Medication Identification and Assistive System for the Visually Impaired: Vismed

Visual impairment poses significant challenges for individuals in independently managing their everyday activities and medication regimens.39 million people are designated as blind by the World Health Organisation (WHO), out of an estimated 285 million people who have visual impairment.Many people have to face difficulties in interpreting prescriptions, recognizing medications, and administering them properly, which can lead to serious health hazards and reduce the sense of autonomy.An innovative Artificial Intelligence (AI)--driven Blind Assistive System, VISMED has been developed to address these critical problems.This advanced system empowers visually impaired individuals to scan their prescriptions and extract medication details using Optical Character Recognition (OCR) technology by accessing a comprehensive database.It also optimizes the prescription writing process for healthcare professionals by incorporating an online prescription service and primary disease predictive model using machine learning.Furthermore, the application has a provision for emergency communication with caregivers in times of dire need.Combining these features, it seeks to significantly improve the independence, health, and overall quality of life of individuals with visual impairments.By leveraging cutting-edge technologies, this system meets the needs of the visually impaired population in terms of accessibility and healthcare management.The necessity of such a system is of supreme importance, as it improves drug safety and accuracy in medication use while encouraging greater autonomy and self-reliance among visually impaired individuals, ultimately contributing to their better state of health and increased involvement in society.

Authors

Institutions

Publication Details

Journal
International Journal of Computer Applications
Published
2024-09-26
DOI
https://doi.org/10.5120/ijca2024923958
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Medication Identification and Assistive System for the Visually Impaired: Vismed

Shibakali Gupta, Sumana Das, Surabhi Pal
International Journal of Computer Applications
Retinal Imaging and Analysis
article

Medication Identification and Assistive System for the Visually Impaired: Vismed

Shibakali Gupta, Sumana Das, Surabhi Pal
article en

Abstract

Visual impairment poses significant challenges for individuals in independently managing their everyday activities and medication regimens.39 million people are designated as blind by the World Health Organisation (WHO), out of an estimated 285 million people who have visual impairment.Many people have to face difficulties in interpreting prescriptions, recognizing medications, and administering them properly, which can lead to serious health hazards and reduce the sense of autonomy.An innovative Artificial Intelligence (AI)--driven Blind Assistive System, VISMED has been developed to address these critical problems.This advanced system empowers visually impaired individuals to scan their prescriptions and extract medication details using Optical Character Recognition (OCR) technology by accessing a comprehensive database.It also optimizes the prescription writing process for healthcare professionals by incorporating an online prescription service and primary disease predictive model using machine learning.Furthermore, the application has a provision for emergency communication with caregivers in times of dire need.Combining these features, it seeks to significantly improve the independence, health, and overall quality of life of individuals with visual impairments.By leveraging cutting-edge technologies, this system meets the needs of the visually impaired population in terms of accessibility and healthcare management.The necessity of such a system is of supreme importance, as it improves drug safety and accuracy in medication use while encouraging greater autonomy and self-reliance among visually impaired individuals, ultimately contributing to their better state of health and increased involvement in society.

International Journal of Computer ApplicationsVol. 186(38)
University of Burdwan (IN)
Openalex Percentile: Top 71%
Retinal Imaging and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.