This is a collection of Python scripts for playing with ADS-B data from dump1090. You will need an rtl-sdr receiver to join the fun.
This is yet another ADS-B decoder written in Python. It feeds off port 30003 on your dump1090 receiver and publishes each message to your MQTT broker. It is invoked using:
% adsbclient.py -m <dump1090 host> -H <MQTT host> -r <radar name> -pdb PlaneBase.sqb
The MQTT publish topic is /adsb/<radar name>/json and the JSON data contains the following fields:
| Key | Description | Sample data |
|---|---|---|
| icao24 | ICAO24 designator | "4787B0" |
| loggedDate | Local timestamp | "2015-09-08 21:08:26.061000" |
| operator | Name of airline | "Cathay Pacific Airways" |
| type | Type of aircraft | "Boeing 777 367ER" |
| registration | Aircrafts ICAO registration | "B-KPY" |
| callsign | Flight's callsign | "CPA257" |
| lost | true if receiver lost sight of aircraft |
false |
| track | Track [degrees] | 131 |
| groundSpeed | Ground speed [knots] | 413 |
| squawk | SSR code assigned to the flight | 3315 |
| altitude | Altitude [feet] | 17500 |
| lon | Lontitudee | 13.33108 |
| lat | Latitude | 55.29126 |
| verticalRate | Vertical climb/descend rate [ft/min] | 2240 |
The aircraft's operator, type and registration are not available in the ADS-B data the aircraft transmits and needs to be pulled from another data source. One excellent source is PlaneBaseNG with about 147k aircrafts and can be downloaded here. Another source is Virtual Radar Server with ~77k aircrafts, mainly UK ones.
If you often see aircrafts that are not found in the above databases you can add them manually to your own database and tell adsbclient.py to search it too using the argument --myplanedb. Invoking adsbclient.py with a non existent database will create and initialize the database in the specified file.
The following arguments are supported by adsbclient.py:
| Key | Description |
|---|---|
| --help | well... |
| --radar-name NAME | name of radar, used as topic string /adsb/NAME/json |
| --mqtt-host HOST | MQTT broker hostname |
| --mqtt-port PORT | MQTT broker port number (default 1883) |
| --mqtt311-protocol | Use MQTT protocol v3.1.1 rather than the default v3.1 |
| --dump1090-host HOST | dump1090 hostname |
| --dump1090-port PORT | dump1090 port number (default 30003) |
| --verbose | Verbose output |
| --basestationdb DB | BaseStation SQLite DB |
| --myplanedb DB | Your own SQLite DB with the same structure as BaseStation.sqb where you can add planes missing from the BaseStation db |
This script subscribes to the JSON radar data from adsbclient.py and calculates the distance to the nearest aircraft using your location and makes an Bing image search for an image of the aircraft (you will need a Bing API key for this, see bingconfig.py).
% proxclient.py -m <MQTT host> -l <your latitude> -L <your longitude> --imagedb planeimgs.sqb
The default publish topic is /adsb/<prox name>/json and the JSON data contains the following fields:
| Key | Description | Sample data |
|---|---|---|
| icao24 | ICAO24 designator | "40688E" |
| loggedDate | Local timestamp | "2015-09-08 13:36:50.732000" |
| time | Local UNIX timestamp | 1441712210 |
| callsign | Flight's callsign | "BAW18" |
| operator | Airline | "British Airways" |
| type | Aircraft type | "Airbus A320" |
| image | URL to image of aircraft | "http://..." |
| bearing | Bearing from receiver [degrees] | 74 |
| distance | Distance from receiver [km] | 9.408453 |
| vspeed | Vertical climb/descend rate [ft/min] | 0 |
| speed | Ground speed [knots] | 518 |
| altitude | Altitude [feet] | 40000 |
| heading | Heading [degrees] | 240 |
| lon | Longitude | 13.50045 |
| lat | Latitude | 55.6902 |
The following arguments are supported by proxclient.py:
| Key | Description |
|---|---|
| --help | well... |
| --prox NAME | name of proxradar, used as topic string /adsb/NAME/json |
| --mqtt-host HOST | MQTT broker hostname |
| --mqtt-port PORT | MQTT broker port number (default 1883) |
| --dump1090-host HOST | dump1090 hostname |
| --dump1090-port PORT | dump1090 port number (default 30003) |
| --lat, --lon | Your location on planet Earth |
| --verbose | Verbose output |
| --imagedb DB | An SQLite DB where the URLs to aircraft images are stored locally |
This script allows commercial pilots to, unknowingly I might add, change your moodlight. Any MQTT controllable moodlight can be set to light up in the prominent color of the airline's logo, dimmed accodring to distance to the plane.
Subscribing to the JSON data from proxclient.py, it fetches the logo for the airline that operates the nearest flight and calculates the prominent color of their logo. The color is dimmed according to distance and posted to an MQTT topic.
The prominent color in the logo is the one found in the most pixels, white and black excluded. Colors are cached in a file called logocolors.json.
% airline-colors.py -m <MQTT host> -d <max distance> -t <color topic>
The default publish topic is airlinecolor containing the message #RRGGBB
The following arguments are supported by:
| Key | Description |
|---|---|
| --help | well... |
| --mqtt-host | MQTT broker hostname |
| --mqtt-port | MQTT broker port number (default 1883) |
| --distance | max distance in kilometers, the color will be black (#000000) for aircrafts beyond this distance |
| --topic | the topic to post color data to |
| --verbose | Verbose output |
Released under the MIT license. Have fun!