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Book ChapterDOI

Home Surveillance System Using Internet of Things

01 Jan 2018-pp 79-85
TL;DR: The implementation of motion detection algorithm for live camera streaming is presented and thus allows analyzing incoming image stream, and recognizing any movement occurs in the area and if so then triggers video recorder to save the information-contained video clip.
Abstract: In recent years, lots of research have been done in computer vision domain. Video surveillance in real-time scenario, especially for humans, like tracking and behavior analysis is one of the most active research topics in computer vision and artificial intelligence in present situation. The main focus is providing the low-cost and efficient video surveillance system for home application and can have wide scope in other areas such as elevator monitoring and server room monitoring. As the traditional surveillance system requires huge storage capacity and consumes lot of network bandwidth, hence it becomes necessary to provide solution for such design issues. This paper presents the implementation of motion detection algorithm for live camera streaming and thus allows analyzing incoming image stream, and recognizing any movement occurs in the area and if so then triggers video recorder to save the information-contained video clip.
Citations
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Journal Article
TL;DR: In this paper, a self-adapting, automatic updating background model is trained to adapt the slow and slight changes of the environment, which can also be applied for external environmental video surveillance.
Abstract: Intelligent video surveillance systems deals with the monitoring of the real-time environment. It monitors the transient and persistent objects within a specific environment. This is not only designed for security systems and can also be applied for external environmental video surveillance. The basic background subtraction algorithm is used for the detection of moving object. A self-adapting, automatic updating background model is trained to adapt the slow and slight changes of the environment. The foreground object is detected when the subtraction of the current image and the background, which is already trained attains a threshold, the foreground moving object is considered as to be in current view. The mobile phone automatically notifies the control unit through SMS(Short Message Service)or by phone call. Background subtraction technique basically works by feature analysis, pixel differences and so on. Here for feature analysis k-nearest neighbour algorithm (k-nn) is implemented. This proposed system requires little memory and less storage space than the previous. This can be used in implementing mobile based security monitoring system.

3 citations

Journal ArticleDOI
30 May 2020
TL;DR: The BGS method was employed with fewer complications so that the approach can be utilised in a pragmatic manner where the real-time video surveillance systems (VSS) is highly needed.
Abstract: This paper illustrates the deployment of the background subtraction (BGS) approach in detecting and tracking the targeted moving objects (MOs). Through the BGS method, there is a potential of cost-saving because the process of storing data occurs once the motion is detected. The aim was to detect the MOs effectively. The applied technique is applicable at all scenarios and places that need the real-time video surveillance systems (VSS), including airports, forest, frequent entrances for criminals, traffic monitoring, country borders, cash machines, schools, banks, among other challenging outdoor and indoor areas. The concept of installing VSS is substantially much needed. The BGS method was employed with fewer complications so that the approach can be utilised in a pragmatic manner (conditions) where the VSS is highly needed. The VSS must be more convenient, effective and efficient to enhance advanced security systems. © 2020 Published by Faculty of Engineeringg

1 citations

References
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Proceedings ArticleDOI
25 May 2015
TL;DR: This paper aims to describe a security alarm system using low processing power chips using Internet of things which helps to monitor and get alarms when motion is detected and sends photos and videos to a cloud server.
Abstract: Internet of things is the communication of anything with any other thing, the communication mainly transferring of use able data, for example a sensor in a room to monitor and control the temperature. It is estimated that by 2020 there will be about 50 billion internet-enabled devices. This paper aims to describe a security alarm system using low processing power chips using Internet of things which helps to monitor and get alarms when motion is detected and sends photos and videos to a cloud server. Moreover, Internet of things based application can be used remotely to view the activity and get notifications when motion is detected. The photos and videos are sent directly to a cloud server, when the cloud is not available then the data is stored locally on the Raspberry Pi and sent when the connection resumes. Therefore, advantages like these make this application ideal for monitoring homes in absence.

