Assistive Technology for Visually Impaired using Tensor Flow Object Detection in Raspberry Pi and Coral USB Accelerator

Amit Ghosh, Shamsul Arefeen Al Mahmud, Thajid Ibna Rouf Uday, Dewan Md. Farid

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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Abstract

Assistive Technology (AT) becomes an interesting field of research in this present era. According to the World Health Organisation (WHO - https://www.who.int), there are approximately 285 million visually impaired people around the world. To address this issue, many researchers are employing new technologies, e.g. Machine Learning (ML), Computer Vision (CV), Image Processing, etc. This paper aims to develop an assistive technology based on Computer Vision, Machine Learning and Tensor Flow to support visually impaired people. The proposed system will allow the users to navigate independently using real-time object detection and identification. Hardware implementation is done to test the performance of the system, and the performance is tracked using a monitoring server. The system is developed on Raspberry pi 4 and a dedicated server with NVIDIA Titan X graphics where Google coral USB accelerator is used to boost processing power.

Original languageEnglish
Title of host publicationProceedings of the 2020 IEEE Region 10 Symposium, TENSYMP 2020
PublisherIEEE
Pages186-189
Number of pages4
ISBN (Electronic)9781728173665
DOIs
Publication statusPublished - 5 Jun 2020
MoE publication typeA4 Article in a conference publication
EventIEEE Region 10 Symposium - Virtual, Dhaka, Bangladesh
Duration: 5 Jun 20207 Jun 2020

Conference

ConferenceIEEE Region 10 Symposium
Abbreviated titleTENSYMP
CountryBangladesh
CityDhaka
Period05/06/202007/06/2020

Keywords

  • Assistive Technology
  • Computer Vision
  • Object Detection
  • Tensor Flow
  • Visually Impaired

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