Paper Title
Enhanced Elevator Security: Advanced Intelligence Surveillance with Opencv
Article Identifiers
: Keywords
OpenCV, Surveillance, Motion Detection, Storage, Face Recognition
Abstract
Film is only recorded under the Advanced Intelligent Footage Surveillance System project when motion is detected within a predetermined area using OpenCV. Additionally, the system controls the operation of a nearby lift, which only activates in response to motion detection. The setup consists of a camera recording the environment in real time, which OpenCV then analyses to detect motion. The lift's motion detection system will trigger the lift to start recording video and start working. When it senses no more motion, the device will cut off the video recording and switch off the lift. The system has many applications, including surveillance in public areas and building security. The system monitors and analyses video feeds in real-time, aiming to enhance security and safety in elevators by employing computer vision techniques. Object detection, real-time video capture, and tracking algorithms specifically designed for the unique dynamics of lift spaces are crucial components. The main functions of the system are to monitor and identify individuals coming into and going out of elevators, monitor any strange activity, and use facial recognition technology to provide access control when required. Anomaly detection algorithms are also employed to identify emergencies or unusual activities.
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How To Cite (APA)
R Jegadeesan, R.Rupa, A. Prasanna, J. Nagaraju, & K.Suryadev Patel, G.Pranavi (May-2024). Enhanced Elevator Security: Advanced Intelligence Surveillance with Opencv. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(5), h46-h53. https://ijnrd.org/papers/IJNRD2405723.pdf
Issue
Volume 9 Issue 5, May-2024
Pages : h46-h53
Other Publication Details
Paper Reg. ID: IJNRD_222561
Published Paper Id: IJNRD2405723
Downloads: 000122257
Research Area: Engineering
Author Type: Indian Author
Country: -, -, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2405723.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405723
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