RECOPTIC APPLICATION DEVELOPMENT WITH ARTIFICIAL INTELLIGENCE ON DRUG DETECTION FEATURE FOR VISUALLY IMPAIRED PEOPLE

Authors

  • Annisa Umulfath Gunadarma University
  • Abdurrahman Gunadarma University
  • Ahmad Mawardi Hakim Gunadarma University
  • Muhammad Haikal Gunadarma University
  • Manfred Michael Gunadarma University
  • Guntur Eka Saputra Universitas Gunadarma

DOI:

https://doi.org/10.56127/ijst.v2i1.276

Keywords:

Recoptic, OCR, Drug, Android, Artificial Intelligence

Abstract

Recoptic application is an optical recognition application. This application is equipped with TalkBack and the application of artificial intelligence so that the camera on the smartphone can detect and provide information about drugs, text, and objects. Recoptic is currently implemented on Android smartphones and applies the image-to-text converter technology with Optical Character Recognition (OCR). The camera can detect the text on the drug cover and the type of drug, and the application will read out the information with TalkBack. Recoptic has been tested with a user acceptance test (UAT) from experts in medical disciplines and potential users, namely blind people. Features in the application include a voice to guide users and drug detection to read and provide information with sound, objects, and text. The application has been tested and received input with the user acceptance test (UAT) method from experts and blind users. Based on the test results and data collected, as many as 923 drugs have been acquired, and the resulting more than 80% UAT is considered successful for the subject by blind people. Recoptic is implemented on Android-based smartphones.

References

Road map of visual impairment control program in indonesia 2017 - 2030. 2017;

Balasopoulou A, Κokkinos P, Pagoulatos D, Plotas P, Makri OE, Georgakopoulos CD, et al. Symposium Recent advances and challenges in the management of retinoblastoma Globe ‑ saving Treatments. BMC Ophthalmol. 2017;17(1):1.

Almukainzi M, Almuhareb A, Aldwisan F, Alquaydhib W. Medication use patterns in the visually impaired in Saudi Arabia and the importance of applying Braille labeling. Saudi Pharm J. 2020;28(3):274–80.

Hidayat L. Assistive Technology Pada Aplikasi. J Exponential (Education Except Child. 2020;1(2):144–52.

Martiniello N, Eisenbarth W, Lehane C, Johnson A, Wittich W. Exploring the use of smartphones and tablets among people with visual impairments: Are mainstream devices replacing the use of traditional visual aids? Assist Technol. 2022;34(1):34–45.

Karolina CM, Aulianto DR. Pengalaman Penggunaan Talkback Dan Whatsapp Pada Smartphone Untuk Menunjang Komunikasi Para Penyandang Cacat Tuna Netra. J Visi Pustaka. 2019;21(3):205–14.

Pratama A, Hadista A, Swedia ER, Cahyanti M, Studi P, Informatika T, et al. Aplikasi Deteksi Teks pada Gambar Menggunakan Implementasi Firebase ML KIT Berbasis Android. 2019;

WHO. Improving access to assistive technology/EB142.R6. 2018;(February):1–6.

Approach S, Countries M-I. Digital Assistive. 2020;(November).

Senjam SS. Smartphones as assistive technology for visual impairment. Eye. 2021;35(8):2078–80.

Sivan S, Darsan G. Computer vision based assistive technology for blind and visually impaired people. ACM Int Conf Proceeding Ser. 2016;06-08-July.

Matiacevich S, Celis Cofré D, Silva P, Enrione J, Osorio F. Quality parameters of six cultivars of blueberry using computer vision. Int J Food Sci. 2013;2013.

Wiley V, Lucas T. Computer Vision and Image Processing: A Paper Review. Int J Artif Intell Res. 2018;2(1):22.

Setiawan AF. Text To Speech Bahasa Indonesia Menggunakan Metode Dhipone Concatenation. Semin Nas Inov Dan Apl Teknol Di Ind. 2016;37–42.

Sommerville I. Software Engineering (9th ed.; Boston, Ed.). Massachusetts: Pearson Education. 2011. 77 p.

Jokela T, Iivari N, Matero J, Karukka M. The standard of user-centered design and the standard definition of usability: Analyzing ISO 13407 against ISO 9241-11. ACM Int Conf Proceeding Ser. 2003;46:53–60.

Published

2023-03-10

How to Cite

Annisa Umulfath, Abdurrahman, Ahmad Mawardi Hakim, Muhammad Haikal, Manfred Michael, & Saputra, G. E. (2023). RECOPTIC APPLICATION DEVELOPMENT WITH ARTIFICIAL INTELLIGENCE ON DRUG DETECTION FEATURE FOR VISUALLY IMPAIRED PEOPLE. International Journal Science and Technology, 2(1), 1–7. https://doi.org/10.56127/ijst.v2i1.276

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