I’ve been working for a couple years now to automate my RV using a combination of Particle.io Photon micro-controllers, an iOS app, and an Alexa skill. This has been fairly easy to do, due mostly to the ease of using the Particle.io API. Over the next year, in addition to adding additional functionality and more Photons, I hope to add Apple TV and Watch apps. This got me to thinking about how to make the system easier to configure and extend.
Since I’ve written all the software pieces myself (iOS app, Alexa skill, Particle sketches), up until now I’ve taken the expedient route of just hard coding the names of each controller into both of the apps. With only a single iOS app and Alexa smart home skill, this meant updating those two programs every time I added a new Photon, or extended one of the existing Photons. Not a big deal, albeit somewhat inconvenient.
However, recently I created an additional iOS app to allow using older iPhones to be mounted to the wall and used as control panels. Hard coding the names of the controllers into the apps means that I have to manually update each device whenever there is a micro-controller change. Now this is becoming a much bigger inconvenience.
So I’ve converted each micro-controller to be self registering with the system:
Each Photon publishes several variables that list the device names it implements, in addition to what ‘events’ it listens for. These variables are exposed by the particle.io API and used by both the Alexa and iOS app to dynamically configure themselves.
All applications use this information, instead of having to hardcode a list of commands.
This functionality is built into a published IoT particle library, so copy/paste is minimized.
So now instead of needing to reprogram the Alexa skill and iOS control panel apps whenever I add a new controller, I just need to expose the data about that controller as described above, and all the applications pick it up.
I’ve posting the Photon and iOS code to Github, so please take a look and let me know what you think.
I’ve now replaced my previously created Alexa Custom Skill with an Alexa Smart Home Skill. I’ve been holding off doing this because of the difficulty of setting up an OAuth2 server. Recently I came across an article describing how to use Login With Amazon to do this though, and I have gotten that working now.
So now I don’t have to say the name of the custom skill when invoking Alexa. Using the custom skill, I would have to say something like “Alexa, tell My RV to turn on the computer”. Sheesh. Quite a mouthful. And easy to get wrong. But using an Alexa Smart Home skill, I now only need to say something like “Alexa, computer on”. This seems like a small change, but it has made a big difference.
I’m working on providing some instructions, and then I’ll post all this code to Github.
Update: I’ve now converted the skill from using the Login with Amazon to using the particle.io oauth directly, and I’ve published the skill. What this means is that it can now be used by anyone, and it will prompt you during installation of the skill to provide your Particle.io login to access your devices. Refer to my other posts and Hackster.io project for more details. I had initially call this ParticleIoT, but that was hard to say and spell so I renamed it Patriot which uses many of the same letters.
I’ve been thinking for awhile now about using my old iPhones in my IoT projects. They have touch displays, wifi, cameras, audio, accelerometers, and maybe GPS depending on how old they are. Plus they have almost no value once they get a few years old. The only real downside to using them is the fact that they’re a bit hard to program, but hey, that’s what I do for a living.
So this past weekend, I scrummaged through my old Apple parts boxes, and came up with (2) iPhone G, an iPhone GS, iPhone 4s, and iPhone 5.
Doing some research, I decided that the iPhone G is not really worth messing with for a couple reasons:
The newest iOS support available is SDK4, so writing code to run on it would be difficult, and could not support the advanced features released over the past five years or so.
The iPhone G does not have a rear facing camera. One of the features I want to eventually support is using the camera for a room monitor. But since the phone will be mounted to a wall, the normal front facing camera will be pointed into the wall.
That said, the support for iPhone 3GS is not bad, but it is limited.
iOS 6 is supported
Xcode 7.3.1 is supported, currently the latest Xcode.
Swift is NOT supported. Swift requires iOS 7.
So just for fun, I created a version of the control panel in Objective-C for iOS 6 to run on the iPhone 3GS. This app simply displays images in a collection view, and calls the Particle.io API when one is pressed. I probably won’t add much more to this app, but instead develop a Swift version for use on the newer phones. I’ll add new features to that version, and leave the Objective-C version for just simple control operations.
Update: I’ve now posted a cleaned-up version of the app code to Github, and and article on Hackster.io.
I’ve updated the printed circuit boards for my IoT projects. These boards are 5×5 cm and intended to be used in a variety of IoT applications. They include the following features:
Switch from linear voltage regulator to buck regulator.
The linear regulators used on my previous boards were getting quite warm as a result of converting the RVs +12 volts to +5 or +3.3v. I found some inexpensive variable voltage bucking regulators for about $1 each. These are marked “D-Sun”, readily available on Amazon.com, and they work well.
Provide direct pin-outs to LED driver boards.
I’ve provided 4 sets of PWM pins that can interface directly with the Sparkfun 12959 MOSFET LED driver boards. I’ve positioned the pins such that standard header pins can be used to attach the boards instead of wires. I’ve gone back and forth about integrating the functionality directly, and finally concluded that the space used by the MOSFET and screw terminals was better pushed off onto small extension boards. Up to four of these can then be optionally added as needed. Sparkfun sells these for $4 each, so it’s sort of a no brainer. Putting them onboard would force me to moving to a larger 10×5 cm board, and only save a couple bucks.
