By The acquisition of smart video is now a keystone factor of modern security and surveillance activity, even as the increase of AI enable smart video is expected to make the global market for video surveillance cameras to hit close to $50 billion by 2025.
In insight presentation, Director of Product Marketing, Smart Video, at Western Digital, Brian Mallari while quoting IDC reported stated next-gen smart video technologies are increasingly being utilised in a variety of ways from medical applications, sports analysis and factories to traffic management, and even in agricultural drones.
According to him, the rise of on-camera AI chips means that AI completes real-time data analysis at the device-level in the camera, in comparison to the past when data analysis was only possible at a centralised location, such as a data centre.
He added that this increase in processing at the edge is occurring in parallel with new technological and data infrastructure advancements, such as 5G.
The Western Digital chief stated that an increase in cameras means an increase in media-rich data to be captured, analysed and used to train AI.
He disclosed that cameras can now operate as a stand-alone devices, rather than depending on a local network saying that “They can utilise direct connectivity to a centralised cloud, and load and run third-party applications with broader capabilities.”
Harping on the impact of AI, he said that new types of cameras are being developed with new types of data to be analysed, and they can be placed in more locations, including atop buildings, inside moving vehicles, in drones, and even in doorbells.
“To support these new AI workloads, the cloud has undergone a transformation. Neural network processors within the cloud have adopted the use of massive GPU clusters or custom FPGAs (field programmable gate arrays). They’re being fed thousands of hours of training video, and petabytes of data”, he said.
Stressing the role that 5G technology now plays, he said that it removes many barriers to deployment, allowing more options for where a camera can be installed and easily used. With this ease of deployment comes new greater scalability, which increases use cases and encourages further advancements in both camera and cloud design.
“As AI-enabled video develops, it’s crucial to understand how storage architectures must also change. With workloads, dynamic capabilities and deep learning analytics all increasing and evolving, data storage must be continuously innovating to support this”, he noted.
