Recently I was working on a project for the Raspberry Pi that grew a little too big for a single Pi to handle. Instead of moving the app to a system that contains more resources, I thought I would divide up the work load and have individual tasks ran on multiple Raspberry Pi’s instead of one. Since I already have a RPi cluster, I thought this would be a great opportunity to put it to work. Even though there are plenty of different ways to do distributed computing, I chose to go the RPC route. Since I had a really good grasp of what needed to be done and what could be offloaded to other Pi’s for processing, I chose not to use any of the available 3rd party frameworks that are out there on the web. Instead, I chose to roll my own module using the XML RPC libraries that come packaged with Python. Since my project doesn’t require any extra dependencies, it makes it easier to get up & running on the different Pi’s in my cluster. Because I went thru the (easy) work of writing the RPC app, I thought I would share a simpler version of it with all of you in case you find yourself needing to do something similar.
In this video, I give a sneak peak of a new app I wrote for Google Glass that allows you to do real-time vehicle diagnostics using a OBD-II diagnostic scanner. Currently I can read my vehicle’s current MPH, RPM, & MPG. As time permits, I will add support for things like coolant temperature, average MPH, average MPG, engine load, etc… I will add support for all PIDs that the OBD-II protocol supports including the ability to read and clear check-engine codes & indicators.
I’m reading my vehicle’s computer data using the Bluetooth Supper Mini OBD 2 / OBD II bluetooth adapter (diagnostic scanner) which I got for $20.00 from Amazon. I will post the source code as soon as I have the remaining commands supported.
In yesterday’s article, I shared with you a webserver written in Python that captures data being logged and transmitted from your vehicle’s computer using the Torque app for your cellphone. In that article, I mentioned that I would also be providing a PHP app that does the same thing. As promised, I now want to share that PHP code with you. If you haven’t read yesterday’s article, I would advise that you check it out first. In it, I introduce you to the Bluetooth Supper Mini OBD 2 / OBD II adapter which I use for reading the computer data from my truck and pass it back to my webserver for logging and future analytics. You can get the bluetooth adapter from Amazon for $20.00. That article also includes the instructions for configuring your webserver’s URL in the Torque app as well as what the Torque app is and does. Once you have finished reading that article, come back here where you can get the code for a PHP app that can be used for capturing and logging the data transmitted from the Torque app on your mobile device.
Over the Christmas break, I have been working on several new apps for Google Glass. One of those apps includes viewing real-time OBDII data from my truck using an OBDII bluetooth adapter and my Google Glass. To do that, I am using the Bluetooth Supper Mini OBD 2 / Mini OBD II adapter which I got from Amazon for $20.00. It’s basically a small device that plugs into your vehicle’s computer (usually under the driver-side dash) and transmits data to another device such as a computer, cellphone, or tablet. When I received this ODBII adapter, I learned that there is a cool program available for Android (possibly iOS as well, but I’m not 100% sure) that allows you to view the data from the adapter & your vehicle’s computer in real-time on your cellphone. One of the coolest things about that app (aside that it’s free) is that it allows you to upload your vehicle’s data to a webserver in real-time as well. Just make sure you have a service plan that includes data. The app is called “Torque“. The example URL for the webserver that comes pre-populated in the Settings page of Torque points to a webserver operated by the app’s creator. However, it allows you to change that URL to point to a webserver of your own. Not knowing exactly what the data would look like coming from the Torque app, I decided to write a small Python app that would act as a webserver and would collect the data from the Torque app & store it in a database for future reference. Since I’m sure there are probably plenty of others out there that would like something like this, I’ve decided to share that Python app with you.
Ever since receiving my new Google Glass a few weeks ago, my inbox has been flooded from people asking if I have built any computer vision apps yet for Glass. The answer to those questions is “yes” and I plan on posting some articles and videos about them very soon. Until then, I thought it would be a good idea to post some articles showing how to get started with computer vision development on Google Glass using OpenCV for Android. Since there are several steps involved with building useful computer vision apps for Glass, I will be breaking up the steps involved into multiple articles. In this article, I will walk you thru the steps required to get your first OpenCV app installed and running on your Glass. While I’m at it, I will also show you how to install and run a simple face detection app. In a future article, I will show you how to do more such as applying filters and even a little bit of augmented reality.