A few years back while I was a researcher at the Department od Computing Science, Glasgow University we purchased 2 small Nabaztag rabbits to augment our prototype multimodal navigation system. The rabbit announced instructions for the users to search the map to find different locations around the world – a sort of digital treasure hunt. Fast forward 7 years and I’m doing it again.

The Karotz, the new name for the rabbit, is a special interactive device. It has ears that you can position, an LED in it’s belly that you can set to various colours, a microphone so you can give the rabbit commands, a speaker to play music either remotely or from a USB stick which can give the rabbit a voice, a nose to smell out those pesky RFID tags and a new feature that’s different from the older rabbits, a webcam to see.

We’ve bought another 2 rabbits for our research at CASA and we’ve been having a think about how we can use them to brighten up the office. For the first few months we had some issues with our corporate WiFi network, think blocked ports and firewalls, so actually getting the rabbit to talk to the outside network has been a challenge. By setting up a 3G router in the office we’ve been able to have more control of our Internet of Things devices and this has meant that we can make these devices respond to some of our collection software.

Once we got the rabbit connected, I decided the first thing we had to do was make the Karotz API friendlier to developers. I set up a small web server written in Node.JS on an internal server where we could send commands to the rabbit and it would proxy these authenticated commands to the Karotz API, which in turn sends to the rabbit.

For example if you want to set the ears to down then you would call the following web service:

http://localhost:9000/ears/9/9 

To set the LED to red you would call:

http://localhost:9000/led/ff0000

And to make the rabbit talk you would call:

http://localhost:9000/speak/Hello%20World

Oliver O’Brien had the idea to attach real world London Underground Tube alerts to the rabbit so I set up a command on the server to make the rabbit announce the tube alerts (which you can see on the video below)

http://localhost:9000/status/ff0000/The%20Central%20Line%20Is%20down

These types of ubiquitous technologies allow developers to integrate real time data into our lives without users having to log onto computers or get our mobile phones out to actively check on services. We are just starting to explore the possibilities of this technology so stay tuned for some more of cool little side projects.

Many maps use overlays to display different types of features on the map. Many examples show old hand drawn maps that have been re-projected to fit on our modern day, online ‘slippy’ map but very few show these overlays over time. In this tutorial we are going to explore animations using the Google Maps iOS SDK to show the current live weather conditions in the UK.

The Met Office is responsible for reporting the current weather conditions, issuing warnings, and creating forecasts across the UK. They also provide data through their API, called DataPoint, so that developers can take advantage of the live weather feeds in their apps. I’ve used the ground overlays from DataPoint to create a small iOS application, called Synoptic, to loop around the real-time overlays and display them on top of a Google Map, very handy if your worried about when it’s going to rain.

Finished App and Source Code

I always find it interesting when these tutorials show you what we’re going to create before digging deep into the code so here is a small animation on the right of the page of what the end product should look like.

What you’re looking at is the real-time precipitation, or rain, observations for the UK on Sunday 19th January 2014. It’s been quite sunny in London today so much of the rain is back home in the North. You can grab a copy of the code for this tutorial from GitHub.

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At UCL CASA our main focus of research is cities and how, as a population we use our cities daily. My main interest is discovering and analysing the hidden city through our daily interactions on social media, blogs, and crowd sourcing data that’s not currently available. We recently held a 2 day conference at CASA (1 day of workshops and 1 day of talks) teaching attendees the skills and tools to visualise these types of datasets.

My workshop was all about Data Hacking and collecting real time data from Twitter. We had around 70 budding data scientists learning how to collect data from Twitter using Node.js and then visualising that data on Google Maps Engine. Here are the slides (and also embeded at the end of this post) from the event so that you can try it out yourself at home and get your hands dirty with some raw Twitter data.

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Hello and welcome to my new blog. I’ve been blogging for a few years in several places but I felt the time had to come to consolidate all the blogs to one location and give me a single place to share some of my views, some of my research and most importantly, hopefully, teach you something new. So before I start blogging I thought I’d tell you a bit about myself.

I’m Steve and currently work as a Researcher at the Center for Advanced Spatial Analysis at UCL (University College London). I originally come from just outside Glasgow, Scotland but have taken the long trip south for tropical climates and ended up living in London. My current research focuses on distributed high performance computing and analysing large datasets in real-time (while mapping the results!). In my spare time you can find me walking long distances, climbing mountains, composing music or playing the piano or trumpet.

In recent years I have specialised on building mobile applications (mainly iOS) and systems that open up the world of data visualisation, mining and analysis to the masses. I can sometimes be found on StackOverflow answering questions about Google Maps API and the iOS SDK, and answering MacOS problems. In addition to this I give lectures and workshops to academics and industry partners on using Google Docs and Fusion Tables to create compelling visualisations to showcase on Google Maps and Google Earth.

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