Considering video analytics? Where to start

Video analytics applications are becoming ever more popular, as they can save costs, add valuable insights and drastically reduce workloads. So, if you are considering using analytics, where do you start?

Broadly speaking, there are two categories for implementing video analytics: centralized and distributed. In centralized architectures, video and other information is collected by cameras and sensors in the network and then brought to a centralized server for analysis. The very first video analytics applications in analog video networks followed this setup – there was simply no other way of processing the video stream. All the recordings from all the cameras had to be transferred to one central processing device. This meant many hours of video – often with no interesting content – had to be sent and stored, clogging up network and servers.

Today, distributed architectures are possible, with clever edge devices (network cameras and video encoders) that are already capable of processing the video data and extracting relevant information themselves.

The most scalable, cost-effective and flexible architecture is based on this ‘intelligence at the edge’ principle. It entails the least amount of bandwidth usage since the cameras can figure out what video needs to be sent over the network for further analysis or action, and what can be deleted or stored for future use. This significantly reduces the cost and complexity of the network, and eliminates the drawbacks of centralized architectures. Servers that typically processed only a few video streams when doing the entire video processing can now handle hundreds of video streams if some of the work is done in the cameras.

Here are some key considerations when designing a video system with analytics:

  • Reliability and system availability – minimizing the risk of system failure and associated down-time
  • Scalability and flexibility – the ability to effortlessly scale the system from a few to many cameras, as well as intelligently distribute processing across the network
  • Interoperability – the ability to use system components and applications from different vendors
  • Security – making sure that only authorized personnel are allowed to access the system
  • Total cost of ownership (TCO) – this includes capital costs for the system components and operational expenses

There are already a large number of network cameras and analytics applications to suit a whole range of requirements, and the market is growing fast. By integrating intelligent edge devices with video management systems and dividing the load between the different parts of the network, video analytics solutions can be created that scale effortlessly, are more flexible, and cost-effective than centralized solutions.

For more information about video analytics, read this web article.