International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 05 | May 2023
p-ISSN: 2395-0072
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Advanced Intelligent Video Surveillance System In Elevators By Using OpenCV AKSHAY VANAPARTHI1, ANUSHA RASAMSETTY2, SIDHARTH REDDY CHAMAKURA3, DHEERAJ SUNDARAGIRI4 1, 2, 3 B. Tech Scholars, Department of Computer Science and Engineering, SNIST, Hyderabad-501301, India 4 Assistant Professor, Department of Computer Science and Engineering, SNIST, Hyderabad-501301, India
---------------------------------------------------------------------***--------------------------------------------------------------------the actual environment to generate information that can be Abstract - It takes a lot of time and effort to manually
described as numbers or symbols, such as judgments. These techniques are all part of the study of computer vision. Realtime computer vision is the primary goal of a set of programming functions known as OpenCV, which stands for open-source computer vision. Intel was the company that came up with the idea first. The collection is available on several platforms and may be accessed by anybody at no cost.
monitor unexpected occurrences that happen in an elevator cab and react in time. In this research, we create a smart video surveillance system and declare. Identification system for elevator cabs that allows for the estimation and security evaluation of information such as the condition of the cab door, human body behavior, and the number of occupants.
Our project called the Advanced Intelligent Video Surveillance System uses OpenCV to detect motion in a certain region and only starts recording video when motion is found. The system further manages the functioning of an elevator in the same location, which only operates when motion is detected. The system uses a camera to record live video of the scene, which is then processed using OpenCV to look for motion. The device will begin capturing video and turn on the elevator when motion is detected. The device will cease capturing video and disable the elevator when motion is no longer being detected. The system may be applied to many different things, such as home, office, and building security systems. The project uses OpenCV, a well-known open-source computer vision library that offers a robust collection of capabilities for image processing and motion detection. The major goal of this project is to develop an intelligent surveillance system that improves the overall security of the area while conserving storage space by only recording when necessary and only operating the elevator when motion is detected.
Traditional video surveillance systems do not permit for a prompt response in the event that a criminal act is in progress. Setting up a system similar to this one is not only fairly costly but also pretty difficult. This project's objective is to develop an intelligent open-source tool that is capable of assisting individuals in need. people or organizations in the process of independently constructing a reliable and cost-effective system They will, as a result, have complete control over their technology, which will provide them the opportunity to lock down the configurations and adjust them so that they are more suitable for their needs. It is imperative that our homes, places of employment, and any other business venues that we frequent be adequately protected from criminal activity. Standard surveillance technology is unable to alert property owners to any illegal behaviour that may be taking place on their premises. The feed is the sole item that is transferred and captured in this process. As a direct consequence of this, the owners are unable to take immediate action to prevent a break-in or theft.
Key Words: Surveillance, OpenCV, Motion Detection, Face Recognition, Storage
Motion detection is a characteristic that can be found in many contemporary elevator systems. This helps to increase both safety and the energy efficiency of the system. We propose in this project to use OpenCV and Haar cascade classifiers to identify motion in real-time video streams coming from security cameras that have been placed in elevators. These cameras will be located in different buildings. The device will call the elevator to your floor and begin recording the video as soon as it senses motion in the room. After then, the video that was taken can be put to use for purposes of security and surveillance. The Haar cascade classifier is used to a video stream in order to identify motion by monitoring variations in the pixel values of the stream. It is possible to expand the capabilities of the system
1. INTRODUCTION One of the many issues that are studied in the extremely broad scientific discipline known as computer vision is the potential application of computers to extract significant insights from digital images or movies. This is only one of the numerous topics that are discussed. From an engineering point of view, the goal is to develop automated processes that are equivalent to those that the human visual system is capable of completing. Computer vision is the study of strategies for acquiring photos, processing those photographs, interpreting those photographs as digital images, and extracting high-dimensional information from
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