Based Embedded System Applications in Intelligent Home Remote Monitoring

2014 ◽  
Vol 602-605 ◽  
pp. 2317-2320
Author(s):  
Yang Li ◽  
Qing Hong Wu ◽  
Xue Xiao
Keyword(s):  
Embedded System ◽  
Video Surveillance ◽  
Surveillance System ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Video Capture ◽  
Home Video ◽  
Intelligent Home ◽  
Front End ◽  
Usb Camera

With the continuous improvement of security awareness, home security has become the focus of attention. The actual demand for home video surveillance system, designed a cheap, practical, small size and low power consumption of video surveillance systems, this paper uses microprocessor S3C2440 ARM9 core as the core hardware control, embedded Linux operating system with software the control core, and cheap, generic USB camera video capture device as a front end to complete the design of a home video surveillance system.

scholarly journals Secure Video Surveillance Framework in Smart City

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4419
Author(s):  
Hao Li ◽  
Tianhao Xiezhang ◽  
Cheng Yang ◽  
Lianbing Deng ◽  
Peng Yi
Keyword(s):  
Video Surveillance ◽  
Smart City ◽  
Key Management ◽  
Surveillance System ◽  
Chinese Remainder Theorem ◽  
Smart Cities ◽  
Group Key Management ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Key Update

In the construction process of smart cities, more and more video surveillance systems have been deployed for traffic, office buildings, shopping malls, and families. Thus, the security of video surveillance systems has attracted more attention. At present, many researchers focus on how to select the region of interest (RoI) accurately and then realize privacy protection in videos by selective encryption. However, relatively few researchers focus on building a security framework by analyzing the security of a video surveillance system from the system and data life cycle. By analyzing the surveillance video protection and the attack surface of a video surveillance system in a smart city, we constructed a secure surveillance framework in this manuscript. In the secure framework, a secure video surveillance model is proposed, and a secure authentication protocol that can resist man-in-the-middle attacks (MITM) and replay attacks is implemented. For the management of the video encryption key, we introduced the Chinese remainder theorem (CRT) on the basis of group key management to provide an efficient and secure key update. In addition, we built a decryption suite based on transparent encryption to ensure the security of the decryption environment. The security analysis proved that our system can guarantee the forward and backward security of the key update. In the experiment environment, the average decryption speed of our system can reach 91.47 Mb/s, which can meet the real-time requirement of practical applications.

Video Surveillance

2015 ◽  
pp. 69-92 ◽  
Author(s):  
Qasim Mahmood Rajpoot ◽  
Christian Damsgaard Jensen
Keyword(s):  
Video Surveillance ◽  
Surveillance System ◽  
Negative Impact ◽  
Developed Countries ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Security Threats ◽  
Privacy Requirements ◽  
Privacy Issues ◽  
Legal Infrastructure

Pervasive usage of video surveillance is rapidly increasing in developed countries. Continuous security threats to public safety demand use of such systems. Contemporary video surveillance systems offer advanced functionalities which threaten the privacy of those recorded in the video. There is a need to balance the usage of video surveillance against its negative impact on privacy. This chapter aims to highlight the privacy issues in video surveillance and provides a model to help identify the privacy requirements in a video surveillance system. The authors make a step in the direction of investigating the existing legal infrastructure for ensuring privacy in video surveillance and suggest guidelines in order to help those who want to deploy video surveillance while least compromising the privacy of people and complying with legal infrastructure.

scholarly journals A deep learning approach to building an intelligent video surveillance system

2020 ◽  
Author(s):  
Jie Xu
Keyword(s):  
Face Recognition ◽  
Object Detection ◽  
Video Surveillance ◽  
Surveillance System ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Single Shot ◽  
Convolutional Networks ◽  
Starting Point ◽  
Intelligent Video Surveillance System

Abstract Recent advances in the field of object detection and face recognition have made it possible to develop practical video surveillance systems with embedded object detection and face recognition functionalities that are accurate and fast enough for commercial uses. In this paper, we compare some of the latest approaches to object detection and face recognition and provide reasons why they may or may not be amongst the best to be used in video surveillance applications in terms of both accuracy and speed. It is discovered that Faster R-CNN with Inception ResNet V2 is able to achieve some of the best accuracies while maintaining real-time rates. Single Shot Detector (SSD) with MobileNet, on the other hand, is incredibly fast and still accurate enough for most applications. As for face recognition, FaceNet with Multi-task Cascaded Convolutional Networks (MTCNN) achieves higher accuracy than advances such as DeepFace and DeepID2+ while being faster. An end-to-end video surveillance system is also proposed which could be used as a starting point for more complex systems. Various experiments have also been attempted on trained models with observations explained in detail. We finish by discussing video object detection and video salient object detection approaches which could potentially be used as future improvements to the proposed system.

Low-Cost Scalable Home Video Surveillance System

2014 ◽  
Vol 19 (2-3) ◽  
pp. 51-58
Author(s):  
Jaromir Przybylo ◽  
Joanna Grabska-Chrzastowska ◽  
Przemyslaw Korohoda
Keyword(s):  
Video Surveillance ◽  
Video Processing ◽  
Surveillance System ◽  
Low Cost ◽  
Video Recording ◽  
Video Surveillance System ◽  
Threat Detection ◽  
Computing Power ◽  
Home Video ◽  
Depth Analysis

Abstract Automated and intelligent video processing and analysis systems are becoming increasingly popular in video surveillance. Such systems must meet a number of requirements, such as threat detection and real-time video recording. Furthermore, they cannot be expensive and must not consume too much energy because they have to operate continuously. The work presented here focuses on building a home video surveillance system matching the household budget and possibly making use of hardware available in the house. Also, it must provide basic functionality (such as video recording and detecting threats) all the time, and allow for a more in-depth analysis when more computing power be available.

