Design And Implementation Of Intelligent Home Monitoring System

With the development of embedded technology and the rise of Internet of Things,intelligent home has been accepted by more and more people.More and more people are willing to monitor and control the home through the Internet by mobile phones or host devices.However,more network bandwidth and stronger video compression capability are needed to complete the transmission because of the large volume of video data.Therefore,the low-end and low-cost hardware platforms can not be purchased to implement the video monitoring system,so the hardware costs are relatively high.In addition early traditional video surveillance can not remotely watch the home situation anytime,only video recording.In short,the price factor and labor costs are one of the main factors restricting the development of home monitoring system.If the network transmission problem,video quality problems and hardware price issues can be solved,smart home is promoted in the ordinary family.This paper is aimed at the above-mentioned problems,and designs a home monitoring system to meet the needs of growing household monitoring.The home monitoring system is designed to be open source and easy to implement.The starting point of this system is to reduce the hardware cost by software such as network connection,video compression and other functions.And by vedio image analysis,the storage cost is saved by storing the dynamic video,and the intelligent intrusion detection is carried out through face detection,which is excluded from inhuman intrusion alarm,thereby reducing labor costs and false alarm rate.The completed content includes the following sections:1.Build video front-end platform based on the Linux operating system with arm development board and single-chip,including the transplantation of embedded Linux operating system and U-Boot(universal bootloader),and the support of iFi connection.2.Design and implement a network video server based on CS(Client Server) etwork connection with TCP,which support for common video compression oding.3.Develop an application which can watch the home vedio in real-time and rec- ord the video.4.Implement motion detection,face recognition and other intelligent monitoring and control based on OpenCV(open source computer vision library).The front end of the video uses OpenCV to capture the video,and the back end(client) uses OpenCV for face recognition.