Object Surveillance Detection

Abstract

Abstract: Thefts have increased over the past few years. This creates a dangerous climate where people live in fear. Issues with home security are a worry in the current atmosphere. The current generation of intrusion detection systems is very expensive and prone to false alarms. Open CV and mobile devices are used to find a solution to this issue. Intruders can be precisely detected using this framework, which filters the motion of moving objects. An API by the name of Twilio will notify the user when an intrusion is made, and the video will be saved locally. This application's main purpose is to act as a surveillance system that can identify persons, recognise faces, and display user information. This lowers the possibility of future system penetration by people. This project gathers camera photos and using image comparison methods to identify intruders using the Open CV library. The streamed video will be delivered from the server to the remote administrator via the Android phone if an intrusion is found after comparison. The administrator can then take the necessary steps and locally notify her security. Users are notified by MMS, SMS, or email when notifications are sent and pertinent data is recorded. able to display videos relevant to the user. This approach improves social stability, keeps your house secure, and lowers burglaries.