Sensing device for integrated image capture of an object and related intrusion detection systems

Abstract

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.

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