101 citations

Proceedings ArticleDOI
11 May 2008
TL;DR: A real time video surveillance system consisting of many low cost sensors and a few wireless video cameras that is adaptable to variant environments and provides real time information of the monitored environment is proposed.
Abstract: One important goal of surveillance systems is to collect information about the behavior and position of interested targets in the sensing environment. These systems can be applied to many applications, such as fire emergency, surveillance system, and smart home. Recently, surveillance systems combining wireless sensor networks with video cameras have become more and more popular. In traditional video surveillance systems, the system performance and cost is proportional to the number of deployed video camera. In this paper, we propose a real time video surveillance system consisting of many low cost sensors and a few wireless video cameras. The system allows a group of cooperating sensor devices to detect and track mobile objects and to report their positions to the sink node in the wireless sensor network. Then, the sink node uses the IP cameras deployed in the sensing area to record these events and display the present situations. We also propose a camera control scheme to initialize the coverage distribution of cameras and support the inter-task handoff operations between cameras. We have implemented the proposed system with 16 sensor nodes and two IP cameras, and evaluated the system performance. The result shows that our surveillance system is adaptable to variant environments and provides real time information of the monitored environment.

88 citations

Proceedings ArticleDOI
07 Jul 2015
TL;DR: The design and implementation of a low-cost system monitoring based on Raspberry Pi, a single board computer which follows Motion Detection algorithm written in Python as a default programming environment, to significantly decrease storage usage and save investment costs are described.
Abstract: Nowadays, the Closed-Circuit Television (CCTV) surveillance system is being utilized in order to keep peace and provide security to people. There are several defects in the video surveillance system, such as: picture is indistinct, anomalies cannot be identified automatically, a lot of storage spaces are needed to save the surveillance information, and prices remain relatively high. This paper describes the design and implementation of a low-cost system monitoring based on Raspberry Pi, a single board computer which follows Motion Detection algorithm written in Python as a default programming environment. In addition, the system uses the motion detection algorithm to significantly decrease storage usage and save investment costs. The algorithm for motion detection is being implemented on Raspberry Pi, which enables live streaming camera along with detection of motion. The live video camera can be viewed from any web browser, even from mobile in real-time.

62 citations

Proceedings ArticleDOI
01 Aug 2014
TL;DR: A novel remote display solution that allows remote surveillance users to watch real-time surveillance video, to use surveillance software and to share screen updates among users on remote desktop is proposed.
Abstract: Cloud based video surveillance systems have been proposed and implemented recently. With the advances in cloud technologies, opportunity for getting on-demand remote video surveillance service can be pursued. In this paper, we propose a novel remote display solution that allows remote surveillance users to watch real-time surveillance video, to use surveillance software and to share screen updates among users on remote desktop. Multiple encoders and parallel encoding method are adopted in remote display to meet quality of service requirement under varying situations. Our proposed system deals with dynamic workload better than traditional remote display methods since surveillance task and encoding task are separately managed. Two queuing models are designed to handle resource provisioning problem for different encoders.

16 citations

Proceedings ArticleDOI
Wang Kechao1, Ren Xiangmin1, Wang Zhifei1, Jia Zongfu1, Yu Jingwei1 
10 Jun 2011
TL;DR: Test results show that the embedded network video monitoring terminal designed and implemented by this company can better utilize TCP/IP network bandwidth and can play without latency and fitter, as a result of real-time transmission and reception of digital video signal.
Abstract: Diggitalization of network video monitoring system, which has advantages of unlimited distance control, flexible extension and so on, is becoming a new standard of security system. Due to limitations of network bandwidth, video signals collected must be compressed to achieve real-time video transmission on the network. Therefore, how to maintain the high quality of the compressed signal, and meanwhile minimize the amount of data becomes a key technical problem To achieve this goal, an embedded network video monitoring terminal was designed and implemented by us This terminal consists of dedicated MPEG-4 compression ASIC, 32-bit embedded processor, 8-bit micro controller, 4-channel video capturing and decoding chips etc. Its corresponding software has been developed Users can not only watch the real-time monitoring images directly with the built-in embedded web server through the network,but also login central server, watch the monitoring images and control the network video terminal through dedicated software. Test results show that our terminal can better utilize TCP/IP network bandwidth Video can play without latency and fitter, as a result of real-time transmission and reception of digital video signal.

5 citations