Cloud9, resin.io, Cylon.js - all coming together

As I mentioned in my previous post, I am really happy I discovered Cylon.js and was able to make basic stuff working. This is all cool but I wanted to be able to interact with my robot over the net so I thought it's time to try the API plugins the framework offers. To make things more fun and learn more in the process, I decided to use resin.io for deployment: this way I can update the code and test changes without being close to my Raspberry Pi all the time. I know it is possible but never tried to have a git project with multiple remotes; this is the perfect time for me to learn how this works since resin.io works by pushing code to the resin remote but I also want to be able to push changes to github. And because I don't want to be tied to my local machine, I decided to use Cloud9 for this project and push the code from there directly to both resin and github - which works great as you'll see below. By the way, Cloud9 is similar with Codenvy but the support for node.js is better (at least from what I know at this time) and having access to the entire VM and the command line makes it awesome; it is like working on a local machine but a lot better since it is in the cloud and accessible via a browser from anywhere.

This post is not really about the code itself: it is a work in progress that can be seen in my repo; instead, this post is about all of the tools coming together with a special nod to resin.io.

To start I read a lot of the Cylon.js docs and was able to put together a test robot without an actual device (using loopback instead) to which I plan to send commands using one of the API examples on the site; as a side note, the robot code only has generic commands like cmd1, cmd2 and so on instead of having commands like toggle and turnOn because this setup will let me change the actual code a command is executing while a client may never need to change. Going back to the API idea, I decided to start with the simplest API plugin (HTTP) even if there are no examples for it on the site. Unfortunately because I want to access my RasPi from outside my network, I don't know the IP (which will be assigned dynamically by resin) and the HTTP API needs to be configured with an IP; I am pretty sure there are solutions for this but instead of digging more, I decided to try the MQTT API which is tied only to a broker and doesn't need a definite IP. The client code is also very simple at this time but I hope it will evolve as I find some time; in the end though, I plan to issue the API commands via node-red which integrates very easily with MQTT.

It was very easy to start with Cloud9: I connected it to my github account, then created a new node.js workspace, there are plenty of docs on the site. And since Cloud9 gives access to the underlying OS, it was also easy to install libusb-dev (needed for Digispark as mentioned in my previous post) and also install all the node modules I need to start with; here are the commands for reference (last module is only needed for the client and I used the --save option so all the modules are registered automatically in package.json):

sudo apt-get install libusb-dev
npm install cylon cylon-digispark cylon-api-mqtt mqtt --save

Next thing was to add resin.io as a secondary remote which was pretty easy:

git remote add resin git@git.resin.io:username/application_name.git

Then all works as normal, git add/commit/push. The only special thing I needed to do was figure out how to install libusb-dev in the resin image. After some search on the web, I found out I can add a "preinstall" script to package.json. This was easy but it took me quite a while to figure out how to install this library because the only one found by apt-get was libusb-0.1-4 and not libusb-dev which I needed. After a lot of fiddling, I asked in the resin.io forum and the answer was quite simple: add apt-get update before the apt-get libusb-dev, as seen in the current package.json. A new push to the resin remote built the image without errors this time. Great!

The coolest thing is that when I built this image my Pi was offline but as soon as I plugged it in hours later, the new image was updated automatically - I know this is documented but it was so neat to see it working. This is so awesome! The resin.io team really thought of everything and I can't say how happy I am to be using their service. The small complaints I had in my original post are really minor, resin.io is really a great way to update your Pi code remotely. Again, big thanks to the entire team!

Hopefully now that all pieces are in place, I will find some time to write a robot that actually does something, and command it via MQTT from node-red. Soon...

Cylon.js - an amazing robot and IoT framework

A few days ago on a blog I follow I noticed an article about the release of Cylon.js 1.0. Never before heard about Cylon.js but the article sounded very interesting, mentioning robots and IoT, javascript and also support for 35 platforms so I decided to check it out. I am really happy I did, I have to say from the start that it is an amazing framework with a great design and tons of supported platforms and drivers, to make it really useful for tons of things: not just robots as the name implies but basically anything related to physical computing and the Internet of Things. It makes it incredibly easy to command robots and devices, and the API plugins it already comes with (http, mqtt and socket.io) make it really easy to connect and interact with these devices online. Really great!

