$GTCH Since a Kirlian image includes a vast amount of information, a private, custom real-time algorithms is planned to be developed. This approach is planned to utilize the analysis of an image object’s neighboring positions, utilizing this data to increase the overall detection speed. The method is contemplated to process a computation of the original objects and their neighboring information to formulate an efficient flow that can be repeatedly executed, achieving a true real-time processing. Finally, advanced algorithmic and hardware related architectures will exploit parallel processing to accelerate the complex computations operations. Data parallelism can be achieved using a CPU that performs programmatic instruction, which is efficient to accelerate large amount of data processing. The company targets this development to achieve a high speed, real time Kirilian imaging processing that may be of use for health-related advice.
