If you are evaluating AI tracking systems for your pallet operation, you will hear two approaches: cloud AI and edge AI. The difference matters more than most vendors will tell you.
Cloud AI vs. Edge AI
Cloud AI sends your camera feeds to a remote data center for processing. The data center runs the AI models, extracts counts, and sends results back to you.
Edge AI runs the AI models on hardware installed at your facility. Video is processed locally. Only lightweight results (counts, timestamps, events) are sent to the cloud.
Why Edge AI Is Better for Pallet Operations
1. Speed
Edge processing happens in milliseconds. There is no round trip to a cloud server. For real-time counting, this means events appear on your dashboard as they happen — not seconds or minutes later.
2. Reliability
Edge AI does not depend on your internet connection for core functionality. If your ISP has an outage, the edge device continues counting. Data syncs to the cloud when connectivity returns.
In a cloud-only system, an internet outage means you are blind. No counts, no events, no data until it comes back.
3. Privacy
With edge AI, raw video never leaves your premises. This is a significant advantage for operations that are sensitive about camera footage leaving their network.
PalletVision processes video frames in memory on the edge device. Frames are analyzed and discarded — not stored, not uploaded. Only metadata (count, timestamp, event type) reaches the cloud.
4. Bandwidth
Streaming multiple high-resolution camera feeds to the cloud requires significant upload bandwidth. A single 1080p camera at 30fps generates roughly 4-8 Mbps. Six cameras could consume 24-48 Mbps of upload bandwidth.
Edge AI processes locally and sends kilobytes of event data — roughly 1000x less bandwidth than cloud streaming.
5. Cost
Cloud AI processing charges per frame, per minute, or per camera. At scale, these costs add up quickly. Edge AI has a one-time hardware cost and fixed software subscription — costs are predictable and do not scale with video volume.
What Edge AI Hardware Looks Like
PalletVision edge devices are compact hardware units installed on-site. They connect to your cameras via your local network (wired Ethernet) and run AI models on built-in GPUs.
Typical hardware:
- Starter operations: Mac mini with M4 chip (handles 4 cameras)
- Mid-size operations: Mac mini M4 Pro (handles 8 cameras)
- Large operations: Dedicated edge AI server (handles 12+ cameras)
The hardware is physically small, quiet, and runs on standard power. It connects to your network and starts processing immediately after configuration.
The Hybrid Approach
PalletVision uses a hybrid architecture that combines the best of both worlds:
- Edge: Real-time video processing, counting, event detection
- Cloud: Dashboard, reporting, historical analytics, ERP sync, multi-site aggregation
This gives you real-time local processing with the convenience of cloud-based dashboards and reporting.
The Bottom Line
For pallet operations, edge AI is the right architecture. It is faster, more reliable, more private, and more cost-effective than cloud-only alternatives. The only thing cloud does better is marketing — edge AI does the actual work better.