Thursday, May 29, 2014

Smoking Meat and Power Usage

I have an electric smoker.  Why electric?  Well, I got tired of running out of fuel during long smokes and decided to just break with tradition and increase the technology.   But, I've wondered for a long time how much power these things use.  Sure there's a label on them, and they're almost always wrong in my experience.

Wait though, I have this cool Iris switch that measures power, and I have charting tools, and I have cloud storage.  Let's take a look:

It uses around 800 watts when it's on and nothing when it's off.  After a start up period of about 20 minutes it settles into a regular cycle that varies around three minutes on and three off that expands to longer off times as the food inside rises in temperature.  If I had run it longer, I suspect the off times would have stabilized to periods approaching 10 minutes.

So, the device doesn't use a lot of power for something that keeps wood smoldering to cook and flavor food, but it could be death on my 'Demand' number for the month.  An extra 800 Watts added to my base usage during this time of year would probably push me up over 2kW and cost around $15 more on my power bill (I usually run around 1.6 kW this time of year).

For you folk that don't have demand billing, this looks like it would be .45 kW for each hour of usage on average if you ran it for 4 hours or more.  Not too bad for smoking food, your dryer uses a heck of a lot more than that.  Just to illustrate how this can combine with normal house electrical usage, take a look at my overall usage during this same period:

This makes it look like I'm a total power hog.  My usage tops out around 17 kW and jumps over 10kW several times during the morning.  That's what happens when you're doing laundry; the dryer is chewing up almost 8kW by itself when the element is on, the washing machine motor eats it fair share, the swimming pool filter is running on high, and the smoker is stinking up the area.  This is life though, we have to figure out how to deal with it and not let the power company take away our savings.

Notice that everything shuts off at noon?  Yep, I carefully shut things down to prevent the demand billing system from eating me alive.  Actually, that's what this site was started for; back before I wandered off into anti-siphon faucets, rattlesnakes, acid handling, battery maintenance and such.  Funny how things take on a life of their own.

It looks like smoking will be reserved for nights and weekends.

Tuesday, May 27, 2014

Voice Recognition on the Raspberry Pi - Reality Check

My recent experience with voice control on the Pi got me to thinking.  Why wasn't this a rising star and constantly being talked about?  The idea of talking to your house is so compelling that there must be hundreds of implementations out there.

Well, there are, and none of them work very well.

I described my experience with Jasper, it just didn't live up to the hype.  So I went looking and did some experimenting.  Everyone talks about how good Siri is.  My experience with it is far less than stellar; all the phones I've tried it on misunderstand me about 6 out of 10 times.  Google's implementation seems to work better and I get about an 80% success rate.  Both of these are stellar compared to several software techniques I tried out, with the absolute worst being CMU Sphinx that Jasper was based on.

Remember, I'm looking at this as a way to control my house with a little computer, not dictate letters wearing a headset, so let me talk a bit about methods.  No, I'm not going to bore the heck out of you with a dissertation on the theories of voice recognition, I want what everyone else wants: I want it to work.  There are basically two methods of doing speech recognition right now, local and distributed.  By local I mean totally on one machine, and distributed is when they send the sound over the internet and decode it somewhere else.  Google's voice API is an example of distributed and CMU Sphinx is an example of local.

What we all want is for it to operate like Star Trek:


Nice clear beep

"Turn on the porch lights"

Nice clear acknowledgement, and maybe a, "Porch light is now on."

I went through the entire process of bringing up CMU Sphinx <link>, and when I tried it, I saw something on the order of, "Burn under the blight."  To be fair, Sphinx can be trained and its accuracy will shoot way up, but that takes considerable effort and time.  The default recognition files just don't cut it.  Especially when I tried the same thing with 100%, yes totally accurate results with Google's voice interface.  The problem with Google's interface is that it only works in the Chrome browser.  Yes, there are tools out there that use the Google voice API; notably VoiceCommand by Steve Hickson <link> , but expect it to quit working soon.  Google ended their offering of version 2 of the interface, and version three is limited in how many requests can be used and you have to have a special key to use it.  Thus will end a really cool possibility, I hope they bring it back soon.

So, the local possibilities are inaccurate and the distributed are accurate, but the one everyone was using is likely to disappear.  There are other distributed solutions, I brought up code taken from Nexiwave <link> and tested it.  There was darn near a 100% success rate.  The problem was delay.  Since I was using a free account, I was shuffled to the bottom of the queue (correctly and expectedly) so the response took maybe three seconds to come back.  Now, three seconds seem like a small price to pay, but try it out with a watch to see how uncomfortable that feels in real use.  This is not that Nexiwave is slow, it's that the dog gone internet takes time to send data and get back a response.  I didn't open a paid account to see if it was any better, this was just an experiment.

But, think about it a bit.  "Computer,"  one thousand and one, one thousand and two, one thousand and three, "Yes".  Then the command, "Turn on the porch light", etc.  It would be cool and fun to show off, but do you really want to do it that way?  Plus it would require that the software run continuously to catch the occasional, "Computer" command initiation.  Be real, if you're going to have to push a button to start a command sequence, you might as well push a button to do the entire action.  Remember, you have to have a command initiator or something like, "Hey Jeff, get your hand out of the garbage disposal, it could turn on," could be a disaster.  A button somewhere labeled, "Garbage Disposal," would be much simpler and safer.

