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A connection of scripts for playing with ADS-B data

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ADS-B funhouse

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.

adsbclient.py

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
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:

Key Description
--help well...
--radar-name name of radar, used as topic string /adsb/NAME/json
--mqtt-host MQTT broker hostname
--mqtt-port MQTT broker port number (default 1883)
--dump1090-host dump1090 hostname
--dump1090-port dump1090 port number (default 30003)
--verbose Verbose output
--basestationdb BaseStation SQLite DB
--myplanedb Your own SQLite DB with the same structure as BaseStation.sqb where you can add planes missing from the BaseStation db

proxclient.py

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:

Key Description
--help well...
--prox NAME name of proxradar, used as topic string /adsb/NAME/json
--mqtt-host MQTT broker hostname
--mqtt-port MQTT broker port number (default 1883)
--dump1090-host dump1090 hostname
--dump1090-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

airline-colors.py

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!

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