Processing architecture comparison
We can approach where to process video from different angles:
| Where | Pros | Cons |
| Edge device without GPU raspberry-pi ex. 🇨🇿 BeeLogger, BeePi | - cheap ~ 95 EUR for the board | - limited to simple numerical models - may not be reliable |
| Edge-device with GPU (jetson nano) ex. 🇩🇪Apic.ai, 🇦🇺Beemate, 🔬BeeAlarmed. Masters thesis | - efficient - low network dependency - can work offline with own GPU | ~ cost 230 EUR for the board alone |
| Hybrid: - on-premise (local) GPU workstation - Video streaming devices | - lower cost in total | - higher initial cost for the device - need of dedicated workstation location |
| In the cloud ex. LabelBee | - need high network bandwidth - need to optimize for variable network bandwidth - expensive - video streaming and processing cost - video storage cost | |
| Specialized PCB devices | - energy efficiency - low production cost | - usually low on RAM, GPU - high development cost |
| On a mobile phone | - price controlled by the customer - has built-in networking - has a camera - has screen - has battery & power management - no vendor-lock - easiest to get started - easy for beekeeper to setup - automatic app redeploys | - high variety of phones, inconsistent experience - for processing on the phone, issues with GPU, need to use custom mobile tensorflow - too high-level (in-browser), hard to handle exceptions & may need user intervention |