Team 28

The main purpose of this SRS document is to illustrate and outline the requirements for our graduation project (Electronic Tongue). This document will explain in detail the software implementation(mobile application) and how our results will appear on the application. The software implementation includes different machine learning algorithms and methods used. E-Tongue is mainly classifying liquids according to their different tastes. Our goal is to save money, effort, and time for food industries by using our product. The application will contain a dataset of different liquids that will be used to classify the user inputs by the potentiostat.

This system will cause great hype in the industrial field. The electronic tongue has several advantages, including reduced detection fatigue, and its results are more reliable. Our proposed project will help in saving money as the system will replace the connoisseurs. So, it won’t be essential for the industries to hire many people. Moreover, it will save more time as the machine is faster than the human and more accurate. The ET system will be used to classify the liquids as if it’s acid, base, or umami taste.

In the application, the first screen includes two buttons. The first button will go to a new screen, which is related only to the chemists. This screen has three empty sections. The user will enter the three readings from the chemical instruments that existed in the faculty of pharmacy at Misr International University. When the user enters the inputs, the API is called to reach the classifier in order to classify the liquids. After this step, the result will appear to the user on a new screen with the liquid name and the percentage of its accuracy. The second button is related to the researchers, scientists, and workers in the industry field (having five working electrodes in electronic tongues). When clicking on the second button, five empty sections will appear to the user. The user will enter five readings of the five electrodes (gold, silver, platinum, palladium, and tungsten), then this will lead him to a new screen with the liquid’s classification. When the user enters the inputs, the API call function is called to reach the classifier in order to classify the liquids. After this step, the result will appear to the user on a new screen with the liquid name and the percentage of its accuracy.  

An E-tongue taste sensor array is a smart instrument with an appropriate pattern recognition system. E-tongue is a fluid classifier utilizing terminal-based sensors. A few references were chipping away at the order of milk, dark tea, and espresso. However, we will chip away at more fluids with better precision and better recognizable proof. This will be the most ideal decision for the manufacturing plants that utilization fluids classifiers as it will be more appropriate and more straightforward. Rather than having a specialist for each grouping, the E tongue will be more helpful and low in cost.