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

Agnes Diza Fahira, Adhi Harmoko Saputro

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationProceedings - 8th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2021
EditorsAuzani Jiddin, M Amjad, Imam MI Subroto, Mochammad Facta
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages267-272
Number of pages6
ISBN (Electronic)9786236264195
DOIs
Publication statusPublished - 2021
Event8th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2021 - Virtual, Semarang, Indonesia
Duration: 20 Oct 202121 Oct 2021

Publication series

NameInternational Conference on Electrical Engineering, Computer Science and Informatics (EECSI)
Volume2021-October
ISSN (Print)2407-439X

Conference

Conference8th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2021
Country/TerritoryIndonesia
CityVirtual, Semarang
Period20/10/2121/10/21

Keywords

  • Android
  • Artificial Neural Network
  • Chlorine
  • Intelligence Instrument
  • Levenberg-Marquadt
  • RESTful API

Fingerprint

Dive into the research topics of 'Colorimetric System Based on Android Smartphone: Study Case of Total Chlorine Level Prediction'. Together they form a unique fingerprint.

Cite this