Edge AI runs a trained model on a device at the point of use, such as a computer mounted on the forklift, instead of sending data to a remote server or cloud for processing.
For collision warnings, where the decision is made matters. A camera system that processes images on the truck can warn the driver or slow a compatible forklift without waiting for a network round trip, and it keeps working when Wi-Fi drops in a freezer, a yard or the back of a building. Cloud processing suits work that is not time-critical: trend reports, event review, model updates and dashboards across sites.
Many forklift vision systems split the work. Detection and alerts run at the edge; events, clips and statistics are uploaded later for review. When comparing systems, ask what happens to warnings if the network is down, how models on the truck are updated and validated, and whether raw video leaves the vehicle or only event data. Keeping images on the device can also reduce privacy exposure. Edge processing does not make a system accurate by itself; the camera view and the model still decide what gets detected. The AI forklift safety guide covers the architecture choices.