Automated Medicine Dispenser and Verification by YOLOv5 Models
DOI:
https://doi.org/10.14456/jcct.2024.6Keywords:
Automated Medicine, Dispenser and Verification, YOLOv5 ModelsAbstract
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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