Mode S in the US

San Francisco & Silicon Valley:

New York, New York:


AviationMapper Demo

Aviation Mapper is LIVE! Click here to use it.

The Aviation Mapper launch video

Running live at Sydney Airport streaming AvMap via 3G mobile Internet

Running the Aviation Mapper desktop app

Presentation at Dorkbot Sydney Finale 2011

Presentation at Ruxcon 2011: "Hacking the wireless world with Software Defined Radio

Software Defined Radio

My Software Defined Radio experiments featured in GQ Australia (April/May) 2012!

SDR-powered Aviation Mapper is now LIVE! Click here to use it.

The Aviation Mapper launch video

Have a look at my Hi-Def intro video on using SDR on HF that was featured on Slashdot:
(The 'cheap SDR' they refer to can be found on my wiki for GNU Radio/Linux and Windows.)

The Software Defined Radio (SDR) I currently use is the Universal Software Radio Peripheral (USRP) 1 made by Ettus Research (in a custom housing!):

I've used it for several of my projects, including an aviation tracking system with a live streaming 3D Google Earth front-end:

Demonstration of BorIP network streaming between HDSDR and GNU Radio using USRP 1:

Example of HDSDR using USRP:

Presentation at Dorkbot

Here are some excerpts of the presentation Matt Robert and I gave at the October 2010 meetup of Dorkbot Sydney.

If you wish to see all of the photos from the set-up phase prior to the presentation on the roof of my apartment block, please have a look at the album in my gallery.

Australian Geographical RadioFrequency Map

RFMap featured in GQ Australia (April/May 2012)!

You can also have a listen to this podcast of a radio interview I did on with Ian Woolf on 2SER:
"Balint Seeber Mashed Up Radio"

UPDATE: I have written an extensive guide with plenty of screenshots explaining how to use the map to the full. The contents of the guide can be found to the left of this text (at the top of this page's left-hand column). Read it if you wish, or dive right in. Alternatively, open two tabs/windows and go through the guide while trying it out live.

The Australian Geographical Radio Frequency Map is a site that overlays all registered RF transmitters on top of Google Maps. Generic antenna sites are shown with the red RF icon, while mobile base stations are represented by the carrier that operates from the site (often multiple carriers do, but currently the first is chosen when determining the icon). A mouse-over will give you the site's description, and a click will tell you who broadcasts from there, and at what frequencies. Much more is to come...

Although people by-and-large won't be terribly interested in the positions of every antenna in the country, they might be interested in checking how close they are to their nearest mobile base station, how good a carrier's coverage is in a particular area, and for prospective spectrum purchasers to assess possible interference, etc. However, having said all that, it is primarily in the ham spirit.

Here is every transmitter site cached in the database, which is fully searchable from the web interface (shown below) by location, site name, client details, frequency range, emission designator and callsign:

Here is a browser preview:

Here is what it looks like on the iPhone:

And on the iPad:

Mapping Software

The mapping software brings all the data together and presents it on a map. Position and measurements are logged to a SQL database, and can be reviewed at will. The 'Level Layer Manager' allows customisation of data shown on the map. For example, one can choose to plot all measurements made on a particular ARFCN, and then further refine that to one cell by specifying the BSIC.

Collecting the data

Two streams of data are of interest: trace information from the mobile and position information from a GPS receiver.

To acquire position information, I used a commercial Navman device, which was modified to boot into WinCE and transmit NMEA data over a TCP connection (via Bluetooth Dial-Up Networking and GPS2Blue) to a virtual serial port on my laptop, which in turn was connected to gpsd. Full details can be found here.

Geolocation Experiment using the Mobile GSM Cellular Network

This experiment involved acquiring CellID and signal strength information from the GSM cellular network, tracking one's position while acquiring this data, and finally presenting it nicely. It is summarised in the following pictures (full details are described in the sub-sections found top-left):


Mapping position and signal strength measurements:

Making your iPhone look like a NMEA GPS receiver with gpsd and WiFi or Bluetooth

TRY IT OUT: If you wish to test the front-end interface on your mobile device, click here and tap 'Find' (not 'Enable'). This is handy if you want to check how well your location service is working, and to get raw lat/lon values! Please note: this will not allow you to send the position updates to your computer - this is purely for your testing only.

UPDATE 2: I have enhanced the web interface further so it supports time-outs and the ability to clear the update backlog that is accumulated following a timeout (see new screenshot below). Thank you to Ryan K for additional testing.
Unfortunately there appears to be a bug that is manifest under Linux: if gpsd is run with no clients connected and updates are sent from the phone, the script will lock up when attempting to send updates to gpsd after an arbitrary period of time. In the short term, this can be fixed by connected to gpsd and sending it a command (e.g. the 'watch' instruction). If a client is connected to it (which should be the case in nearly all circumstances) this doesn't seem to happen. This behaviour has not been seen under Windows.
Preliminary tests on Mac OS X are reported to be successful. If installing gpsd via a package manager, be sure to disable auto-startup (via init.d scripts and/or hotplug, etc) otherwise the gpsd instance launched by the Python script will not be able to bind to the normal listener port and you will be left wondering why you're not getting any data (as you'll be connected to the wrong gpsd instance).

