A Big Data Platform for Surface Enhanced Raman Spectroscopy Data with an Application on Image-Based Sensor Quality Control

Surface-enhanced Raman spectroscopy (SERS) significantly enhances the Raman scattering by molecules, enabling detection and identification of small quantities of relevant bio-/chemical markers in a wide range of applications. In this paper, we present a big data platform with both a local client and cloud server built for acquiring, processing, visualizing and storing SERS sensor data. The local client controls the hardware (i.e., spectrometer and stage) to collect SERS spectra from HP designed sensors, and offers the options to analyze, visualize and save the spectra with meta-data records, including relevant experimental conditions. The cloud server contains remote databases and web interface for centralized data management to users from different locations. Here we describe how this platform was built and demonstrate its use for automated sensor quality control based on sensor images. Sensor quality control is a common practice, employed in sensor production to select high performing sensors. Image-based approach is a natural way to perform sensor quality control without destructing the sensors. Automating this process using the proposed platform can also reduce the time spent and achieve consistent result by avoiding human visual inspection.