istrain — a passive RF train detector you can build

Is a train blocking the crossing? istrain answers that by listening — passively, on public railroad radio frequencies — to the transmitters every train carries: the crew/dispatch voice and trackside defect detectors on 160–162 MHz, and the End-of-Train and Head-of-Train telemetry on 457.9375 / 452.9375 MHz. It decodes the End-of-Train brake-pressure and motion data, transcribes the voice, and fuses it all into one live verdict.

Live instance: istrain.jhestyr.net · featured on rtl-sdr.com

New here from the blog? → the full build guide is APOCALYPSE-EDITION.md (human- or coding-agent-readable). Open problems we'd take help on are at the bottom.

It's built on a couple of ~US$30 RTL-SDR dongles, some wire, and an always-on Linux box running Docker. No transmitting, no license needed to receive in the US, no railroad cooperation — the trains announce themselves; you just get set up to hear them. It works at any North American crossing because the EOT/HOT frequencies are continent-wide and the voice channel plans are public — you change one config file for your location.

This repository is the complete, working system — the DSP, the decoders, the web dashboard, and the container definitions — shared so anyone (or any coding agent) can build one from scratch and learn from it.

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→ Start here: APOCALYPSE-EDITION.md

The full from-scratch build guide: hardware shopping list, operating-system setup, freeing the dongles from the TV driver, researching your crossing's channels, bringing up the container stack step by step, transcription, and the hard-won tuning lessons. It's written to be read straight through by a human or handed to an LLM coding agent pointed at this repo.

What's here

Path	What it is
APOCALYPSE-EDITION.md	the complete build guide (read this first)
scripts/	the signal engine + decoders — stdlib Python + NumPy only
scripts/iq_hop.py, iq_channelize.py	the retune-in-place 452⇄457 hop and the sub-channel splitter (the mission radio)
scripts/eot/	the two-pass FFSK End-of-Train decoder (drift-tolerant; validates via vendored PyEOT)
scripts/bot-recover.py	Head-of-Train frame recovery + head/tail join
scripts/transcribe-worker.py	voice clip → comms filter → Whisper → transcript
dashboard/	serve.py (the API + static server, stdlib, no framework) + the web UI
docker/	Compose template + Dockerfiles (web / airband / scanhop / worker)
config/	istrain.conf.example (your channels go here) + the DVB-blacklist file

The idea in three transmitters

1. Voice (160–162 MHz): dispatchers, crews, and defect detectors that read out milepost, axle count, and speed in plain English. The most direct "a train just passed here" signal.
2. End-of-Train (457.9375 MHz): the last car's telemetry box — unit ID, brake-pipe pressure, motion flag — a 1200-baud FFSK burst every few seconds. The brake-pressure curve tells you passing vs. dwelling vs. cut-and-standing vs. departing.
3. Head-of-Train (452.9375 MHz): the locomotive's half; decode it and join head to tail for a confirmed complete train.

Any one can be too weak to read, but a real train lights several bands at once — so istrain correlates across all of them.

Open problems — what we're still figuring out

Passersby with RF chops: these are the live unknowns. Pull requests, corrections, and "actually, it works like this" all welcome.

• Range is antenna-bound. The rail voice band is weak and buried in house RF; gain doesn't help (it just amplifies the noise). A grounded rooftop antenna is the open lever — height and distance from the shack, not dBi. What we've got works; what we want is the dwellers' faint keys cleanly.
• Mid-train / DPU bursts (±12.5 kHz off the EOT/HOT centers) are unidentified. They're not drifted EOT (our decoder says no). Next step is sub-channel labeling to separate a real distributed-power emitter from the fixed wayside booster carrier before any raw-IQ demod.
• The Head-of-Train frame is only half-cracked. We recover the frame and decode the addressed unit (enough to join head to tail), but the command/type field + BCH are still unread. HOT-format docs are scarce; if you know the framing, we'd love a pointer.
• Direction of travel should fall out of the approach/recede signal envelope — unbuilt, and blocked on the better antenna above.
• The brake-pressure taxonomy (passing / dwelling / cut-and-standing / departing) came from ~50 ground-truthed passages on one subdivision. It may read differently on other railroads and operating patterns — more ground truth from other crossings would sharpen it.

License & credits

GPLv3 — see LICENSE. The EOT decoder validates frames against PyEOT by Eric Reuter (GPLv3, vendored under scripts/eot/); full attribution and the licensing note for forkers are in ATTRIBUTION.md. The communities and tools that made this possible — RTL-SDR Blog, osmocom rtl-sdr, RTLSDR-Airband, faster-whisper / OpenAI Whisper, FFmpeg, NumPy, Docker + Dockge, and the railfan frequency databases — are credited in the dashboard's With Thanks panel.

Contact

Questions, corrections, or you built one and want to compare notes — jhestyr@gmail.com. Open an issue or a PR here too.

A community project. If you build one, we'd love to hear what you heard.