A portable potentiometric electronic tongue leveraging smartphone and cloud platforms

TL;DR

This paper introduces a portable electronic tongue system that combines potentiometric sensors, smartphone interface, and cloud computing to enable rapid, remote chemical analysis and classification of liquids.

Contribution

It presents a novel integrated platform with miniaturized sensors, smartphone data acquisition, and cloud-based machine learning for portable chemical fingerprinting.

Findings

Classifies beverages and mineral water within 1 minute

Uses a sensor array without a true reference electrode

Employs machine learning for liquid identification

Abstract

Electronic tongues based on potentiometry offer the prospect of rapid and continuous chemical fingerprinting for portable and remote systems. The present contribution presents a technology platform including a miniaturized electronic tongue based on electropolymerized ion-sensitive films, microcontroller-based data acquisition, a smartphone interface and cloud computing back-end for data storage and deployment of machine learning models. The sensor array records a series of differential voltages without use of a true reference electrode and the resulting time-series potentiometry data is used to train supervised machine learning algorithms. For trained systems, inferencing tasks such as the classification of liquids are realized within less than 1 minute including data acquisition at the edge and inference using the cloud-deployed machine learning model. Preliminary demonstration of the complete electronic tongue technology stack is reported for the classification of beverages and mineral water.