Mathieu MoranandCopilot 6d61b70a06 Add SIM868 cellular fallback for tracking uploads (untested, no SIM card)
modules/app_cellular.py: uses the SIM868's built-in AT-command HTTP(S)
client (AT+HTTPINIT/HTTPPARA/HTTPACTION/HTTPREAD) instead of a real
ppp0 interface, since the module's GNSS (polled continuously by
app_gps.py) and its GSM/GPRS radio share the same physical UART
(/dev/serial0) - a pppd/chat dial-up would take over that port
entirely and starve GNSS polling. Staying in AT-command mode lets
cellular HTTP calls interleave safely through the same serial lock.

Only carries small JSON tracking batches, never dashcam video -
cellular is far too slow/limited for that, and the modem's HTTP AT
interface has too small an internal buffer anyway. Dashcam uploads
remain WiFi/Ethernet-only, unchanged.

modules/app_upload.py: tracking-batch upload always tries WiFi/
Ethernet first; only on a connection-level failure (not an HTTP error
status, which means the server was reached) does it retry over
cellular. Exposes last_network_path/cellular_fallback_configured in
/api/upload/status; UI shows which path the last batch used.

Feature-flagged off by default via new YARIS_CELLULAR_ENABLED/
YARIS_CELLULAR_APN/_APN_USER/_APN_PASS keys in db/upload_creds.env
(all blank by default) - has zero effect on the existing WiFi upload
path unless explicitly configured. Regression-tested against the real
deployed server that normal WiFi uploads are unaffected while
cellular stays unconfigured.

*** UNTESTED against real cellular hardware - no SIM card was
*** available. See docstrings in app_cellular.py and PLAN.md for
*** exactly what needs validation once a SIM card is available.

Co-authored-by: Copilot <[email protected]>
2026-08-08 20:34:53 -04:00

yaris-obd 🚗📡

A Raspberry Pi 3-based OBD-II + GPS tracker for my 2013 Toyota Yaris — reads live vehicle data over USB, tracks position with a SIM868 GNSS/GSM HAT, and serves it all from a local web UI you can pull up on your phone by connecting to the car's own WiFi hotspot. Fully usable offline: no internet needed in the car, offline map tiles included. Also handles pulling dashcam footage off a USB dashcam for local/remote backup.

rené lévesque bangers i have a dream

Listen on Spotify

Screenshot

UI

Features

  • 📊 Live OBD-II data (speed, RPM, DTC codes) over a cheap USB ELM327-compatible adapter
  • 🛰️ Real GPS tracking via a Waveshare SIM868 GNSS/GSM/Bluetooth HAT, plotted live on an offline Leaflet map (pre-cached map tiles — no internet needed in the car)
  • 📶 Self-hosted WiFi hotspot so you can load the web UI on your phone from inside the car, with automatic fallback to your home WiFi when in range (http://yaris.local — no port number)
  • 🎥 Dashcam file retrieval — detects a USB dashcam automatically (any brand/folder layout, no hardcoded device path) and copies its footage locally
  • 🗄️ Local SQLite trip logging, with an optional MongoDB remote sync path
  • 🔌 Runs fully headless as a systemd service, autostarting on boot

Hardware

Part Notes
Raspberry Pi 3 Model B Web UI host + hotspot
Waveshare SIM868 HAT GNSS (GPS) + GSM/GPRS, unused Bluetooth
USB OBD-II adapter PL2303-based, ELM327-compatible (originally Bluetooth, switched to USB)
USB dashcam Any brand — detected as generic USB mass storage
2013 Toyota Yaris The patient

See PLAN.md for full hardware bring-up notes (SIM868 jumper/UART setup, antenna gotchas, etc.) and the detailed project history.

Getting started

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python3 app.py

The app serves on http://<host>:5000. On the Pi it also runs as a systemd service (see deploy/) and is reachable with no port number at http://yaris.local once the mDNS + port-redirect setup described in PLAN.md is installed.

Project status

This project was revived after a couple of years on the shelf. Progress is tracked phase-by-phase in PLAN.md — currently through Phase 8 (dashcam retrieval), with the remote server/upload phase still to come.

S
Description
rpi obd app with way less features... yet
Readme MIT
4.6 MiB
Languages
Python 43.5%
Kotlin 21.6%
HTML 15%
JavaScript 13.2%
Shell 5.1%
Other 1.5%