Right now, tech that used to be relegated solely to the scenes of science fiction films is now a common part of everyday life. This is certainly true of artificial intelligence (AI).
AI is everywhere, from smartphones to Hollywood.
In a new piece for Security Magazine, Satish Raj details the potent role AI is playing in physical security. He points to the fact that remote video monitoring (RVM) — what he dubs “the most effective physical security strategy available to fight crime” — has become energized by AI technology.
He explains that AI is taking this kind of surveillance from “the reactive to the proactive era.” The end goal is to make physical security solutions smarter and more sophisticated. As criminals rely increasingly on more advanced tech themselves, it’s up to physical security officials to harness the new tools available to them to keep their companies and assets safe.
From CCTV to RVM
Raj begins by tracing the timeline of how the security world arrived at this point. He recalls that closed-circuit television (CCTV) was once at the vanguard of visual monitoring. These systems were designed for surveillance cameras to generate live feeds that covered a businesses’ entire campus.
“The problem? This footage was recorded, typically without anyone watching in real time, and stored for later viewing. High-end operations would have security guards watching the video, but as a standalone technology it was mostly reactive — a business owner could go back and review the footage for evidence and use it for insurance or law enforcement purposes, but the damage had already been done. And for businesses, this meant monetary loss and potential brand damage,” Raj explains.
To address these blind spots, CCTV evolved into RVM, delivering Internet-connected solutions where feeds could be viewed remotely. This was certainly a great boon to security professionals.
Now, camera feeds could be observed on phones, laptops, and tablets. Security managers could keep an eye on sensitive sites miles away. The big flaw of these systems is that they offered more simultaneous feeds that are impossible for human operators to keep track of — this is where AI comes into the picture.
A future of predictive tech
“It’s easy to understate the impact that analytics, especially AI-powered analytics, have had on RVM. They completely changed the game. Although computer vision was among the first practical applications of AI, in the RVM industry AI started adding material value only in the last decade,” Raj adds. “Advancements in AI technology have enabled wider adoption possible through reduction of cost, complexity and effort in applying AI to RVM.”
This tech is significant because “virtual guards” that are on call can be alerted by AI to “take action before a crime occurs.” AI systems can be trained to detect common breaches like someone jumping a fence or a rock being thrown at a store window.
“Pairing AI with RVM brought physical security into the proactive era. Thanks to the continued evolution of AI, security leaders should assume this is only the beginning. AI’s next act will take physical security into the predictive era,” Raj writes.
As AI analytics systems become more advanced, companies will have a leg up on potentially damaging criminal activity.
It’s a brave new technological world, and the industry professionals who learn how to harness the capabilities of AI-driven tech solutions will be able to shore up their physical assets and sensitive data in ways that would have felt like sci-fi dreams just a few decades ago.
Peter Cavicchia II 