Potential of edge machine learning for instrumentation.
Journal:
Applied optics
Published Date:
Mar 10, 2022
Abstract
New developments in radiation and photonic detectors improve resolution, sensitivity, size, and rate, all of which contribute to a gigantic increase in the data production rate. Moving data analysis and compression adjacent or even embedded within the detector hardware will reduce the data volumes generated, thereby reducing material cost, power, and data management requirements. Several solutions are already being developed both on the hardware and on the software side to facilitate the use of machine learning as a real-time data analysis solution.