Automated Medicine Dispenser and Verification by YOLOv5 Models

Authors

  • Pinphong Ruangraweenukit Student, Faculty of Informatics, Burapha University, Chonburi 20131, Thailand https://orcid.org/0009-0008-1055-4628
  • Thanakrit Nupim Student, Faculty of Informatics, Burapha University, Chonburi 20131, Thailand https://orcid.org/0009-0008-2713-9359
  • Anucha Luebangyai Student, Faculty of Informatics, Burapha University, Chonburi 20131, Thailand
  • Ponlawat Chophuk Lecturer, Faculty of Informatics, Burapha University, Chonburi 20131, Thailand

DOI:

https://doi.org/10.14456/jcct.2024.6

Keywords:

Automated Medicine, Dispenser and Verification, YOLOv5 Models

Abstract

Medication errors are a major problem to affects the safety of patients around the world, and is one of the causes of death is incorrect drug use. This issue is particularly acute for patients with complex medication schedules, exacter Medication errors are a major problem to affects the safety of patients around the world, and is one of the causes of death is incorrect drug use bated by hospital dispensing delays that contribute to these errors. This research focuses on developing an automated pill dispenser powered by a Raspberry Pi to enhance the accuracy of drug dispensing, reduce errors, and provide pertinent medication information. The system is designed to accept direct prescription inputs from physicians and incorporates YOLOv5 as the artificial intelligence (AI) component to ensure prescription accuracy. The findings from the development phase reveal that Model 3 demonstrated the highest efficiency at 64%. The AI's verification accuracy was determined to be 90%. Which makes the medication error from the system 11%.

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Published

07/18/2024

How to Cite

Ruangraweenukit, P., Nupim, T., Luebangyai, A., & Chophuk, P. (2024). Automated Medicine Dispenser and Verification by YOLOv5 Models. Journal of Computer and Creative Technology, 2(2), 45–60. https://doi.org/10.14456/jcct.2024.6

Issue

Vol. 2 No. 2 (2024): Journal of Computer and Creative Technology Vol. 2 No. 2 (May - August 2024)

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Reseach Article

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