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Forklift Safety is an automated collision prediction and traffic management system designed to monitor vehicle movements and pedestrian presence in warehouse aisles, blind corners, and loading zones.
By processing live feeds from overhead cameras, the system calculates vehicle speed, trajectory, and proximity to workers. Using motion vectors to project paths 2.4 seconds ahead, it automatically flags risks when paths intersect.
This active intervention connects directly to floor systems like vehicle speed limiters (via PLCs) and warning beacons, resolving warehouse hazards in real-time before accidents happen.

Forklift Safety with LogiScan
Deploying Forklift Safety models onto LogiScan’s local edge compute system converts standard video feeds into active collision warnings. Here is our edge deployment checklist:
Sub-28ms Inference
Frames are analyzed locally on Nvidia GPU edge compute nodes, predicting hazards with ultra-low latency.
PLC / Speed Limiting
Directly trigger vehicle decelerators or floor warning lights to physically stop hazards.
Near-Miss Logging
Maintain complete, audit-ready reports of near-miss events to identify high-risk warehouse zones.
Zero Camera Swaps
Bridge directly into your existing IP camera infrastructure via standard RTSP protocols, avoiding rewiring costs.

Deploying Analytics in Minutes
Our customer portal allows security administrators to easily configure stream integrations and bind AI playbooks without writing code.
Register Camera Stream
Provide the RTSP address, IP camera feed, or link your existing VMS/NVR grid directly within the stream manager portal.
Draw Polygon Detection Zones
Define active tracking boundaries and safety tripwires directly on the live camera viewport overlay inside the browser.
Bind AI Model Playbook
Select and load the customized Forklift Safety neural model to run frame inference on this specific camera channel.
Configure Alert Egress Actions
Choose warning targets to dispatch events automatically: Slack channels, EHS log databases, or custom REST webhooks.
