Logistics Safety AI

Event Gates Logistics Safety AI

Event Gates Logistics Safety AI is an advanced industrial vision system designed to enhance safety in busy logistics environments. By combining deep-learning image analytics with real-time monitoring, it detects potential hazards—such as collisions between forklifts, trucks, pedestrians, or falling loads—and intelligently triggers vehicle deceleration before an accident occurs. The system also ensures compliance by monitoring the use of personal protective equipment (e.g., helmets, hi-vis vests) and vehicle safety measures like curtains and wheel chocks, automatically logging safety violations and issuing notifications as needed.

The solution is tailored to high-risk zones like loading docks, sideloading bays, and high-rack corridors, where precise coordination between people, vehicles, and equipment is crucial. It integrates seamlessly with existing infrastructure—such as vehicle restraint systems and automated alerts—without requiring wearable tags or manual intervention. This enables organizations to proactively manage workplace safety, reduce accident risk, and ensure operational continuity—all while collecting valuable video and event data for audit and continuous improvement.

Features

Logistics Safety AI is a VIS solution therefore it has all VIS features and functions where applicable:

• Disconnected solution, deployed to the edge devices on the crane trolley or bridge, does not need internet or corporate network access.
• Proprietary high performance person detection model Event Gates PF, specially trained for top down view in industrial environments.
• Vislet Model Fusion allows detections of multiple models interplay together.
• Built-in trustworthiness features: Heartbeat, Short Term Memory, Emergency Preset of IPIO.
• Logging features including system logs, event logs and optional emailing features.
• All flexibility of regions(ROI), including polygons and multiple regions.
• Built-in mute with IPIO.
• Tracking
• Person counting helps secure unmonitored blind spots.