A sensing device for integrated
image capture of stationary or moving objects in roadway intrusion detection systems comprises a camera and
central processing unit configured with
artificial intelligence to capture images within a specified area, calculate
mass and motion of objects, and predict trajectories. The CPU employs neural networks trained on custom models for
vehicle detection and classification without requiring internet
connectivity. When objects are predicted to enter protected areas such as work zones with emergency, construction, or maintenance personnel, the
system generates
voltage signal outputs to activate audible, visual, and haptic alert indicators. The device features a single housing with
monocular camera, CPU, and
wireless communication, mountable on fixed locations or vehicles, functioning in both stationary and mobile applications. The
system is expandable with additional cameras for stereoscopic vision or doppler
radar for enhanced measurements, determines safe traffic patterns by analyzing direction, lane position, and speed, provides staged warnings at multiple distance thresholds, detects irregular traffic patterns, collects traffic data, operates in
drone-mounted aerial configurations, and recognizes changes in
safety equipment patterns to alert workers of compromised
work zone perimeters.