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Updating video surveillance infrastructure for IoT connectivity

There is a common saying that data is the new oil. With video footage being such a pure and rich source of information, it indeed has become a valuable commodity. However, I prefer to think of data as the new solar power, as oil is both polluting and an incredibly finite resource. The need to collect video data and store it in a more forward-thinking environment takes this analogy a bit further.

So many businesses have been built on the premise that video surveillance and CCTV is the be-all, end-all for securing a facility. Though video is critical to the goal of protecting people and assets from threats, the kind of video used and how it’s stored is important. On-premises storage for video has traditionally been accepted as the standard. However, the cloud is emerging as a more scalable and open option for businesses of all sizes.

Let’s face it: on-premises and legacy video surveillance infrastructure are still in the dark ages. Physical servers often have limited virtualization integration and support, as well as racks upon racks of servers that clog up performance regardless of whether the data center is using NVR, direct-attached storage, storage area network or hyper-converged infrastructure. It’s been that way for the last 10, if not 20, years.

In the meantime, cloud solutions have gathered and transformed IT services, revolutionized application deployment and even radically altered the way people purchase and consume IT resources with software-as-a-service (SaaS) models. It’s high time that video surveillance evolved to take advantage of these technology advances, and below are three main reasons why.

On-premises surveillance infrastructure is ill-designed

Retention times for video surveillance in most deployments is only designed for a 14, 30 or 60-day retention, unless mandated by regulations or compliance. Though this is adequate for organizations that aren’t looking to drive valuable business insights from video data, forward-thinking businesses often drive intelligence over a longer timeframe to truly understand the behaviors of their customers, business processes and staff to help improve efficiency, customer experience and business intelligence.

Organizations with limited numbers of cameras on small sites or large organizations with multiple small sites often suffer when it comes to on-premises video solutions. Buying and housing an NVR for five or six cameras is expensive and time-consuming from a management and maintenance point of view. With great improvements in connectivity, compression and data transfer methods, a cloud-native solution becomes an excellent option.

However, collating all of that video data into a centralized storage platform also presents its own challenges, especially when organizations have multiple locations spread around the world where customers will interact with organizations differently based on local customs and influences. The cloud offers an easily accessible, scalable, secure and resilient collation point for all of that video. Simple connectivity options allow data from any part of the organization to be analyzed on demand, whether on-premises or by a SaaS application.

Video analytics are rapidly moving into the cloud

There are already a number of video analytics companies that operate on a SaaS model, with more announcing cloud integrations and hosting on cloud platforms every quarter. The cost justification is simple: pay for what is used when it’s used. This means that organizations don’t have to buy expensive, GPU-laden workstations or servers to process video data.

It wouldn’t surprise me if one of the video analytic vendors took things a step further in the future, using containers or software as code to deliver a true pay-per-investigation model. Organizations would simply upload their incident or research data, charge their account and analyze their data. There would be a readily available market for an analytics storefront-type model where a talented integrator would host multiple analytics platforms in the cloud, and organizations could simply select the analytic that works best for their incident or research and pay to use that analytic tool.

Data from multiple sources enters IoT

IoT is quickly becoming a valuable asset in the augmentation of video because it can deliver actionable intelligence to physical security teams, which enhances investigations and creates a richer context when video is used for business intelligence.

IoT sensors and applications create similar volumes of metadata to video surveillance, but in an incredibly different way. Billions of data points are continually streamed in tiny packets via a collecting service and stored as a massive amount of unstructured data. The cloud is the de facto environment for IoT to operate considering a cloud environment scales seamlessly and to levels that are almost impossible to realize on-premises, both in terms of storage and data processing. Housing video alongside it will simplify management, security and integration between the two.

IoT often gets associated with the concept of edge computing, and there should be no reason to discount video surveillance from that association given that it quite neatly fits the definition for IoT. In a majority of situations, edge computing sits out at the far extremities of organizations infrastructure. I personally define edge as the location where the data first originated in whatever form and has not been altered in any fashion.

All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.

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