UPDATE 1: I have uploaded a new version of the package (new Python and HTML). The new features include:

  • asynchronous updates (no more locking up Safari)
  • batching of updates (which should solve the Bluetooth problem described below), and
  • filtering of duplicate updates (you will see an asterisk * next to the 'Acc' value, as in the screenshot).

Many thanks to 'gabe' for testing! Also, please be aware that the HTTP server opens files from the current working directory of the Python process. If you're seeing 404s then your current directory is probably not the same as where the script is (you can check the current directory when it is printed out upon starting the Python script).

I was suprised to find that seemingly none of the dedicated GPS iPhone apps could stream your current location to a computer. Therefore I knocked up this simple solution, which uses a Python script to wrap up gpsd and make it think it's connected to a real GPS receiver that outputs NMEA sentences. The receiver is of course the iPhone, which uses Javascript (to retrieve location) and basic AJAX (to send the results to the Python script) all running in Safari. The page is served from Python (running on a computer) via WiFi or a tethered connection (Bluetooth or cable). Please note that Python and gpsd are not running on the iPhone - only the web browser is. This is what you would see in Safari once the page has been loaded from the Python web server:

Patch for Linux Kernel Orinoco WiFi driver re-enabling original monitor mode with Prism II headers & packet power levels

I was disappointed to find that the improved Linux Kernel Orinoco drivers do not report power levels via the standardised iwconfig 'monitor mode'. When the iwpriv 'monitor' mode was available, Prism II packets were sent from the driver to userland. These packets contained extra information reported by the hardware, such as per-packet signal & noise levels. I think having SNR measurements is one of the most useful features of Kismet, as it allows to you roughly determine the direction to a network based on signal power. Therefore I took the old-style monitor mode code and transplanted it into the modern driver (in kernel version Now both monitor modes are accessible. Kismet picks the older one (Prism II packets) first, before trying the standardised mode.

Without too much fuss, the Kismet SNR meter is back - for example:

TokyoCabinet and TokyoTyrant DLLs for Windows MSVC

TokyoCabinet (TC) is a wonderful open-source key-value pair database library by Mikio Hirabayashi, part of his TokyoProducts suite. TokyoTyrant (TT) is the networked portion of it (i.e. the database client & server). Since I am working on a project in Visual Studio under Windows and set out to use TC over the network, I needed to access the TT client API with MSVC.

My Contribution

I wrote the following major system components:

    1) A multi-threaded, load balancing MPEG-2 video decoder engine, featuring:
    • Automatic memory management & caching
    • Level-Of-Detail support and seamless transitions
    • Continuous playback or shot looping (given cut information)
    • Asynchronous loading and destruction

    [Initial tests indicate it can play over 500 videos simultaneously on one computer (with 2 HT CPUs and 1GB of RAM at the lowest LOD). TVisionarium is capable of displaying a couple of hundred videos without any significant degradation in performance, but there's so much still to optimise that I would be surprised if it couldn't handle in excess of 1000.]

    With my latest optimisations, TVisionarium is able to play back 1000 shots simultaneously!
    While profiling the system, total CPU usage averages around 90-95% on a quad-core render node!
    This indicates that those optimisations have drastically minimised lock contention and support far more fluid rendering.
    Have a look at TVis in the following video:

    This is an in-development 'video tube' test of the video engine:
    (Watch it on to leave comments/rate it if you like.)

Video Behind the Scenes

1000 videos can be seen playing back simultaneously!

This is a preview video produced by iCinema:


T_Visionarium was officially launched on 08/01/2006 as part of the 2008 Sydney Festival. Please read my blog post about it. Here are some pictures:

The festival banner:

Crowd before the speeches:

The digital maestros (Matt McGinity & I):

Appearances in TV News

09/01/2007 - SBS World News:

August 2006 - Channel Nine News:

T_Visionarium (AKA Project TVisionarium Mk II)

This series of pages summarises the contribution I made to TVisionarium Mk II, an immersive eye-popping stereo 3D interactive 360-degree experience where a user can search through a vast database of television shows and rearrange their shots in the virtual space that surrounds them to explore intuitively their semantic similarities and differences.

It is a research project undertaken by iCinema, The iCinema Centre for Interactive Cinema Research at the University of New South Wales (my former uni) directed by Professor Jeffrey Shaw and Dr Dennis Del Favero. More information about the project itself, Mk I and the infrastructure used, is available online.