Like I said, there are tons of platforms supported (basically anything I can think of is already supported) but since I happened to have a Digispark with an RGB LED shield handy since I last played with it and node-red, I decided to give it a try. It would have been easier probably to start with an Arduino to avoid a few hiccups but in the end I am very happy I gave it a try because it worked really well.

The Digispark documentation is really good but since I ran in a couple stumbling blocks on my Linux Mint machine (quickly clarified on the IRC chat by a very helpful user) I decided to quickly document the steps here, maybe they'll help somebody some day.

As mentioned in the Ubuntu section of the Digispark docs, first thing to do is install the cylon-digispark npm module. Next commands use "gort" and while this may not be an issue for anybody else, it was for me; I am not familiar with it and apt-get didn't find it so I stumbled a bit with the next step. However, when I asked about it on the chat channel I got a reply right away, saying I need to download it from here. Same user also mentioned that after I install it, I should run

gort digispark set-udev-rules

which was a great pointer because the docs where not very clear about what to run next (this one or upload) so this helped me a lot. Next command in the docs though is

gort digispark upload

which didn't work for me no matter what I tried. In the end I looked at the output of the command and decided to try instead

gort digispark install

and this worked right away. Then cd to the examples dir in the cylon-digispark module and first example I tried, blink, worked like a breeze. After trying most of the examples all I can say is that Cylon.js is indeed awesome and in the end pretty easy with just a couple stopping points, mostly due to my lack of Linux experience, I'm sure.

A big thank you to the Hybrid Group team behind this great project!

Project follow-up: Raspberry Pi with 433 MHz radios, mqtt and node-red

Now that my Arduino sensors to Raspberry Pi using 433 MHz radios project is done and I learned a lot about posting to the web and using a db, it was time to learn something new; mqtt is a very hot topic in the IoT world so this was my next target. Using an MQTT broker like mosquitto is not only cool but allows for decoupling of the different parts; for example, instead of writing a monolithic piece of code that does everything (read sensors, post to the web, save to a database, like in my previous project) and which needs a lot of work in order to add some new functionality, one could write a piece of code that for example, only reads sensors and publishes to an MQTT topic; then another piece of code can subscribe to that topic, get the sensor values and post them to the web; and yet another piece can subscribe to the same topic, get the values and save them to a database. And so on, the possibilities are endless and different parts of the system are independent and can be plugged in and out very easily. And since it is very easy to install mosquitto on a Raspberry Pi, I decided to go ahead.

To integrate mqtt in my C code I used mosquitto client library (libmosquitto) with some docs here: not a lot of help for a beginner but I found plenty of articles and example code. I ran into a lot of issues because the library that I installed was older and none of the example code worked; Roger (mosquitto's author) was kind enough to point me to a page explaining how to install the latest library so I installed libmosquitto-dev from this repo and it solved my problems. I also needed to add -lmosquitto to the Makefile.

After this code was done (if you are interested you can find it here), I had to decide what is the next piece so I decided on node-red: a chance for me to dig deeper into this cool technology and add to my experience from my previous projects. As Simen Sommerfeldt so eloquently makes the case in this great article, node-red is perfect as the "glue" between different pieces of code. To start with I decided to create a flow that reads sensor motion data from the MQTT broker and plays a sound via a python script. I already had a script but Simen's was much better so I used his - big thanks goes to him for sharing his work. The node-red flow was done in minutes; I then added 2 exec nodes to start the C code reading sensor data and the python script. As a side note, at this time I am running this exec nodes manually instead of starting them automatically when the flow starts, until I can figure out how to prevent multiple instance from running at the same time. This project is by no means as cool as Simen's moving skull but I will use as my Halloween project to play some random scary sounds when trick-or-treaters come to the door.

While I was working on this project I got an email from the great folks at dweet.io and freeboard about some great features they added recently. When I saw their email I decided to add another branch to my flow to get the sensors data and post it to dweet.io. Node-red is so awesome that I had all this done in a matter of minutes: I found a dweetio node-red node, installed it, added the nodes to post to dweet, and I also had a quick freechart done. The node-red flow is also in my github repo.

By the way, if you haven't yet, you really need to try dweet.io and freeboard: really awesome services with a free tier - big thanks to the guys at Bug Labs that are behind these services.