  In general, most of the substances in nature exist in mixtures, and the
noninvasive identification of mixture composition with high speed and accuracy
remains a difficult task. However, the development of Raman spectroscopy,
machine learning, and deep learning techniques have paved the way for achieving
efficient analytical tools capable of identifying mixture components, making an
apparent breakthrough in the identification of mixtures beyond the traditional
chemical analysis methods. This article summarizes the work of Raman
spectroscopy in identifying the composition of substances as well as provides
detailed reviews on the preprocessing process of Raman spectroscopy, the
analysis methods and applications of artificial intelligence. This review
summarizes the work of Raman spectroscopy in identifying the composition of
substances and reviews the preprocessing process of Raman spectroscopy, the
analysis methods and applications of artificial intelligence. Finally, the
advantages and disadvantages and development prospects of Raman spectroscopy
are discussed in detail.
