Research Article
Deep Learning Based Smart Survilance Robot
@INPROCEEDINGS{10.4108/eai.16-5-2020.2304191, author={Dr Vithya Ganesan and Smritilekha Das and Tamal Kumar Kundu and J Naren and S. Nikkath Bushra}, title={Deep Learning Based Smart Survilance Robot}, proceedings={Proceedings of the First International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India}, publisher={EAI}, proceedings_a={ICASISET}, year={2021}, month={1}, keywords={surveillance robot aws rekognition aws kinesis}, doi={10.4108/eai.16-5-2020.2304191} }- Dr Vithya Ganesan
Smritilekha Das
Tamal Kumar Kundu
J Naren
S. Nikkath Bushra
Year: 2021
Deep Learning Based Smart Survilance Robot
ICASISET
EAI
DOI: 10.4108/eai.16-5-2020.2304191
Abstract
Surveillance Robot aims to blend IoT capabilities with the support of cloud and machine learning is an advancement to deliver a sophisticated solution for real time security. Industrial and commercial surveillance data security is required for small camera as well as large scale deployment with a drones or robot cars. This paper deals with face recognition using AWS Rekognition and video streaming using AWS kinesis and AWS SNS(Simple notification Service) . AWS Rekognition uses deep learning algorithms to introspect the video stream and find objects / faces on them and compare it with the collection of information that it has trained previously. It detects face with video feed and scans the database to identify the person with AWS Rekognition ,there is also an option of adding new faces by uploading photo of the person to an S3 bucket and face can be indexed.
