Each time I hear about a break-in, theft, or other physical security incidents at a facility these days, I think of one of my dad’s most-loved analogies. “The time to discover you need a plunger isn’t when the toilet’s overflowing.” Crass, yes. But so true, isn’t it? As one of nine kids, remembering this colorful adage saved me a lot of grief throughout my childhood. It still does. And now I can’t help wondering, with all that’s on the line, why aren’t more enterprises or government organizations taking a more proactive approach to physical and cybersecurity?
Let’s look at video security. Most companies and government agencies have video security products. That’s not the problem. The problem is that many get lulled into a false sense of security simply because they’ve installed security cameras. This mindset misses a major piece of the prevention puzzle. Video security without analytics to provide the critical insight needed to act—rather than just record incidents—is like being without that plunger.
I’m referring to machine learning-powered security that can capture, analyze, and make sense of loads of unstructured data picked up by cameras and thrust upon security professionals every day. Frustrated operators aren’t getting the right data at the right time, even when bad incidents may actually be happening.
Before taking—forgive me—the plunge into smart detection, you should be aware of a few key things. First, go with a video security solution that can be used with most of your existing cameras. Imagine plug and play perimeter detection leveraging analytics! Overnight, your organization will be more proactive, increasing the value of previous video surveillance investments.
Second, video analytics technology has been changing fast. AI enables software to ‘learn’ what is considered normal and what isn’t for your organization. Through machine learning algorithms, raw video content is converted into meaningful actionable intelligence and enhanced situational awareness. Ava Aware, our intelligent video management system (VMS) (formerly Vaion vcore), for example, detects, identifies, extracts, and catalogs input like object type, appearance, and similarity.
Then it adds behavioral detection factors like dwell times, line crossings, vehicles in no-cross zones, or persons in sensitive areas. Combined with directional sound analytics on glass breaking, screams, and gunshot, operators only get alerts on what really matters. And when analytics analyze all your cameras, you get a complete picture because they help inform YOU what needs attention.
It’s not every day I share my Dad’s pearls of wisdom, but as COVID-19 upends just about everything, moving toward proactive security to protect your organization’s assets and people seems all the wiser. Contact me at firstname.lastname@example.org to learn more or register for a proof of concept of our Aware VMS.
Originally published Jun 09, 2020, updated Sept 01, 2020.