Medicine Identification Application for Visually Impaired People Using Images in Machine Learning

Medicine Identification Application for Visually Impaired People Using Images in Machine Learning

Omkar Yadav,  Ajinkya Deshmane, Sarthak Ranawade, Tanuja Waghmode, Prateeksha Chouksey

Department of Computer Engineering, Genba Sopanrao Moze College of Engineering, Pune, Maharashtra, India

ABSTRACT—Mobile devices have become one of the most widely used consumer products as a result of the development of new technology. Modern life is very dependent on mobile phones. Many of us have a constant need to call or send messages. For physically challenged and blind persons, the issue is more visible, but it also affects many others, such as when driving or using a smartphone in direct sunlight. Due to subpar prescriptions, bad design, inadequate user support, and impracticality, the majority of mobile pharmaceutical apps created in Thailand for visually impaired persons fall short of the needed standard; as a result, visually impaired individuals are unable to utilise them. The restricted usage of this technology in basic healthcare services serves as the driving force behind this project, which aims to make it possible for persons with disabilities to obtain useful digital health information. When non-visual engagement is necessary, sighted users frequently find them to be inescapable. Android app "Be My Eyes" enables voice commands. The visually impaired are the target audience for the application. Your reference to the Android app "Be My Eyes" is a great illustration of how technology can be used to improve the accessibility of digital health information and other services for people who are blind or visually impaired. The software addresses the difficulties that visually impaired users encounter when using mobile devices and accessing information by incorporating voice commands and non-visual interaction.

Keywords – mobile device, Android app, visually impaired persons, digital health, healthcare services,