Utilizing Machine Learning Algorithms in Conjunction with Terahertz Spectra for Enhanced Plastic Sorting Efficiency

The imperative of addressing climate change is clear, compounded by inadequate waste management intensifying plastic pollution. Challenges in waste management, such as manual sorting and recycling contamination, contribute to ongoing plastic accumulation. To surmount these hurdles, advanced technologies like terahertz (THz) technology integrated with machine learning algorithms such as Linear Discriminant Analysis (LDA), Principal Component Analysis (PCA), and Support Vector Machine (SVM) are being investigated. This integration demonstrates considerable potential in improving plastic separation and sorting processes, achieving an impressive accuracy of 100%. Such advancements represent a significant stride towards more effective and sustainable solutions in combating plastic pollution and revolutionizing waste management practices.