In this article, we will discuss recommended practices and initial expectations for Rhombus Artificial Intelligence.
- What does our AI do for Rhombus?
- Initial AI expectations
- Properly setting up the camera for optimal AI accuracy
What does our AI do for Rhombus?
The current artificial intelligence we use for Rhombus cameras helps track humans, vehicles, faces, and license plates. Our AI can identify the camera's humans, faces, vehicles, license plates, and unusual behavior. The AI compares faces and assigns an alphanumeric value to license plates in our cloud infrastructure.
Initial AI expectations
Some of our AI is stored/performed locally on the cameras. This means that when first registering the Rhombus camera you may experience some false positives for human or vehicle movement. If you experience a large number of false movements please feel free to reach out to the Rhombus Support team here for better assistance with this issue.
Properly setting up the camera for optimal AI accuracy
Below is a quick start guide for how to properly set up the camera to track particular movements and recognition for certain features. Below is a list of common tips that can be applied to the initial setup of the camera along with the expectations for AI features.
Framing of the camera view
When mounting and setting up a Rhombus camera you should always try to eliminate all unmoved space from the camera view. The camera should be mounted parallel to the horizontal plane. Here is a mounting guide for Rhombus cameras So if a camera is framed on a wall, you would not want the wall to be visible or limit visibility as much as possible. Below is an example of framing of a camera view with too much of the ceiling in the picture along with a fix.
Below is the same camera now adjusted to eliminate the ceiling from the frame.
Placing Activity regions
Setting up activity regions in a camera frame view helps by providing AI alerts only if the movement passes the threshold of that region. Also, setting up 'don't trigger' activity regions for areas such as bushes or any other non-human or vehicle movement that occasionally moves by environment changes. This helps improve your AI by reducing the number of false movement alerts. To learn more about activity regions see the article here.
For vehicle movement, you will need to have the camera positioned so that the full car enters the field of view. If only portions of the car enter the field of view this may not trigger a vehicle movement detection from the AI. In order for the AI to detect human or vehicle movement, a certain number of pixels in the frame have to be changed.
License Plate Recognition
Our unusual behavior feature is a great feature to use to track people falling over, running through a building, or any other non-normal human movement. To configure the unusual behavior, please check out this article here.