nanoll extt
Please use this identifier to cite or link to this item: http://lrcdrs.bennett.edu.in:80/handle/123456789/771
Full metadata record
DC FieldValueLanguage
dc.contributor.authorManjari, Kanak-
dc.contributor.authorVerma, Madhushi-
dc.contributor.authorSingal, Gaurav-
dc.date.accessioned2023-03-31T03:50:02Z-
dc.date.available2023-03-31T03:50:02Z-
dc.date.issued2019-11-
dc.identifier.isbn9781728156866-
dc.identifier.urihttp://doi.org/10.1109/SITIS.2019.00049-
dc.identifier.urihttp://lrcdrs.bennett.edu.in:80/handle/123456789/771-
dc.description.abstractIn the era of technological advancements, where humans are leveraging it in every sector, it will be highly unfair for the visually impaired to be left off. Hence, this research of developing a compact computational constrained travel aid to help them easily tackle the daily practice is a necessity. As there are approximately 1.3 billion visually impaired people, having a low-cost solution for them is an important requirement. To match this condition, we have used raspberry pi 3 and pi 4 tagged with the pi camera and sonar sensor, all of which are budget-friendly and serves our purpose. This system is attached to a cane and notifies the user about the nature and range of object with the help of sonar sensor and images captured from the pi camera. We have used the lighter versions of You Only Look Once (YOLO) and Single Shot Multibox Detector (SSD) model that has been deployed on both raspberry pi 3 and pi 4. The performance of both versions of raspberry with different models has been tested in an outdoor scenario. It has been observed that raspberry pi 4 is twice faster than pi 3 and the overall performance of Tiny YOLOv3 (Model2) is best in comparison to other models on both pi 3 and pi 4. © 2019 IEEE.en_US
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.subjectCompact Computing; Object Detection; Raspberry Pi; Sensors; SSD; Travel Aid; YOLOen_US
dc.titleCREATION: Computational constRained travEl aid for objecT detection in outdoor eNvironmenten_US
dc.typeArticleen_US
dc.indexedscen_US
Appears in Collections:Conference Proceedings_ SCSET

Files in This Item:
File Description SizeFormat 
269-CREATION.pdf
  Restricted Access
1.35 MBAdobe PDFView/Open Request a copy

Contact admin for Full-Text

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