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2018 Halloween IOT Clown Brought to you by Particle, DNN, and Open Source!
2018 Halloween IOT Clown Brought to you by Particle, DNN, and Open Source!

I need to start out by saying that I’ve been inspired to do all this by some great guys in the Charlotte area and they are Dan Thyer, Mike Linnen, and Jay Ziobrowski… thanks for the motivation guys! I am either copying something creative I’ve seen them do or trying to imitate their passion, talent, and drive for Halloween and/or IOT projects. One day I hope to be as sharp and creative as they are.

Halloween & IOT
In 2016 I made a flame throwing pumpkin (copy-catting one of Dan’s inventions) and let’s just say some of the parents weren’t too keen on fire being near their kids and I also didn’t make any fans on the community’s HOA! Though, we all must start somewhere. In 2017 I went the safer route and made the AirGhost which is very similar to this year’s project.

The IOT Clown
This year I have created an IOT Clown. I did some testing and iterating on various ideas and concepts and there’s just no way to get around it… the thrust of compressed air brings a startling surprise and the best part is that it’s safe. We have tons of young kids in our neighborhood and moving a skeleton bone (which I debated in this early prototype) could likely hit someone, cause a toddler to fall, or trip someone up which could potentially lead to a spill on the concrete sidewalk. I don’t want to injure anyone or have some local parents mad at me, so I reverted to the compressed air, but then added a few more movements and changed the medium from a ghost to a clown.

Here’s a quick video of the end-product prototype just to show you where we’re heading… I’m going to dress it up a little more by Halloween, but you’ll get the gist.

Parts Used
Here are the main components I’m using for this project:

Here’s a video “talk-through” of the mechanical parts and power supplies being used.

Let’s Talk About Particle
Particle's Photon The Particle platform is awesome! Check out this video of the Particle platform to learn more. I am admittedly a little bit behind all of Particle’s new innovations. I still need to learn about their Mesh and Argon solutions. Even though I’m not 100% up to speed I know you can do tons of creative stuff with the particle platform, their multiple IOT devices, and their integrated IDE. Since I’m using the Particle photon, we’ll start with it.

The Particle photon is a small IOT (internet of things) device that makes it easy to bring real world objects online. Particle makes it easy to setup the device and to connect to Wifi via a mobile app. If you want to know more about initially connecting and getting up and running with Particle they have some of the best documentation I’ve seen check out the doc, tutorials, and guides.

For this project all I really want to do is to move 3 servos… one for the head to spin, one for the head to roll, and one to push the handle on the air compressor. To do that we need to use the components I listed above + Particle’s platform + some code. I’ve listed out the components and just introduced the photon… now let’s look at some code.

Let’s Look at Some Code!
Particle’s platform is awesome, but we need some code to make things happen! I could easily copy and paste code here, but that wouldn’t help you understand the “why” and “how” behind some of the concepts. I hope to help you connect some dots here and as such I’ve cut a video walking through how I’m doing some of this stuff. The video shows code and includes videos of the device in action.

To all you senior devs… yes, the code shown in the video could be much better. I have not refactored anything yet, so the code is not nearly as efficient as it could be. And yes, I showed my handy Particle access token in the video… no worries though, by the time you read this I’ve already recycled it and created a new one.

Here are some relevant links:

So, with some disclaimers down and links shared let’s talk through the code some…

If you take the sum of all the info presented here that is how I’m making this happen!

And We Wait on Halloween!
Halloween is just about a week away at this point. If you have any questions or issues filling the gaps in this high-level tutorial, please reach out and ask your question. I plan on trying to video some of the fun at Halloween and posting any interesting reactions here just below this section… so stay tuned!

The Halloween Video
Check out some of the reactions we got from kids and a few adults!


IOT Example: Using Particle & Splunk to Monitor & Make Sense of Temperature
IOT Example: Using Particle & Splunk to Monitor & Make Sense of Temperature

In the past few years I’ve been getting into IOT. You may have seen tweets or blog about the Tech-Turkey project I’ve been working on or flame throwing pumpkins at Halloween. I’ve learned and used Arduinos, Raspberry Pi’s, and Particle Photons and Electrons. It has been fun to learn more and get into the connected world… the internet of things!

