Proposal Number:          21-1- S5.03-3258

          

          

   

Subtopic Title:
      Accelerating NASA Science and Engineering through the Application of Artificial Intelligence

          

          

   

Proposal Title:
      ML-based Model for Autonomous analysis of Spectral Data.

          

          

   

Firm:

          

eXaminArt, LLC

          

   

Address:

          

922 San Leandro Avenue, Suite G, Moutain View, CA 94043

          

   

Phone:

          

(650) 799-2118                                                                                                                                                                                

          

   

Name:

          

Philippe Sarrazin

          

   

E-mail:

          

philippe.sarrazin@examinart.com

          

   

Address:

          

922 San Leandro ave, Ste G, CA 94043 - 1998

          

   

Phone:

          

(650) 799-2118                                                                                                                                                                                

          

   

Name:

          

Philippe Sarrazin

          

   

E-mail:

          

philippe.sarrazin@examinart.com

          

   

Address:

          

922 San Leandro ave, Ste G, CA 94043 - 1998

          

   

Phone:

          

(650) 799-2118                                                                                                                                                                                

          

   

Estimated Technology Readiness Level (TRL) :                                                                                                                                                          
Begin: 2
End: 4

          

          

     

Technical Abstract (Limit 2000 characters, approximately 200 words):

We propose to develop the foundation of a Machine Learning (ML) model for autonomous interpretation of spectroscopic data, and demonstrate in a cloud-based application for interpretation mineralogical data. Our goal is to demonstrate a tool that can process a range of analytical techniques with a high degree of automation and performance that rival that of expert users with conventional analytical software. The automation and ease of use will enable automated analysis of large quantities of data, allow non-experts to extract valuable high-level scientific products from raw data, and empower experts with a new approach to data analysis. The model demonstrated with this effort will provide the base on which methods for automated analysis spectroscopic data can be developed for implementation in autonomous rovers and spacecrafts.

While our proposed approach can be –and will be– extended to more analytical techniques, we are focusing our current development on two methods: X-ray diffraction (XRD), a well-established technique for identification and quantification of crystalline materials, currently deployed on Mars in Curiosity, and Raman spectroscopy, a more recent method that has shown increasing popularity over the last decade and that will be deployed in upcoming Mars missions including Mars 2020. XRD and Raman provide two different case studies on which we will ultimately develop a technique-agnostic analytical tool.

          

          

     

Potential NASA Applications (Limit 1500 characters, approximately 150 words):

Analysis of mineralogical data in planetary exploration using our web-app QAnalyze (X-ray diffraction, Raman spectroscopy, and more). Model for on-board autonomous analysis of a wide range of spectral data from rovers used in planetary exploration or ISRU, or for remote sensing platform fitted with spectroscopic instruments.

          

          

     

Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words):

Provide rapid, accurate, and automated data analysis of XRD patterns and Raman spectra in a Software as a Service model. New applications opportunities in a wide range of industries (oil and mining exploration, pharma, etc) for discovery, quality control and process monitoring.

          

          

     

Duration:     6