Configurations that reduce cloud dependency and perform inference at the on-site edge are increasing. Security and latency are cited as the two reasons.
On-device AI configurations are increasing in manufacturing sites. The main reasons are shorter latency compared to cloud inference and the fact that drawings and process data do not leave the premises.
Rather than moving all inference to the edge, a mixed configuration is common: latency-sensitive inspection and classification are processed at the edge, while heavy analysis is handled on the server.
Plans that try to solve everything with a single edge box usually fail. Dividing roles is key.
If you tell us your site conditions, we will review a configuration that can be applied.
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