Alexa | Darian Johnson's Favorite Things

Random Thoughts (Aug ’19): Proto-Pasta, Alexa Gadgets, Dual Extruder 3D Printers

Sometimes you gotta spend more on 3D filament to Save More

I love Proto-Pasta’s filament. Yes, it costs more that what I was originally using (Inland filament), but it’s not too expensive (especially their Sparkly HTPLA line) and I find that I waste less time (and filament) on failed prints. The extra $10 I spend is well worth it…

Bonus – I can get it from my local Microcenter (10 mins away from my house)

Sparkly HTPLA

Longing for a Dual Extrusion Printer

I love my Wanhao i3 plus 3D printer. So far, I’ve added Z braces, a new cooler, a new build plate, and a glass bed. My prints (for the most part) come out exactly how I expect. I’m planning to add a metal hot end and new extruder gear to start printing exotics…

That being said… there is one thing that the Wanhao will never give me (easily) – dual extraction/multi-modal printing. So, I’ve been thinking a lot about a Prusa MK3 or (gasp) an Ultimaker…. Maybe one of them will be my gift to myself at Christmas…

Amazon Gadgets, a game changer?

The Echo Wall Clock (an example of an Alexa Gadget)

Last month, Amazon quietly rolled out an updated Alexa Gadgets API. For those unaware, gadgets allow you to connect a smart device to an Amazon Echo. You can build smart clocks, toys, games, etc. – and have them interact with custom skills or “base” Alexa functionality (alarms, timers, wake word detection, etc.) So far, the API is limited, but this could be a game changer for the IoT/connect device landscape… if Amazon can move from Bluetooth classic to BLE…

https://developer.amazon.com/alexa/alexa-gadgets

Cool Contests:

There are a few contests that I’m considering entering

Instructables Indoor Lighting Contests – I think I have a good idea… if I can find the time
Either the Hackster or Element14 Avnet Azure Sphere contests: I have no good ideas for either of these contests (yet)… but I’m excited about working with a hardware chip that’s customized to work with one of the major cloud providers

https://www.instructables.com/contest/lighting2019/

https://www.hackster.io/contests/SecureEverything

https://www.element14.com/community/docs/DOC-92683/l/sensing-the-world-challenge

… more thoughts next month!

dbj

Building an Automated Cat Feeder with Amazon Alexa

In my second IoT project, I tackle feeding my cats by voice commands.

My family owns three cats; for the most part, they are well behaved – unless they are hungry. When it’s time for them to eat, they get a little crazy – constantly meowing and running under/between our legs, or waking us up at night.

We used to keep extra food in their dishes, but they would just overeat – resulting in cat throw-up (which, without fail, I seemed to step in every morning on my way to the kitchen).

We’ve been living in this “claw-ful” situation for a few years, and never really considered resolving the problem. My oldest daughter suggested that we (and by we, she really meant me) build an automated cat feeder. I told her that I didn’t have the time to build one… but then, I figured, why not give it a try.

Full instructions are on the write up at Hackster – https://www.hackster.io/darian-johnson/alexa-powered-automated-cat-feeder-9416d4

Getting the Most out of my Amazon Echo: Using TuneIn Radio

Telling Alexa to “Play The Big DM on TuneIn” has been the highlight of my Alexa experience to date

Before I talk about technology, a quick segue: I grew up in the age of radio and cassettes. The hiss of a cassette tape is a callback to simpler times – when most albums were constricted as complete pieces (and not as a string of singles); when the order of an album was important (no easy skipping)… when building a mixtape was more art than science.

I feel the same way about radio. There’s nothing like the excitement of not knowing what great song is coming next, or the magic of slowing flowing from one song to another. Before there was music video¹, there was radio – where I discovered Incognito, and Angela Bofill, and Teena Marie…. Continue reading “Getting the Most out of my Amazon Echo: Using TuneIn Radio”

Building a Magic Mirror using Alexa, AWS, and a Raspberry Pi

Some people spend their vacations traveling, or relaxing, or visiting family. I spent my two weeks off building an Alexa enabled, Raspberry Pi device for Hackster’s Internet of Voice challenge.

But, to paraphrase Madonna: “Don’t Cry for Me, Internet.” I really enjoyed those two plus weeks of coding. I learned a ton about AWS IoT and MQTT (and re-enforced some “non-sexy” skills – like security and IAM).

And the device that I decided to build…. a magic mirror. Why a magic mirror? Well, I am the guy that:

Never checks for delays in his work commute until he is stuck in a four-lane accident
Forgets his umbrella when the forecast calls for afternoon showers
Doesn’t find out about a major news event unless the story breaks on ESPN
Always forgets to pull my trash bins to the curb on garbage pick-up day

In short, my morning routine is a mess (#firstworldproblems). An Amazon Echo (or a phone, for that matter) would resolve most of those problems. Unfortunately, I never seem to have my phone with me as I’m getting ready in the morning (it’s usually charging). And I’m usually not asking Alexa for these details (I don’t have an Alexa device in my bathroom).

60% of my morning routine is centered in and around the bathroom or bedroom, so I decided to build an Alexa skill and Alexa Voice Service-enabled magic mirror – which I’ve titled the Mystic Mirror.

Continue reading “Building a Magic Mirror using Alexa, AWS, and a Raspberry Pi”

Using Amazon Machine Learning to Predict the Best Time of Day for Exercise – Pt 3: Automating the Model with Alexa

Integration with Alexa allows a user to obtain a workout recommendation (and create a machine learning model) all by voice command.

[su_note note_color=”#d3d3d3″]Note: This is the third post about using Amazon Machine Learning to predict workout intensity. Check out Part 1 (Overview) and Part 2 (Building the Machine Learning Model) for background. A working model is available via web and Alexa. Code can be found/downloaded from my Hackster site.[/su_note]

After I was able to build a working model, I needed to come up a way to automate the model. I originally planned to allow access through my website, but decided to use Alexa in addition to the website link.

Note: The process of creating an Alexa skill isn’t too complicated (if you have experience building lambda functions). That being said, I suggest you start by building a sample skill – such as the Fact Skill example. Also, be sure to read and follow the certification requirements.

Alexa, AWS, and the exposed Fitbit APIs provided a mechanism to build a model and return results for a specific user – all initiated by voice.

Step 1 – Linking the user’s Fitbit account to the skill

A user has to link his/her Fitbit account to the skill before s/he can (a) build a specific machine learning model based on their history and (b) get a workout recommendation. Step 1 covers the logic for this functionality.

Click image to enlarge

Continue reading “Using Amazon Machine Learning to Predict the Best Time of Day for Exercise – Pt 3: Automating the Model with Alexa”