Abstract:
It takes a lot of time and work to manually monitor and react to unexpected occurrences that arise in a lift cab. We develop and proclaim a smart video surveillance syste...Show MoreMetadata
Abstract:
It takes a lot of time and work to manually monitor and react to unexpected occurrences that arise in a lift cab. We develop and proclaim a smart video surveillance system in this study. An identifying system for lift cars that allows data like occupancy level, human body behaviour, and the condition of the cab door to be estimated and assessed for security. According to this research, an intelligent video surveillance-based lift system should be designed to detect activity in a designated region and start capturing video only when motion is detected. A adjacent lift is similarly controlled by the system; however, it only operates when motion is detected. The system's camera records live footage of the scene, which OpenCV then processes to detect motion. The lift will activate and video recording will begin as soon as motion is detected by the device. The gadget will cease capturing video and turn off the lift if it detects no motion. The system can be used for a variety of purposes, including building, office, and home security systems. The project makes use of OpenCV, a well-known open-source computer vision library that provides a broad range of image processing and motion detection capabilities. The main objective of this project is to create a smart surveillance system that increases the area's overall security while minimizing storage requirements by only taking pictures when necessary and only running the elevator when motion is detected.
Published in: 2023 3rd International Conference on Technological Advancements in Computational Sciences (ICTACS)
Date of Conference: 01-03 November 2023
Date Added to IEEE Xplore: 25 January 2024
ISBN Information: