plt-airt-2000

ADS-B processing stuff using "big data" tools.

General approach

Data source is a Raspberry Pi 2 B running dump1090 software. Using Malcolm Robb's fork: https://github.com/MalcolmRobb/dump1090.

The program receives data via a DVB-T stick with winecork antenna. Setup mainly according to: http://www.satsignal.eu/raspberry-pi/dump1090.html Winecork antenna is described in http://www.rtl-sdr.com/adsb-aircraft-radar-with-rtl-sdr/. There are also a lot better antenna setups, but this one gives up to 200 km range from my home in Utrecht.

Data exchange via WiFi dongle.

NEW setup 2023

You need only 2 files

• send_kafka.sh, enter all your detail here, including Confluent Cloud credentials and your unique ID per receiver
• dump1090-kafka.service, systemd definition file, update the path to send_kafka in this definition and then install to /etc/systemd/system, enable and start

Setup instructions

• On your Raspberry, set up the flight radar receiver, for instance from this repo https://github.com/MalcolmRobb/dump1090, or from https://www.flightradar24.com/
• clone this repo to the raspberry: https://github.com/hellmarbecker/plt-airt-2000
• in your home directory, (I assume /home/pi), create a copy of plt-airt-2000/raspberry/send_kafka.sh
• edit this copy:
  • overwrite the Confluent credentials with the correct ones (CC_BOOTSTRAP, CC_APPIKEY, CC_SECRET)
  • enter a unique string for CLIENT_ID (you can just use your name)
  • enter your own geo coordinates for LON and LAT
• make sure the script is executable
• copy file plt-airt-2000/raspberry/dump1090-kafka.service to /etc/systemd/system/
• make sure the path in ExecStart=/home/pi/plt-airt-2000/send_kafka.sh points to your customized script
• enable and start the service

Raspi setup notes

• For headless setup, check https://www.raspberrypi.org/forums/viewtopic.php?t=74176.

• Default setup for rsyslogd will try to write to console and fail, writing lots of messages to /var/log/messages. To fix this, see here: https://blog.dantup.com/2016/04/removing-rsyslog-spam-on-raspberry-pi-raspbian-jessie/.

• In /etc/ssh/sshd_config, set PermitRootLogin no.

• Disable WiFi power saving by editing /etc/network/interfaces and adding a line to wlan0 configuration like so:

allow-hotplug wlan0
iface wlan0 inet manual
    wpa-conf /etc/wpa_supplicant/wpa_supplicant.conf
wireless-power off

• Adding systemd service definition files for dump1090, Minifi, connect.sh (TBD)

Data sourcing

dump1090 listens for incoming connections on port 30003 and will start writing comma separated records when a client connects.

Simulator

This repo also contains a small simulator (serve_data.py) that can replay a previously collected data file, servicing port 30003 as well.

Data transfer

1. Kafka VM cluster from: https://github.com/elodina/scala-kafka.git

   Note: if the host is Windows, need to make sure that the files in the vagrant and checks subdirectories have Unix line endings!

2. Install Docker based Kafka cluster on a single Linux VM. See linux-install-notes.md

Data transfer, preferred approach

1. NiFi single machine "cluster" to move data in, on AWS

2. MiNiFi on the Raspi

Setup based on the excellent article by Andrew Psaltis: https://community.hortonworks.com/articles/56341/getting-started-with-minifi.html

MiNiFi side (Raspi)

Using the TCP Listen processor on MiNiFi. Since dump1090 is listening (acting as a server) itself, connect the ends like this:

nc localhost 30003 | nc localhost 4711

For now, using connect.sh script to transfer data from 30003 to a listening port (ListenTCP processor) on MiNiFi.

NiFi side (HDF 2.0 on AWS)

1. Parse and process the data by using first ConvertCSVToAvro and then ConvertAvroToJSON. Avro schema is in the repo, for explanation and example see:

   https://avro.apache.org/docs/1.8.0/gettingstartedjava.html#Compiling+the+schema

2. Merge data together into ORC files by cascading two MergeContent processors. Note that with just one processor, NiFi will consume excessive heap space and crash.

Processing

TODO - use Spark to get interesting aggs

Visualization

Use Google Maps API?

Kafka Client

C Client

Pilfered from Confluent examples. This simply takes whatever it gets and writes it to a Kafka topic. No key is added at this stage.

Note that librdkafka has to be available on the Raspi (sudo apt-get install librdkafka-dev).

Call like this:

nc localhost 30003 | ./producer adsb-raw ~/.ccloud/example.config 

This was done on purpose - original idea was to parse the key already during data generation, like so:

nc localhost 30003 | perl -ne 'my @x=split /,/;print "$x[4]|$_"' | ./producer test-topic ~/.ccloud/example.config

and have a producer client that splits key and value at the pipe character. However, it is more interesting to do that part in KSQL.

Using kafkacat as Kafka client

The easiest way to get data into Kafka is probably by using kafkacat. The included shell script send_kafka.sh does the following:

• Gets ADS-B data in CSV format by connecting to dump1090 on port 30003
• Extracts the Hex code as key and prepends it to the record
• Uses kafkacat to send data to Confluent Cloud