Machine Learning Technology Using Thick Film Gas Sensor Toxic Liquid Detection For Industrial IOT Application

Right now proposed paper has been made to investigate the affectability, reaction of SnO 2 based Pd-doped thick gas sensor for hazardous liquid as for example Vodka, LPG and Whisky identification. 1" × 1" alumina matrix material was exploited prevarication of thick film gas sensor. It comprises of a gas touchy layer SnO2 doped with 1% Pd, a conjoin of electrodes underneath the gas detecting layer filling in as a contact cushion for the sensor. Likewise, a radiator component is additionally planned on the posterior of the substrate The affectability of the sensor has been learned at various Pd-doped concentration (1 % Pd doped) at a constants temperature 3000C upon exposure Vodka, LPG & Whisky. In this paper, experimental results simulate in Anaconda software with the Spyder tool (Spyder 3) tool using the python programming language. Python programming is written in machine learning clustering techniques and simulated results match the experimental results with different temperatures. Industrial internet of things predominantly exploited in the frame of reference for industry 4.0. In the proposed paper, IIoT was exploited for identifying hazardous liquid.