An Intelligent Video Surveillance System for Android Smart Phone

2013 ◽  
Vol 850-851 ◽  
pp. 884-888 ◽  
Author(s):  
Gang Yang ◽  
Xin Tan ◽  
Yong Rui Zhang
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Surveillance System ◽  
Smart Phone ◽  
Image Data ◽  
Gaussian Mixture ◽  
Moving Object ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Surveillance Technology

Video surveillance technology is playing an important role, and it is widely used in some fields. With the popularity of Android OS, it draws researchers attention to increase the development of video surveillance systems on the platform. This paper presents a smart real-time video surveillance system based on Android smart phone. This system detects moving object by using improved GMM (Gaussian Mixture Mode) algorithm, recognizes invading human with cascade classifier, processes image data with coder & decoder, transmits data over RTP (Real-time Transport Protocol). It also applies some methods to improve the accuracy of moving object detection and recognition, speed up recognition process. The experimental evidences show that it can realize real-time video surveillance and smart alarm.

Human Detection by Surveillance Camera

2018 ◽  
Vol 6 (1) ◽  
pp. 21-33
Author(s):  
Larbi Guezouli ◽  
Hanane Boukhetache ◽  
Imene Kebi
Keyword(s):  
Video Surveillance ◽  
Surveillance System ◽  
Video Sequence ◽  
Rapid Development ◽  
Human Detection ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Considerable Time ◽  
Surveillance Camera ◽  
Analytical Tools

Security problems and decreasing costs, leads to the rapid development of video surveillance systems. It is necessary to implement analytical tools capable of identifying objects that may appear in the video sequence. The work presented in this article consists of designing a video surveillance system for the automatic detection of humans in a video sequence acquired by a fixed camera. The principle of this work is based on the modeling and subtraction of the background. In order to determine the nature of the objects, the authors make the detection of the contours of the foreground image, then by matching this contour with the images of a base, silhouette images of people in different positions. The acquisition of the frames is carried out in real time, the matching of the images takes a considerable time and this time becomes increasingly longer based on the size of the base. To solve this problem, the authors have used the parallelism.

Design and Implementation of a Prototype Cloud Video Surveillance System

2014 ◽  
Vol 18 (1) ◽  
pp. 40-47 ◽  
Author(s):  
Yong-Hua Xiong ◽  
◽  
Shao-Yun Wan ◽  
Yong He ◽  
Dan Su
Keyword(s):  
Cloud Computing ◽  
Video Surveillance ◽  
Surveillance System ◽  
Distributed Storage ◽  
Video Data ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Campus Network ◽  
Design And Implementation ◽  
Cloud Computing Service

Cloud-based video surveillance systems, as a new cloud computing service model, are an emerging research topic, both at home and abroad. Current research is mainly focused on exploring applications of the system. This paper proposes a design and implementation method for cloud-based video surveillance systems using the characteristics of cloud computing, such as parallel computing, large storage space, and easy expandability. The system architecture and function modules are built, and a prototype cloud-based video surveillance system is established in a campus network using key technologies, including virtual machine task access control, video-data distributed storage, and database-active communicationmethods. Using the system, the user is able to place a webcam in a location that requires monitoring so that video surveillance can be achieved, and video data can be viewed through a browser. The system has the following advantages: low investment and maintenance cost, high portability, easily extendable, superior data security, and excellent sharing. As a private cloud server in the campus network, the system is able to not only provide convenient video surveillance services, but it can also be an excellent practical experimental platform for cloud computing-related research, which carries outstanding application value.

Research of Intelligent Video Surveillance System Based on the 3G Technology

2012 ◽  
Vol 614-615 ◽  
pp. 1377-1380
Author(s):  
Yong Li Ma
Keyword(s):  
Embedded System ◽  
Video Surveillance ◽  
Surveillance System ◽  
Video Data ◽  
Video Surveillance System ◽  
Intelligent Video Surveillance ◽  
3G Network ◽  
Intelligent Video Surveillance System ◽  
The Embedded System ◽  
Remote Viewing

Face to the questions in the traditional video monitoring system, this paper proposed the intelligent video surveillance system based on the 3G technology, developed by the embedded system. The system can realize the information transmitted through the 3G network. And the system has the function of remote real-time audio monitoring, remote viewing and download the video data acquisition, and message security alarm.

Design and Implementation of an Intelligent Video Surveillance System Based on Android Phone

2013 ◽  
Vol 816-817 ◽  
pp. 1126-1130 ◽  
Author(s):  
Yu Xin Zhang ◽  
Fu Quan Li ◽  
Xi Tao ◽  
Guo Yu Lin
Keyword(s):  
Video Surveillance ◽  
Surveillance System ◽  
Detection Algorithm ◽  
Video Surveillance System ◽  
Intelligent Video Surveillance ◽  
Traditional System ◽  
Design And Implementation ◽  
Front End ◽  
Intelligent Video Surveillance System ◽  
Traditional Surveillance

This paper proposes a new intelligent video surveillance system based on Android phone. By using Android phone, this system can be deployed easily and quickly. Compare with the traditional surveillance system, this new one uses Android phone to replace the large and expensive surveillance cameras. In addition, the functions of back-end equipment of the traditional system have been moved to the front-end equipment. With a modified invasion detection algorithm, the front-end equipment becomes more intelligent. This schema can significantly increase the mobility and flexibility of the entire system. Therefore this system will have a better performance dealing with emergencies in different surveillance scenarios. Moreover, this state-of-art intelligent video surveillance system not only brings a new method for surveillance, but also advances the development of surveillance techniques.

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