Home intrusion: smart security and live video surveillance system

Abstract Security concerns are rampant in our world today. No location is immune to crime, whether it be public spaces, commercial areas, offices, or private property. While law enforcement agencies work to address crimes after they have taken place, there is no guarantee that they can prevent them from occurring. Communities and businesses often turn to security personnel and surveillance cameras to keep watch, but this only provides passive protection. Criminals may act while security is absent and cameras only record events, they do not prevent them. Although, there are few systems with face recognition and alerting mechanisms are existing, they are too expensive and not affordable to a common man. In response to this challenge, this work proposes a most economic, hassle free proactive home security system which can be used as a plug and play device for the already installed surveillance system employing CCTV cameras. This system features facial recognition technology, enabling it to identify authorized individuals by storing their images in a database, thus swiftly distinguishing between intruders and residents. In cases of unauthorized intrusions, the system promptly activates alerts and alarms. Additionally, it incorporates supplementary security measures utilizing sensors and actuators for heightened protection. Moreover, the system utilizes an IP camera, permitting remote monitoring via live streaming. An array of machine learning algorithms is assessed to ascertain the most effective method for facial recognition, integrated into a monitoring dashboard using RTSP streaming.