I’ve been keeping ServoCity in business and even recently worked to get a custom PCB created. Every step of the way I’ve been learning different things and realizing just how much more there is to learn. Recently I’ve started learning more about Splunk.

What is Splunk
If you don’t already know what Splunk is, Splunk is a software company based in San Francisco that produces software for searching, monitoring, and analyzing machine generated big data via a web style interface. Splunk’s software helps organizations with operational intelligence, log management, application management, enterprise security and compliance. 

Side note: In my first exploration into Splunk I wrote a blog about using Splunk with DNN that may interest you.

Particle & Splunk
DNN is a web application, but what if I wanted to get data from an IOT device? That’s when we call on Particle. If you’re not familiar with Particle, it makes it really easy to bring real world objects online. Particle is one of my favorite IOT platforms. It makes awesome microcontrollers, provides a nice IDE, has awesome documentation, and a great community. Connecting to Particle’s cloud is straight forward and even southerners can do it! See my presentation at our user group on DNN & Particle.

If you’re not familiar with Splunk, it makes it really easy to pull in data (machine data) and make sense of it. I’m talking about parsing vast amounts of data, creating visualizations and/or alerts and making it simple to understand. Even southerners can use it too!

Both Particle and Splunk are industry leaders and have some really big names behind their companies and as clients of their companies.

So why not bring Particle & Splunk together?

Reading Temperature with Particle
To use the awesomeness that both solutions bring us we’ll first need to read the temperature and post it to a webservice. Here again, Particle makes this easy. I used a basic temperature reader in a bread board layout for this experiment.

Temperature reading with a Particle, breadboard layout

Then, in Particle’s IDE I used the basic tutorial level code to read an analog value and post it to a Particle cloud variable. Cloud variables are accessible via web services. That is, I can make a GET request and parse the JSON object to get the data. Epic.

Particle code to post a variable to a web service

And all you have to do is “flash” the firmware to the device and then hit the API endpoint. In my case I accessed the service and saw the following JSON

JSON returned from Particle

Now we were cooking with oil! The next step was to get this data into Splunk.

Getting Particle’s RESTful Data Into Splunk
Getting RESTful data into Splunk is really straightforward thanks to Splunk’s extensibility. Splunk has an extensions gallery that can be found on the Apps and Ad-Ons sections of the Splunk website. I tell you this because ultimately, I followed a blog by Damien Dallimore on getting REST data into Splunk which used a modular input extension and that was all it took. I simply completed the required fields in the Splunk REST Modular Input as shown below.

Configuring the REST API modular input by Damien Dallimore in Splunk

After clicking save, the data from my Particle temperature reader was showing up in Splunk!

Creating Dashboards from the Particle Data
Once data shows up in Splunk you can literally perform any search query you want on the data and create/configure dashboards, panels, reports, alerts and more. Splunk is very powerful in this regard and scale to infinity. However, for this scenario I just wanted log the temperature over time from one device, as well as the temperature’s highest, lowest, and average. Splunk, again, made this very simple.

After clicking on the “result” field I created some visualizations and voila! Out popped some neat dashboards showing all my data in a way that’s easy to understand.

Splunk Dashboards displaying temperature reading from Particle

If you are like me, you kind of want to see things in action. So for those of you like me who are visual learners, here’s a quick video of the solution in action.

An IOT Combination That’s Hard to Beat!
As you can see, both solutions are awesome and the opportunities are endless. Consider the possibilities here… Particle is easy to deploy and post data to the net and Splunk can easily connect, suck in data, and bring instant insights. The more data you give to Splunk the more knowledge you’re going to have. Splunk can handle this at scale too… I mean massive scale. Why not connect thousands of devices and pump all the data into Splunk and tune it to your liking! I believe that’s what they refer to as operational intelligence 😊 Now my mind is spinning with possibilities. Is yours?


Clint Patterson

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