The surveillance industry is undergoing a transformation and the effect is being felt by all industries. New camera technology, increasing data retention times and more advanced analytics are combining to render traditional surveillance infrastructures too costly and ineffective. And while this may put pressure on current surveillance architectures, the upside is incredible, especially for forward-thinking companies seeking more from their surveillance solution than just improved security.
Moving Beyond Surveillance Images to Video-Based Data
Surveillance solutions – once considered specialized and kept isolated from other parts of IT – are now becoming more integrated. Cameras are being deployed onto IT networks, and as such, coming under more traditional IT discipline. That fact, along with the dramatic increase in data being stored and managed, has captured the attention of more than security professionals.
As video analytics applications become more feature-rich and sophisticated, non-traditional business units are taking notice that video—when integrated and correlated with data from other systems—can be used to make better business decisions. For example, logistics companies are using video data to track cargo through ports and rail yards to improve efficiency. Retail companies are using video to observe shopper behavior to make better decisions regarding product placement, store layout and advertising.
Building from a Solid Foundation
The combination of more high-definition cameras, the integration of video with other systems and data elements—such as audio data, metadata tagging, access control information, and proximity sensors—and the size and volume of data assets being stored and managed is forcing the system architecture to change. For example, with all these changes, a network video recorder (NVR) that may have been able to support 100 cameras in the past may only be able to support 20 cameras in the future. Adding more servers to keep up can quickly become expensive and difficult to manage. Something must change and it begins with storage.
A surveillance infrastructure capable of delivering maximum business value rests on a firm foundation of “intelligent” storage. As more cameras are deployed and the business use for video data becomes more wide-spread, performance matters. The storage infrastructure must be capable of handling input from thousands of cameras without dropping frames, as well as deliver excellent response time for analytics and PSIM applications.
As budgets tighten or remain flat, controlling cost is vital. More money will need to be spent on adding and upgrading cameras; therefore, less will be available for other components of the infrastructure. To minimize storage costs, the storage management system must keep content at the most cost-efficient medium of storage, as well as manage the movement of the data according to policy-based criteria. High priority, frequently-used files should be stored on high-performance disk while lower priority files should be stored on tape or in the cloud.
Strive for a Multi-Tiered Architecture with a Single File System View
Implementing a multi-tiered, intelligent storage infrastructure is the best approach to managing video data. A tiered architecture consisting of high performance disk, secondary disk, tape, and cloud storage viewed as a single file system allows video files to be cost-effectively retained for a long time and to be retrieved quickly and easily for analysis when needed, because the system manages the movement of the data between tiers and the metadata remains intact.
As I mentioned before, the surveillance industry is changing. Camera counts are increasing, video files are getting larger as higher definition cameras are deployed, data retention times are going up, and real-time analytics are becoming more sophisticated. Meeting the storage needs of this changing industry requires a storage infrastructure that is high performing, scalable, and multi-tiered in order to protect people and property from harm and to derive maximum business value from video-based data.
Originally published on Security Info Watch