Best practices for deploying intelligent video

Start with the right team, pick the right applications and be reasonable in expectation, says Holtenhoff


Achieving success with your intelligent video applications isn’t just about selecting the best products. Without advance planning, focusing on implementing the most appropriate applications, and evaluating deployment and management issues, you’re not likely to meet your goals. Here, then, are best practices for successfully deploying intelligent video applications.

Plan for success
First, establish an internal cross-functional team impacted by the new video system, comprised of IT, security and any other pertinent constituencies, such as operations.

Typically, IT implements, maintains and troubleshoots hardware/software/networking issues. Thus, it looks at the acquisition from a systems perspective, independent of the video applications. Meanwhile, security and other constituencies must communicate their feature and function needs with IT to ensure application needs and overall goals are met.

Once the internal team forms, it is paired with a team consisting of the vendor and integrator. The key to this partnership is trust. The customer needs to share information about its business requirements, note trouble points and discuss measurement criteria, timelines and budgets with the video manufacturer and systems integrator. The best way to ensure open and frequent communication is to schedule regular calls and meetings for brainstorming, problem solving, planning and status updates.

From this joint team, internal and vendor/system integrator groups should establish project management leads, who will give both sides a single voice to facilitate discussions and move the project forward.

Next, the joint team should develop a clear requirements statement. This is something that often does not receive the attention it deserves. First prioritize. Let’s say smash-and-grab crimes are up 20 percent, resulting in a $10 million increase in losses. If so, define the desired outcome based upon physical limitations and other barriers to success. Be wary of goals that seek perfect results. Too often organizations have been led to believe that a particular analytics application provides 99 percent accuracy when that number doesn’t reflect real-world conditions.

Expecting near perfect accuracy reflects a flawed understanding of analytics. For example, consider other helpful tools, such as email spam filters (perhaps 85 percent accurate) or even 5-day weather forecasts (maybe 75 percent). Despite their lack of perfection, we rely on both – and benefit from them. Likewise, analytics can provide tremendous benefits even if the results aren’t perfect.

As the user and as integrator, you will need to determine what level of performance is acceptable. For example, one retailer obtained 95 percent accuracy in its overhead people counting applications and noted with 80 percent accuracy how many customers lingered in front of specific retail end caps. In another case, a perimeter breach application that replaced motion detection reduced the number of false alarms from 300 to 4. Even though none of these applications was perfect, in each case the customer obtained genuine value.

The joint team should then look at system design, scope and support. Will your architecture be centralized, decentralized or even hosted? How many cameras will you place in how many sites? Will your desired solution scale across the enterprise? These are all important issues to review. Finally, figure out if the system fits within your existing video surveillance architecture and whether your IT and security departments can properly support it.

Select applications that deliver success
When evaluating applications, carefully select first those which you believe can be most successful. Consider both real-time alerts for prevention and forensics for recovery.

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