ITU-R P.833-9 vegetation-attenuation model + ESP32-S3 link-budget
solver produce bounded sensing range estimates per frequency and
foliage density. Plus a biomechanics-grounded gait-frequency taxonomy
spanning bears (0.5 Hz) to mice (15 Hz).
Headline ranges (121 dB link budget, 10 dB SNR margin):
freq sparse moderate dense
2.4 GHz 99.6 m 12.0 m 4.1 m
5 GHz 19.9 m 5.2 m 2.1 m
The 2.4 GHz / sparse cell (~100 m) is the practical sweet spot —
10x camera-trap coverage, always-on rather than PIR-triggered.
Honest scope called out explicitly: this is feasibility math, not
field measurements. Animal cooperation, foliage flutter, regulatory
limits, and BSSID-fingerprint degradation in remote forest are all
real follow-up problems.
Vertical applications (10-20 year horizon) catalogued:
- Endangered-species population census
- Wildlife corridor verification
- Invasive-species early warning
- Anti-poaching (human gait well-separated from wildlife)
- Livestock-on-rangeland tracking
- Agricultural pest control
Cross-connects to:
- R5 (saliency is task-specific — per-species classifier needs own
saliency map, same lesson as R12)
- R8 (wildlife sensing wants CSI not RSSI for per-subcarrier shape)
- R9 (fingerprint K-NN primitive transfers to per-individual ID)
- R7 (multi-link consistency for corridor coverage)
Pure-NumPy, no framework deps. ITU model + binary search solver.
Coordination: tick avoided PROGRESS.md to prevent races (horizon-
tracker M3+ track concurrent at the time).
Files:
* examples/research-sota/r10_foliage_attenuation.py
* examples/research-sota/r10_foliage_results.json
* docs/research/sota-2026-05-22/R10-through-foliage-wildlife.md
* docs/research/sota-2026-05-22/ticks/tick-6.md
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