


Volume 20 No 20 (2022)
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REAL TIME SURVEILLANCE USING DEEPLEARNING
Mr. DHANUSH MUNAGALA , Miss. A NARMADA
Abstract
Basic capabilities like video recording and archiving
are all that traditional video surveillance offers. It
cannot distinguish between approved and
unauthorised faces. A vital component of
contemporary cities' security and defence systems is
video surveillance, thanks to the rapid growth of
information technology. Particularly prevalent and
important in the current world are surveillance
cameras, which are almost everywhere. But as the
monitoring network continues to grow, more and
more people are using surveillance cameras, which
not only make life easier but also produce a huge
quantity of data that is difficult to store, analyse, and
retrieve. Both authorised and illegal people may be
seen by an intelligent surveillance system using
intelligent video analysis technologies. In this
research, we can distinguish between approved and
unauthorised persons by applying deep learning
algorithm approaches to identify people filmed using
camera module. The individual in the video is
recognised and recorded using convolutional neural
networks (CNN), and the security team will instantly
get an email notice with a picture of the unauthorised
person if they enter prohibited places.
Keywords
Surveillance, DeepLearning,FaceRecognition,CNN,Monitoring
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