Deployment of Computer Vision Application on Edge Platform
| dc.contributor.author | Geetha, V. | |
| dc.contributor.author | Kiran, C. | |
| dc.contributor.author | Sharma, M. | |
| dc.contributor.author | Rakshith Kumar, J. | |
| dc.date.accessioned | 2026-02-06T06:36:05Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | In our work, we propose a low cost device which will aid visually impaired people to understand what is in their surroundings without the requirement of internet. Current technology makes use of Cloud Architecture and would require internet to achieve this purpose. But these systems will not work in areas with poor internet connectivity. Edge platform built on Raspberry Pi powered with Intel Neural Compute Stick is used by us for this purpose. Multi Label Image Classification Deep Learning Model is trained in the cloud. It is later optimised and deployed on Edge Device which is Raspberry Pi. Setup also consists of PiCamera which will record the video and give it as input to deployed model. Model will describe the items present in video, basically describing the surroundings. The output is in the form of audio which is played through speakers, thus enabling visually impaired people to understand their surroundings without the requirement of internet. Deployment of popular Machine Learning and Deep Learning Models is also examined in the edge device and a comprehensive performance evaluation is performed. © 2021 IEEE. | |
| dc.identifier.citation | Proceedings of the 2021 IEEE 18th India Council International Conference, INDICON 2021, 2021, Vol., , p. - | |
| dc.identifier.uri | https://doi.org/10.1109/INDICON52576.2021.9691632 | |
| dc.identifier.uri | https://idr.nitk.ac.in/handle/123456789/30213 | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.subject | Computer Vision | |
| dc.subject | Deep Learning | |
| dc.subject | Edge Devices | |
| dc.subject | Internet of Things | |
| dc.subject | Neural Compute Stick | |
| dc.subject | Raspberry Pi | |
| dc.title | Deployment of Computer Vision Application on Edge Platform |
