Colorimetric System Based on Android Smartphone: Study Case of Total Chlorine Level Prediction

Abstract

Colorimetric is a system used to measure and describe color. Several previous studies have successfully implemented this system using a smartphone camera for image acquisition of test strips. But unfortunately, most of these studies still transfer image data manually to a computer for processing. In this study, the colorimetric system applied to predict the value of total chlorine levels was made as an Android application. The application can take a picture and directly get results on the smartphone screen. This makes the system work more portable than previous studies. The application is made in a client-server architectural style with RESTful API communication and has two servers, one server is used to transfer images and the other is used to process images into total chlorine values. The application's success rate to reach the two servers is 100%, with the average time required is 2.58 seconds to reach the upload server and 2.68 seconds to reach the computational server. The evaluation results of the regression model used in the application are 0.31 to 0.13 RMSE. These results indicate that the regression model, Artificial Neural Network with Levenberg-Marquardt function, can be used for total chlorine levels prediction system on test strip based on colorimetric.