Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1134
Title: Machine Learning-Based Smart Shopping for Visually Impaired
Authors: Nagenthiran, N.
Priyanha, P.
Nirosha, S.
Vivek, J.
De Silva, H.
Sriyaratna, D.
Keywords: e-commerce
technology
accessibility
location- based
voice navigation
analysis
Issue Date: 9-Dec-2021
Publisher: 2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT
Abstract: There are diverse applications built for the e- commerce platform, each with its own set of advantages. All goods should be relevant to all members of society around the world, but there are people with unique needs who should be considered when technology advancements are made for the common good. People who are blind require particular attention since they require assistance from others. For this research, we referred to several studies with comparable goals and approaches, which our group closely examined to enhance our study and outcomes, and which were highlighted when relevant work was discussed. The purpose of this study is to provide accessibility for all members of society, including the blind, as well as location-based solutions for consumers. These include voice navigation through the app, product suggestions, offering quick paths to the shop location by comparing existing algorithms for identifying short paths and providing a function to give voice feedback. This paper thoroughly examined the findings and provided appropriate evidence to support the answer to the challenge mentioned above. This sort of research will have a beneficial influence on our IT companies' consideration for those who live with specific needs that technology may help them meet.
URI: http://rda.sliit.lk/handle/123456789/1134
ISSN: 978-1-6654-0862-2/21
Appears in Collections:3rd International Conference on Advancements in Computing (ICAC) | 2021

Files in This Item:
File Description SizeFormat 
Machine_Learning-Based_Smart_Shopping_for_Visually_Impaired.pdf
  Until 2050-12-31
3.52 MBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.