IP multicasting is an extremely powerful networking feature that allows video from the same camera to be efficiently viewed and recorded by multiple operators at the same time, with the same network bandwidth requirement as would be for a single operator. Using multicasting on a distributed system is an efficient solution for IP video systems.
Motion Detection Analytics
Real-time analytics running in the cameras at the network edge can be used to reduce the amount of video that is streamed across the wireless network. When a scene is inactive, there is no point in transmitting full-frame video. Motion detection analytics can be used to detect a change in motion in a scene and automatically modify the video output stream from low frame-rate to maximum.
Cameras on some IP video systems are capable of dual streaming, that is outputting two separate video streams at different frame-rates. Typically, this could be used to transmit a lower frame-rate stream across a wireless network, while using a full frame-rate stream for recording on a local NVR.
Often, IP video systems will have a set of tools for bandwidth management. These allocate bandwidth to each camera stream based on a pre-configured maximum available for a particular network setup. These tools would typically work on a WAN connection, not on the local network. In the case when the WAN connection is wireless, this can be a very useful tool for ensuring the available bandwidth is not exceeded and works well alongside features such as dual streaming, mentioned above.
The benefits of using wireless networks with IP video systems are clear and can sometimes be the only solution available for large or remote areas. However, the overall performance of the network -- and hence the surveillance system -- is very dependent on the performance, features and capability of the IP video system itself and the selected wireless technology.
About the author: Oliver Vellacott founded IndigoVision in 1994. He was previously a product manager with a background in intelligent camera products; he holds a degree in software engineering from Imperial College London and a PhD in electrical engineering from Edinburgh University.