A Review on Artificial Intelligence-based methods for Gemstone Analysis, Quality Grading, and Valuation

Abstract

The introduction of Artificial Intelligence (AI) and Machine Learning (ML) to gemology has revolutionized conventional processes by which gemstone identification, grading, and valuation are done; automation, objectivity and precision are now a part of the process. Traditional approaches to gem evaluation are highly dependent on human experience and human eye, which tend to be biased and subjective. The latest progress in computer vision, deep learning, and spectroscopic data interpretation allowed developing the intelligent systems that could recognize the type of the gemstones, determine the quality of their clarity and color, and determine their market prices with greater accuracy. Moreover, the neural networks that are mixed with the fuzzy logic and probabilistic reasoning have enhanced the making of decisions in unclear situations. This review discusses the intelligent gemstone assessment system development, including intelligent authentication, visual feature mining, and price prediction using data with the aid of AI. New applications of the internet of things enabled sensing, Ra-man spectroscopy, and multispectral imaging are also introduced, and the shift to the reality of real-time, scalable, and transparent systems of gem evaluation is highlighted. The paper ends by summarizing the existing challenges including lack of data, model interpretability, and standardization and provides some future directions of the next generation of intelligent gemstone analysis technologies.