Both 3.3v and 5v supplied
I’m using a 5v regulator to provide power to the Photon. It then has a 3.3v regulator for itself, and can provide 3.3v @ 100 mA to other sensors, etc. Since most of the Photons pins are 5v tolerant, this enables using both 3.3v and 5v sensors.
Provide groups of pins for ease of connecting other devices
To simplify adding additional sensors such as DHT11 temperature sensors, I’ve provided groups of pads that provide a GPIO, power, and ground. Some are 5v, and some are 3.3v. I was careful to ensure that the GPIOs provided with the 5v power groups are in fact 5v tolerant. These are great for things like PIR motion sensors, various switches, and so forth.
So after checking that the first batch of 10 boards work as intended, I’ve ordered another 10 and am in the process of replacing most of my existing controllers with these. While the Photon costs substantially more than the previous Arduino Pro Mini and RF24 radios, the ease of programming over the air combined with their robust design (5v tolerant pins, super stable operation) and included Particle.io support make these worth it!
I’m currently using my Echo and Dot to control these, but recently got AVS running on my Raspberry Pi and may throw that into the mix also.
If anyone is interested in using these boards in your own projects, post your request in the comments and I’ll provide links to the Eagle files so you can have boards made yourself. If you don’t mind waiting about 6 weeks, you can order these from itead.cc for $13 total for 10 boards. If you’re in a hurry, DHL shipping increases the total cost to about $26 total for 10 boards that arrive in less than 2 weeks. I ship with DHL for the first batch, then use the cheaper shipping to get more while I work with the first batch.
At this point I’ve installed about a dozen Arduino Pro Mini based controllers in my RV. These are very inexpensive, about $2 each, but suffer from several limitations:
This is ok if all you need is something to read a switch and set a corresponding set of outputs, but becomes an issue as requirements grow.
Require a direct FTDI cable connection to program or update
In my usage case, I’m mounting these things above ceilings to control lights, and behind wall switches to read and broadcast switch state. This means every time I need to change or debug them, I have to open up the wall, which means removing the switch plate and switch or lamp fixture to get to them.
Require direct physical access to reset
Sometimes they just hang, or their associated circuitry hangs up, and it is necessary to “hard reset” them. They have a push button reset on them, but as mentioned above it isn’t easy to access them in my situation.
So for awhile now I’ve been contemplating converting my Arduino Pro Mini based designs to use the Particle.io Photon MCU instead. These parts are awesome:
Fast 32 bit CPU
Lots of memory
Built-in WiFi and antenna
This last item is the biggie. I can update them remotely, meaning that I can leave the boards buried in a wall somewhere and still reprogram or reset them.
The thing that has made me reluctant to do so up until now has been the price. These parts are $19 each. That may not sound like much, but I plan on using a lot of controllers in my RV, probably on the order of 30 to 40. But then I stopped and did the math: 30 Photons at $19 each comes out to $570.
What? I’ve been using one Photon to bridge between the Pro Minis and the internet to allow Alexa to control them. Now I’m going to have each directly accessible, simplifying the overall design. So I’ve designed and built another PCB for the Photon.
So far things are working great. I’ve redesigned the architecture to use a publish/subscribe model, which will allow the system to be expanded without having to reprogram existing units. And I’ve converted my Alexa code so my Echo talks directly to the boards using particle.io publish instead of functions calls. But that’s a topic for another post.
As mentioned in my last post, I have connected my Echo to interface with my Arduino controlled RV lights. And thanks to the Particle.io Photon, this was quite easy. Perhaps the toughest part about this process has been getting past all the unfamiliar language used by Amazon, such as “Lambda functions”, “Skills”, and so forth. The actual implementation was fairly quick and easy, as I’ll explain in this post and the accompanying GitHub project.
Who is Alexa, and what is an Echo?
In a nutshell, the Amazon Echo is a small electronic device that you can interact with using spoken natural language. It has directional listening capability that allows it to hear you talk even in a noisy environment; for example when you’re playing the TV or stereo. It responds to you after you speak the work “Alexa”.
Requirements for connecting Alexa to your Arduino
You don’t have to own an Amazon Echo to get started. You can design and build a voice controlled interface, and test it using the Alexa Skills Kit (ASK) Service Simulator. The simulator allows you to type in what you would speak, and responds exactly as the Echo device would.
You’ll need to join the Amazon developer program, and setup an Amazon account to handle the backend. Both of these things can be done for free.
I’ve posted all the details on Github. I’ll warn you though; the instructions appear quite long. But don’t be deterred. None of the steps are particularly difficult, and the results are amazing!
I’ve been sharing tips and ideas with my buddy Don. He’s setup his Echo to control his pipe organ clocks. You can check out his work on facebook or at donholmberg.com. There’s also a blog article on Mutual Mobile’s website talking about some of our Arduino projects before connecting them to the Amazon Echo.
