Real-Time Edge Neuromorphic Tasting From Chemical Microsensor Arrays.

ABSTRACT: Liquid analysis is key to track conformity with the strict process quality standards of sectors like food, beverage, and chemical manufacturing. In order to analyse product qualities online and at the very point of interest, automated monitoring systems must satisfy strong requirements in terms of miniaturization, energy autonomy, and real time operation. Toward this goal, we present the first implementation of artificial taste running on neuromorphic hardware for continuous edge monitoring applications. We used a solid-state electrochemical microsensor array to acquire multivariate, time-varying chemical measurements, employed temporal filtering to enhance sensor readout dynamics, and deployed a rate-based, deep convolutional spiking neural network to efficiently fuse the electrochemical

SUBMITTER: LeBow N 

PROVIDER: S-EPMC8695490 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature