AI Smart Glasses: On-Device vs Cloud Processing for B2B

AI smart glasses can run inference on-device via NPU or stream to cloud servers. This guide compares both architectures for B2B roadmap planning.

On-Device AI Processing

NPU (Neural Processing Unit) handles inference locally. Typical chips: Qualcomm QCS6490, Mediatek Genio 700.

• Latency: <10ms response
• Privacy: Data stays on device
• Power: 0.5-2W typical
• Capabilities: Wake word, voice commands, on-device translation

Cloud-Assisted AI Processing

Heavy inference runs on cloud GPU clusters. Requires stable connectivity.

• Latency: 200-500ms (network dependent)
• Privacy: Data encryption in transit, GDPR compliance possible
• Power: ~0.1W transmit only
• Capabilities: LLM chat, image analysis, real-time transcription

Architecture Comparison

Selection Guide for B2B

Choose architecture based on use case:

• Warehouse/logistics: On-device for offline voice commands
• Field service: Hybrid — wake word on-device, LLM by cloud
• Enterprise translation: Cloud ASR preferred for accuracy
• Healthcare: On-device for HIPAA compliance

AI Smart Glasses FAQ

Q: Can AI smart glasses work offline?
A: Yes, with on-device NPU. Wake word, basic translation, and voice commands work without internet.

Q: What is the latency difference?
A: On-device <10ms. Cloud 200-500ms depending on network.

Q: Are cloud AI glasses secure?
A: End-to-end encryption supported. For sensitive data, choose on-device processing.

Q: Which architecture costs less?
A: Cloud has lower BOM but recurring API fees. On-device has higher upfront NPU cost.

Why GenChipEMS for AI Smart Glasses?

• 18 years foreign trade experience
• Shenzhen production base — global logistics hub
• NPU integration: Qualcomm QCS6490, Mediatek Genio
• Full compliance: CE, FCC, RoHS
• Flexible architecture: on-device, cloud, or hybrid
• 12-month warranty, spare parts support

Contact Our AI Team

Email: [email protected]
Phone: +86 138 2651 9287

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