I’m having a blast working with all this new technology, and its fun to be able to use it to enhance my RV lifestyle!
Today I finally got all the pieces working to allow Alexa to control my RV lights. It turns out that the Alexa code only took a couple hours to implement, using a great tutorial posted by Kevin Utter on the developer.amazon.com site. This tutorial shows how to implement in under an hour a trivia game using Alexa. I followed the tutorial, created first a Reindeer trivia game, and then modifying it to be a Lisles Trivia game.
Once I was familiar with the process, I followed similar steps to create my own RvDuino Echo app. This app uses Alexa to listen for commands, and then forwards them to Particle.io which forwards them to a Photon Arduino.
I didn’t have to write any code on Particle.io. Code running on the Photon instructs Particle.io what commands to listen for, and which Arduino functions to run as a result. It really doesn’t get any easier than that. This has really made me a big Particle.io fan now!
I then used the Particle web IDE to write a fairly small Arduino sketch on the Photon that routes commands received from Particle.io to the desired Arduino Pro Mini over a simple RF24 network.
I’ve posted all the information and code on Github: https://github.com/rlisle/alexaParticleBridge.
The least expensive PCB manufacturer that I’ve found so far is iTead Studio. They currently will create ten 5cm x 5cm 2-sided printed circuit boards for $9.90. Yes, that’s less than a dollar each.
They offer 3 different shipping options, so I decided to order 3 batches of PCBs, each using a different option, to assess the difference. I’ve now received all 3 batches, so can report my findings.
Batch 1: ten 5cm x 10cm boards ($14.90) shipped least expensive ($4).
Total turn around time: 4 weeks.
Batch 2: ten 5cm x 5cm boards ($9.90) shipped medium cost ($4.50).
Total turn around time: 3 weeks.
Batch 3: ten 5cm x 10cm boards ($14.90) shipped most expensive (DHL $18).
Total turn around time: 6 days.
Note that this was done in December, so I would expect future shipments to be faster when not done around the holidays. The processing time by iTead was about 3 business days.
On my first order, I had forgotten to include any dimension information in the gerber files. I received an email from iTead explaining what was needed, and providing a couple simple options for how to fix it. I uploaded a file to their site that included the needed info, and the order proceeded without delay.
So based on my results, I’m going to order parts using DHL shipping when I need fast turn around, and use the middle option when I have a the time to wait. For merely a 50 cent difference, I see no reason to ever use the cheapest option.
I am very impressed with the high quality and very low cost, and expect to continue doing business with iTead Studio for a long time.
I’ve started replacing the lighting wall switches in my RV. Instead of hard-wiring the switches to the lights, I’m using radio connected Arduinos. The switches will appear to work the same, but what is really happening is that the switches are read by an Arduino, that then sends information over radio to another Arduino to control the LED light.
So why all the extra cost and complexity?
To begin with, the cost is not very much. The parts I’m working with amount to about $10 per board. As for the complexity, I have several objectives:
Enable dimming of the lights
Enable grouping of lights
Enable remote control
This last one is the exciting part. Once I get the internet connection working, I’ll be using my Amazon Echo to voice control the lights.
So, where am I in this process? I had initially cobbled together a wall switch to remotely control ceiling lights over my desk.
As you can see in the picture, this was pretty fragile, with parts soldered directly to the switch pins. I had to resolder things after breaking things when installing it into the wall. This was part of my motivation for creating custom printed circuit boards.
In this photo you can see the new 5cm x 10cm PCB I created for mounting to the wall switches. On this board I’m not going to use any of the 4 LED driver circuits, so they are unpopulated.
And here you can see the new PCB mounted to the switch. The FTDI programmer is connected to the Arduino for programming. It will be disconnected when I install the board into the wall. The nice thing about this arrangement is that it simply mounts into the wall like any other light switch.
The small blue board on the right side is an HM-10 Bluetooth LE part. This provides BLE communication and Beacon capability. This was my first attempt at surface mount soldering. Total cost on this board, including PCB, was about $7.50.
I finally received my second batch of printed circuit boards from ITead Studios. Delivery time was about 3 weeks. The total cost including shipping was $14.50 for ten 5cm x 5cm 2-sided boards! This is just amazing.
The quality of the boards is very good. In the image above you can see that I’ve mounted most of the parts. These took me about 30 minutes to hand solder to the board. Starting from the left, going clockwise, they are:
3.3v power regulator using an LD1117v33 and some capacitors
Arduino Pro Mini 3.3v
3 x 30N06 power mosfet 12v LED drivers.
The unoccupied squares on the right were intended for screw terminals, but I picked the wrong size Eagle part template, so they don’t fit. I could easily update the Eagle files and order new boards, but I have decided to simply solder the wires for now. I’ll fix the problem once I use up the current batch of boards and need to order more.
These boards are small enough that they can fit through the 3″ hole in the ceiling used to mount the recessed LED lights that I’m using.
Total cost for this board and parts is under $10 each. I populated all 3 LED drivers, but only need to populate the number needed on each board going forward, reducing the cost by about a buck each.