A Drug Pill Recognition System for Visually Impaired People with Voice Assistant

Authors

  • Meenakshi A. Thalor Associate Professor,AISSMS Institute of Information Technology, Maharashtra, Pune,
  • Mrunal Pathak Assistant Professor,AISSMS Institute of Information Technology, Maharashtra, Pune
  • Aamrapali Chavan Assistant Professor,AISSMS Institute of Information Technology, Maharashtra, Pune
  • Asphana Shiralkar Assistant Professor,AISSMS Institute of Information Technology, Maharashtra, Pune
  • Amita Shinde Associate Professor,AISSMS Institute of Information Technology, Maharashtra, Pune
  • Prachi Vast Assistant Professor, AISSMS College of Engineering, Pune

Keywords:

Deep learning, Drug Pill Recognition, Elderly People, Imprint, Neural Network

Abstract

The loss of faculties like eyesight or memory is a common effect of ageing, which is a natural process. Seniors who are visually impaired have more difficulty performing daily tasks, which can occasionally put them in danger. One of the most significant causes has to do with misusing medications or just forgetting to take them. Elderly people health care is prioritized because these mistakes seriously endanger lives and health. In literature many automated systems were proposed which recognize a drug pill by the imprint code i.e. the text carved on the pill but there are many drugs pill which can have same imprint code carved on them so it is necessary to consider the color, size and shape of pill too to recognize it effectively. This paper presents a drug pill recognition system which considers the pill imprint code, shape, size and color by using convolutional neural network and provides voice assistance to visually impaired people. The system's accuracy is 99%. The suggested system also prompts patients to take their medications at the appropriate times.

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Published

25.12.2023

How to Cite

Thalor, M. A. ., Pathak, M. ., Chavan, A. ., Shiralkar, A. ., Shinde, A. ., & Vast, P. . (2023). A Drug Pill Recognition System for Visually Impaired People with Voice Assistant. International Journal of Intelligent Systems and Applications in Engineering, 12(2), 42–47. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4218

Issue

Vol. 12 No. 2 (2024)

Section

Research Article

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