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A smart handheld Raman spectrometer with cloud and AI deep learning algorithm for mixture analysis
Author(s): Lynn Chandler; Bill Huang; Tao Tao Mu
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Paper Abstract

Raman spectrometry has proven to be by far the most powerful noninvasive analytical technique for direct material identification. In this paper we introduce the first smart Raman device with a Cloud data platform and AI deep learning algorithms- the CloudMinds XI™. This smart phone operated Raman features high performance, fully automated operation, and capability for mixtures analysis in real time. This novel Cloud AI Raman spectrometer is fully integrated with the Android-based CloudMinds A1 smart phone. The A1 phone provides the full functionality of a smartphone including voice calls, emails, GPS location, and image capture by camera, and maintains constant Wi-Fi/blue tooth and 4G LTE connections, letting you stay connected to Raman data constantly. The cloudbased data platform not only allows speedy analysis but also enables spectral library expansion with ensured security. In addition, CloudMinds has developed its proprietary Al algorithm using Google Brain's second-generation machine learning system, TensorFlow. This technology improves analysis accuracy and gets continually better results as it learns and trains data while connected to the cloud. A mixture of three substances has been successfully analyzed with ratios within seconds by this handheld Raman spectrometer for the first time, and this paper will present the results from the mixture analysis. This Cloud AI handheld Raman is the best solution for many field applications, especially when real time analysis and central cloud data platform support are essential.

Paper Details

Date Published: 13 May 2019
PDF: 9 pages
Proc. SPIE 10983, Next-Generation Spectroscopic Technologies XII, 1098308 (13 May 2019); doi: 10.1117/12.2519139
Show Author Affiliations
Lynn Chandler, CloudMinds Technology Inc. (United States)
Bill Huang, CloudMinds Technology Inc. (China)
Tao Tao Mu, CloudOptek, Inc. (China)
Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 10983:
Next-Generation Spectroscopic Technologies XII
Richard A. Crocombe; Luisa T.M. Profeta; Abul K. Azad, Editor(s)

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