Do you remember our Data Scientist Max? He wrote his Master Thesis at the University of Luxembourg in collaboration with Circu Li-ion. His focus: Object localization and classification for automated battery upcycling. In this blog post, Max explains how AI and deep learning can help enable a circular battery value chain.
Why did you choose to focus your research on automated battery upcycling in collaboration with Circu Li-ion?
Max: Firstly, the battery upcycling technology has a huge environmental impact on reducing battery waste as well as sustainable recycling. By showcasing the potential of AI and deep learning in enhancing the efficiency of battery upcycling, we can inspire innovation and encourage the adoption of green technologies across industries. Secondly, this topic highlights the significance of interdisciplinary collaboration in solving complex environmental challenges, demonstrating how data science can contribute to sustainability.
What did you find out about object localization and classification?
Max: Within my Master Thesis project, important image data of Ninebot battery packs, used e.g. in E-scooters, were collected and stored enabling easy access for future use. From this data two different object localization and classification models were trained to reliably classify Ninebot battery packs into upcycling or recycling based on visual features.
Were there battery packs falsely classified as ready to recycle?
Max: In the case of misclassification, it was more often the case that a recycling battery pack was mislabelled as upcycling. This means that if the model's predictions are not correct, there are no valuable intact battery packs at risk of being disposed.
How do these results benefit Circu Li-ion?
Max: This project helps Circu Li-ion's mission to revolutionize the battery recycling industry. An AI-powered classification system improves the accuracy and efficiency of the battery upcycling process. This does not only enhance the company's capacity to recover valuable materials, but also reduces environmental impact and operational costs. The advantage lies in the collaborative nature of the project, where academic research meets industrial application, resulting in innovative solutions that address real-world problems.
Thank you for sharing your contribution, Max!
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Photo: Max Sinner
Source: The information presented is derived from Max’s Master's Thesis and the collaborative project between the University of Luxembourg and Circu Li-ion S.A.