"Deploying LPR Cameras with Existing Assets" Blog graphic

Deploying LPR Cameras with Existing Assets

Big news! Gone are the days of having to buy an expensive, single-use license plate recognition (LPR) setup. Easily utilize existing camera assets in combination with powerful AI-driven LPR software without losing any of the benefits or functionality of traditional LPR systems

Okay, but how? Let’s talk about it…

How to utilize existing assets for LPR (+ powerful software)

While the cameras are essential in capturing information, the key component of LPR is the software, data capture and analysis capabilities. Rekor (Brite’s ALPR partner) has powerful software built on AI and machine learning to capture license plates with 99.02% accuracy.  

The best part is that it can connect to existing IP-based cameras like those utilized for traffic or surveillance. Let’s explore the requirements needed to utilize existing assets. 

LPR camera requirements: 

  1. The camera has to be IP capable
  2. Depending on the speed of traffic the camera must be able to produce 15fps – 30fps (the more the better!)
  3. The camera has to support the ONVIF protocol

Computer requirements:

  1. Must be capable of handling the total FPS load of all cameras connected to the computer
  2. Must have a connection to the computer which allows for the total frame rate of 15fps – 30fps without latency
  3. Must be able to run Windows or Ubuntu Linux operating system

Can cameras be multi-functional – or solely for LPR use? 

If the camera has the ability to supply two or more ONVIF feeds then you can simply turn on an additional feed and not interrupt the camera’s current usage (normally VMS) so you can run to both VMS and ALPR. If the camera only supports a single ONVIF feed, and that feed is currently being used by another source, then you would have to break that connection before moving to the ALPR software. Having two connections to a single ONVIF would cause connection issues.

Important notes

For a camera to be able to read a license plate you should be able to read the license plate in the frame of view yourself.  If you are looking at a video feed and you can’t read the license plates of the vehicles driving past, either because of angle or distance, then the computer will most likely not be able to read the license plates as well.

Rekor’s already strong AI-driven platform that delivers high accuracy is even stronger with the flexibility to adapt and utilize existing assets, minimizing expensive hardware costs and installation.  

We would love to chat if your department is interested in ALPR software and exploring how to utilize existing assets – contact us here!

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