I was contracted by iCinema to develop several core system components during an intense one month period before the launch in September of 2006. My responsibilities included writing the distributed MPEG-2 video streaming engine that enables efficient clustered playback of the shots, a distributed communications library, the spatial layout algorithm that positions the shots on the 360-degree screen and various other video processing utilities. The most complex component was the video engine, which I engineered from scratch to meet very demanding requirements (more details are available on the next page).

Luckily I had the pleasure of working alongside some wonderfully talented people: in particular Matt McGinity (3D graphics/VR guru), as well as Jared Berghold, Ardrian Hardjono and Tim Kreger.

Correctly lit, textured cloth: Torn Up

I fixed the lighting calculations and thought I would use a built-in texture:

Paused Tornado Simulation Fly-thru

Here is a fly-through of the standard tornado simulation with some pretty filaments:

DS with Correct Physics!

Shortly after the presentation day, I ripped out the original physics code that someone (who shall not be mentioned!) had written in the minutes prior to the presentation and replaced it with more 'physically correct' code:

Physically Controlled LED Display

A little something I made in my spare time:
(More details coming later...)

Atmel at76c503a Wireless USB Adapter

This started with my desire to build a Woktenna.
Of course you can't very well put a PCMCIA wireless card at the focal point of a cooking wok!

So the alternative is using a USB WiFi adapter that can hang on the end of a USB extension cable and
introduce minimal analog signal loss and USB is digital!

Despite the fact is says "Linux compatible" on the box, it wasn't immediately possible to do what I wanted to do,
which is: monitor mode!
With monitor mode, I'd be able to point the woktenna around and pick up the beacon frames of distant APs.

I found two drivers available for this device:
one over at BerliOS,
and the other at SourceForge.

LED Display

Thanks to the generosity of Aras Vaichas, I came into possesion of an old (1992) 60x8 dual-colour LED display. As it was just the display itself (no manual, instructions, software, etc) I set about reverse engineering the board. Using my multimeter I re-created the schematic for the board and found all the relevant datasheets online. Having figured out how to talk to the display, I interfaced it via the parallel port and wrote some control software for it. Once I could display various test patterns (multi-colours sine waves), I 'net-enabled' the software so that the display could be controlled over a network via UDP packets - the resolution is so low that the entire LED configuration fits into a single packet! Finally, I wrote a plugin for Winamp that streams the frequency analysis of the playing song to the display, which produces results like this:

Genetic Programming: 3D Visualisation in Python

This is a GUI frontend to the genetic programming assignment given in this subject. The aim is to evolve a wall-following robot. The program provides multiple visualisations of the process. It was written with Janice Leung - many thanks for the beautiful widgets! Developed on (but not for) Linux using Python and its bindings & add-ons: PyQt, PyOpenGL, PIL and psyco. README available. It contains more information about the code used to render the robot & world.


Broadcast Flooder & Network Bandwidth Hammer

My friend Rafal Kolanski and I decided one night to put our gigabit network cards to the test and measure how quickly a user-space program could generate packets and how many would be discarded before the destination's NIC would receive them. Therefore we wrote a small Linux program to complement my Broadcast Flooder, which I had previously written to test other aspects of my network.

Counting Lines of Code

Although there exists a plethora of programs that count lines of code, I thought I would write my own. It is designed to analyse C/C++ code and ignore whitespace, // and /**/ comments (both the single and multi-line sort). It also counts the number of FIXME's one has left in their code. Other languages (eg: Javascript, assembly) that also use such commenting conventions are compatible too.

Motion Vector Visualisation

Using my modified version of ffdshow, which sends a video's motion vectors via UDP to an external application, I visualised the motion vectors from The Matrix: Reloaded inside my fluid simulation. The grid resolution is set based upon the macro-block resolution in the video sequence and each type-16x16 motion vector controls one spatially-matching point on the velocity grid. The following visualisation is taken from the scene where they are discussing the threat to Zion while inside the Matrix before Neo senses that agents are coming (followed by Smith) and tells the ships' crews to retreat.

The final video is on YouTube, with the MVs overlaid on top of the source video.

Blue Milk

This is the new-and-improved fluid simulation in action. I'm perturbing the 'blue milk' with my mouse. Watch for the darker region form and expand behind the point of perturbation. Due to finer resolution of the velocity grid, the linear artifacts apparent in the earlier version have disappeared and it now looks smooth in all directions.


2D Fluid Dynamics Simulation

Velocity-grid-based 2D fluid simulation with effects that interestingly enough resemble Navier-Stokes simulations (well, a little anyway).

Reversing My Motion Vectors

To more carefully study the effects of reversing motion vector directions, I created a 'control' video of me making particular motions at different speeds. You can witness the results:

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