IREX has introduced a new neural network architecture, trained on a proprietary dataset, to advance video stream quality monitoring and tampering detection for CCTV systems. The upgraded AI model is capable of identifying both full and partial camera occlusion—whether caused by human interference or drones—while intelligently ignoring natural, non-threatening environmental changes such as lighting shifts or snowfall.
The enhanced AI-powered detector can now accurately distinguish between a wide range of camera conditions, including:
These improvements empower IREX to automatically monitor the health and reliability of thousands of surveillance cameras deployed across urban environments. If video quality deteriorates, the system immediately notifies the Network Operations Center (NOC) to initiate timely inspection and maintenance, ensuring cameras remain mission-ready to detect and respond to real-time threats.
The enhanced AI-powered detector can now accurately distinguish between a wide range of camera conditions, including:
- Field of view obstructed
- Dirty lens
- Lens out of focus
- Overexposed (too bright) image
- Underexposed (too dark) image
- Signal loss
- Bitrate too high
- Frame rate too low
These improvements empower IREX to automatically monitor the health and reliability of thousands of surveillance cameras deployed across urban environments. If video quality deteriorates, the system immediately notifies the Network Operations Center (NOC) to initiate timely inspection and maintenance, ensuring cameras remain mission-ready to detect and respond to real-time threats.
