AST Digital Magazine February 2017 AST Digital Magaiinse Volume 10 | Page 73

Volume 10
erything we do . Those vendors base their products on what we call “ old-school ” ALPR technology . I ’ m talking about the old , closed , hardware-dependent systems that you see mounted on police vehicles .
Not only are those systems bulky and expensive , all they really do is attempt to report a license plate number . They get a license plate hit on a criminal database , they alert you .
That ’ s about it . More importantly , they don ’ t do it very accurately in real-life conditions .
Most companies base their accuracy rates on testing conditions that don ’ t mirror reality .
At PlateSmart , we ’ ve moved way beyond that point , and so we can ’ t really call ourselves an ALPR company anymore . ALPR is still a part of what we do , but our focus is on complete vehicle identification .
That means recognizing not just the license plate , but also the vehicle make , type , color , and many other identifiers . We can do that because we don ’ t use Optical Character Recognition ( OCR ) like the competition does .
Feb 2017 Edition
Our proprietary algorithm performs true object analysis on a video image , which means that yes , it can read license plates , but it can also read just about any other data you wish , like product labels or shipping crate markings , for example .
But it can also recognize objects in a frame , such as a vehicle , as well as the important identifiers of that vehicle such as make and color .
In addition to all that , we also include analytics capabilities that you don ’ t normally see in an oldschool solution .
For example , ARES , our flagship enterpriselevel platform , can recognize suspicious vehicle movement patterns and can also tell you if a particular vehicle has loitered in one location for too long .
We ’ re also adding many new analytic features in the second and third quarters of 2017 , such as vehicle style recognition and facial detection based on vectorless technology , that will increase the user ’ s real-time situational awareness .
All of those features are advanced capabilities we realized were needed long ago by government agencies at the local , state , and national levels , which are tasked with protecting the public from crime and terror .
The biggest advantage for all of these agencies is that , because we ’ re software-based , our technology , with all of these capabilities , can be mass deployed quickly and easily .
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