The impending exhaustion of non-renewable natural resources emphasizes the importance of sustainable materials. One environmentally friendlier alternative to plastics are biocomposite materials, which are composed of recycled or virgin polymer and a natural fiber material. In order to be to be truly sustainable, the material has to be efficiently recycled, a task which demands a means for their sorting. This paper outlines a method for distinguishing different plastic and biocomposite samples from one another based on hyperspectral imaging. The developed regression model correctly classified 96 % of the samples in the dataset. In the case of biocomposite samples, the accompanying polymer was quite accurately recognized.
|Title of host publication||4th International Conference on Natural Fibers – Smart Sustainable Solutions, ICNF 2019|
|Subtitle of host publication||Book of Abstracts|
|Number of pages||2|
|Publication status||E-pub ahead of print - 1 Jul 2019|
|MoE publication type||Not Eligible|
Sormunen, T., Järvinen, S., Lämsä, A., Immonen, K., Mannila, J., & Peltola, J. (2019). Material sorting using hyperspectral imaging for biocomposite recycling. In R. Fanguiero (Ed.), 4th International Conference on Natural Fibers – Smart Sustainable Solutions, ICNF 2019: Book of Abstracts (pp. 250-251)