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Tim Brooks on Emerging Technologies in Physical Security

Historically, video surveillance has been used for forensic purposes such as going back to review footage and reconstruct an incident that has already occurred. For example, if a purse were stolen on camera someone would review past footage in hopes of finding the appropriate video. Not only is this method labor intensive, but it also results in limited success, which concludes a limited ROI case.

AI is changing this paradigm as it is more focused on preventive measures including real-time alerts and analysis. While AI can still help with post-crime analysis, this new generation of AI is able to predict or interrupt criminal activity.

To do so, AI uses specialty, deep-learning algorithms to predict behavior. For example, these algorithms can determine the difference between fighting or hugging, measure social distancing for COVID-19 safety, detect opioid theft from a patient’s IV and more.

Now, when looking into access control, AI is important within facial recognition. Instead of scanning a crowd for criminals, AI is trying to detect identity. For example, it spots if people are wearing masks and socially distancing appropriately. AI can also tie into building systems such as elevator control or other touchless solutions.

So, how is the security integrator positioned to benefit from the change in physical security? Thanks to AI advancements, there is now a ROI case for video surveillance as the end user has a better solution, experience and success rate, which ultimately leads to expansion of these systems and new sales opportunities.