Edge AI at the Waste Pile: Sub-Second Classification on a $999 Phone
The Compliance Gate runs Gemma 4 E2B (2.3B parameters) on the Pixel 10 Pro via LiteRT-LM runtime on the Tensor G5 EdgeTPU. Binary classification in under 500 milliseconds. Zero cloud latency. Zero per-inference cost. Zero internet dependency.
Why edge, not cloud: Latency (cloud = 2–15s vs. edge = <500ms). Connectivity (rural Ontario has no reliable cell). Cost ($0 marginal vs. per-request API fees). Privacy (images never leave the device).
The hardware stack: Tensor G5 SoC (Samsung 3nm SF3E), EdgeTPU (nanoTPU) for quantized inference, NPU for sustained workloads, InFO-POP 3D packaging. Titan M2 discrete security processor for hardware root of trust, tamper detection, and attestation API. LiteRT-LM v0.10.1 with speculative decoding and NPU acceleration.
The pipeline in 500ms: Frame capture → preprocessing (GPU) → E2B inference (EdgeTPU) → confidence evaluation → E4B fallback if needed → audio analysis (Gemini Nano) → result display → Hold-to-Seal available.
Cost comparison: Visual inspection ($0, low accuracy, no audit trail). Cloud AI ($0.01–$0.10/classification, no offline). Lab XRF ($50–$200/test, high accuracy). 905WOOD Edge AI ($999 device, $0/classification, high accuracy, audit-proof, offline).
Android 16 provides 7 years of updates through 2032 — past the REWOOD 2029 deadline.
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