An innovative method was developed to evaluate the feasibility of combining artificial intelligence (AI) and advanced methods to standardize high-quality turquoise from the Neyshabur mine. Initially, conventional methods in gem identification and artificial intelligence were used to identify turquoise, then advanced gemological methods were used for standardization.
   The gemological characteristics of turquoise were determined with the help of digital image analysis and artificial intelligence (AI). This method relies on image processing by artificial intelligence (AI). 1600 digital image series of 18 samples from different areas of the Neyshabur turquoise mine were prepared and transferred to the database. The accuracy of turquoise gemstone identification using this method was 94%. With the help of XRD analyses, mineral identification, crystal structure determination, phase determination, and crystal particle size determination were possible. The average particle size of lower quality turquoise was 201.2 °A and gem quality turquoise was 137.9 °A calculated by Debye-Scherer formula. The identified Raman peaks are in the ranges of 200 cm^1-, 400 cm^1- and 1000 cm^1-. The peaks at 1031 cm^1-and 1036 cm^1-are related to phosphate vibrations, but the peaks in the range of 1-200 cm^1- are probably related to water or hydroxyl vibrations in the structure. Turquoise samples examined by SEM showed that low quality turquoises contain Si and Ca elements in addition to their main elements.
   Comparison of RAMAN, XRF, XRD and SEM analyses of turquoise from Neyshabur mine with turquoise from other regions of the world showed that turquoise from Neyshabur mine has its own unique XRD pattern that is significantly different from that of turquoise from other regions of the world. These differences are also clearly visible in RAMAN, XRF and SEM data analyses. This research showed that the turquoise gemstone from the Neyshabur mine (of gem quality) should be introduced as the world's standard turquoise reference.