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analytics will give the power of AI to stake- holders in the most common sense and effec- tive ways. Who knows their security needs better than those in the trenches?
The Softest of Soft Targets
Not long ago, I visited a university hospital, headed to the Pediatric ICU. The Pediatric ICU houses some of the most vulnerable persons in the hospital. I checked in with reception and, upon request, told them the name of the patient I was visiting. They checked their database, found the patient, and quickly filled out a visitor pass for me. I placed the purple visitor sticker on my chest and, just like that, had free reign of the hos- pital. I took the elevator to the correct floor and roamed around until I believed I was at the correct door to the ICU.
A phone outside of the locked doors instructed visitors to dial a number, tell them who you were visiting (not who you were), and the door would be opened. A couple in front of me was already on the phone. They hung up and I followed them inside as the door opened. I walked around the ICU for a couple minutes without protestation from any staff members, before realizing I was in
the wrong wing of the ICU. A friendly nurse pointed me in the right direction. There was no security present.
At the correct door now, I called the num- ber, gave the patient’s name, and entered when the door opened. Thankfully, I was in the right wing, found the room where I was headed, and had no malicious intent. As I walked through the ICU, I thought to myself: “Why is it that our most vulnerable targets are the least secured?” From Pediatric ICU patients in the hospital, to students in dorms, to the elderly on our campuses.
A simple guest list, powered by face recog- nition, that allows the creation of Safelists and Blocklists assigned to each patient would, in the least, stop an estranged parent who has a restraining order against him or her from freely walking into the child’s room.
All you need is the name of the patient? If we rewind my steps to get to the ICU, I would not have even made it past the check-in desk, or the security guard who visually scanned me for a purple sticker at the elevator, before security was alerted and steps were taken to immediately remove me from the premises.
For all the shiny, fantastical things that AI and deep learning can and will do in the future, it’s the common-sense use cases, the automating of the mundane but critical security processes, which we currently rely on over-taxed human resources to accom- plish, that represents the truly exciting outcomes of deep learning-powered video analytics solutions.
Brent Boekestein is the CEO and Co-founder of Vintra.
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campuslifesecurity.com | March/April 2019
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