200 if done with AI-operated machines.
With AI technology one major bottleneck in the process of waste management can be avoided.