Integrating video surveillance with alarm systems involves configuring the two systems to communicate and work in tandem. For instance, a motion detection event in the video software could trigger an alarm or vice versa. This creates a more robust security environment. Such integrations often require compatible hardware and software, and might sometimes need a middleware solution or custom coding.

With cutting-edge AI technology, including real-time object detection and facial recognition, you can transform your computer into a powerful security system. Traditional video surveillance systems require infrastructures including expensive servers with capabilities to process images and store video recordings. These surveillance systems produce and need to store a huge amount of data and to execute on them specific image analysis in real-time in order to detect safety events. We propose a video surveillance system based on P2P that collects multimedia streams generated by surveillance cameras, optimizes their transmissions with Scalable Video Coding (SVC) according to network condition and stores them in a cloud storage system in an efficient and secure way.