Don't talk to me about Dragon Naturally Speaking from Nuance <link>.  That tool is just unbelievable.  It is capable of taking dictation at full speed with totally amazing accuracy, but it only runs on machines much larger than a Pi, and not at all under Linux.  Even their development version is constructed for Windows server machines.  Microsoft has a good speech recognition system built right into the OS, and under Windows 8, it is incredible.  Especially at no additional cost at all.  But, there aren't many Raspberry Pi machines running Windows 8.

Thus, I don't have a solution.  The most compelling one was Nexiwave, but the delays are annoying and I don't think it would work out long term.  Here's the source I used to interface with it:


# Copyright 2012 Nexiwave Canada. All rights reserved.
# Nexiwave Canada PROPRIETARY/CONFIDENTIAL. Use is subject to license terms.

import sys, os, json, urllib2, urllib, time

# You will need python-requests package. It makes things much easier.
import requests

# Change these:
# Login details:

def transcribe_audio_file(filename):
    """Transcribe an audio file using Nexiwave"""
    url = '' + USERNAME +'/recording/?authData.passwd=' + PASSWORD + '&auto-redirect=true&response=application/json'

    # To receive transcript in plain text, instead of html format, comment this line out (for SMS, for example)
    url = url + '&transcriptFormat=html'

    # Ready to send:
    sys.stderr.write("Send audio for transcript with " + url + "\n")
    r =, files={'mediaFileData': open(filename,'rb')})
    data = r.json()
    transcript = data['text']
    # Perform your magic here:
    print "Transcript for "+filename+"=" + transcript

if __name__ == '__main__':
    # Change this to your own
    filename = "/data/audio/test.wav"
I took this directly from their site and posted it here because it is hard to find, and I don't think they care if I advertise for them.  All I did to make it work was to sign up for a free account and enter my particulars in the fields up at the top.  It worked first try; simple and easy interface.  It would be relatively easy to adapt this to a voice control system on my Pi if I decided to go that way.  Which I may do for control in the dark of my bedroom where I don't want to search for a remote that may be behind the side table.

The audio file I sent was my usual, "Porch light on," and it decoded it exactly first try.  I tried a few others and they all worked equally well.  Which brings up another item, sound on the raspberry Pi.  Frankly, unless you're dealing with digital files and streams, it sucks.  There isn't enough filtering on the Pi to keep audio hum out of things.  The amplified speakers I was using had a constant low level hum (regular ol' 60 hertz hum), and it would get into the audio captured from the USB microphone as well.  This could have been reduced by an expensive power supply with very good filtering, or maybe not; I didn't try.

To add insult to an already injurious process, ALSA (Advanced Linux Sound Architecture) is the single most confusing sound implementation I've ever seen.  It was constructed by sound purists and technology students so it is filled with special cases, odd syntax, devices that mostly work, etc.  The documentation is full of 'try this'.  What?  I love experimenting, but I sort of like to have documentation that actually has information in it.  Pulse audio is another possibility, but I'll approach that some other time.  Maybe a few weeks after hell freezes over, ALSA was bad enough.  But, if you're going to experiment with sound under Linux, you'll have to deal with ALSA at some point.  Especially if you actually want to turn the volume up or down.

I think I'm going to do some research on remote control ergonomics.  There's got to be a cool and actually useful way to turn on the porch lights.

Sunday, May 25, 2014

Jasper for voice commands

I'm rapidly getting to the point that I need to have a simple remote control that I can use around the house.  I've thought about several possibilities, but I ran across Jasper <link> and that would be so cool.  A house that I can talk to.

On their site, they have a great video of the microphone setting a few meters away and the authors gleefully giving it commands and listening to the responses.  I could make a few of these and scatter them around the house to control things by voice; that would really be nice.  Very slick site and seemingly well documented.

So, looking at the directions, they have a pretty complex system that installs voice recognition and speech capabilities on the Pi.  I decided to try it out.  Since their image file is most likely configured differently than what I use, I decided to do the full installation ... DON'T DO THIS.  Their instructions leave a lot of tiny little things out, like what directory to be in when you do things, how long the various steps can take, how freaking big it is.  Y'know things like that.

After 26 hours of installs, updates, compiles (some of which failed) and a whole lot of head scratching, I just gave up.  I still wanted to try it out, so I downloaded their disk image and installed it on my Pi.  After spending quite a while messing around, I still couldn't get it to respond to a command or hear what it was saying; obviously there was something wrong with the audio setup.  The authors used ALSA (google it) so I started digging into it to see how to test the audio.  After changing the terminal interface on Putty several times, I discovered that my alsamixer settings were all set to the minimum.  After jacking up the input gain and the output volume, I managed to get sound into and out of Jasper.

Then the disappointments really began.  I couldn't recognize my voice most of the time, when it did manage to get it, it was mostly wrong.  "What is the meaning of life," one of the built in commands, would check my mail.  Interesting, but not what I expected.  It would do the time pretty well, but most everything else would cause an exception in the python script that was running.  Sometimes, it would fail so bad the Pi actually crashed.  Nothing has done that to me before.  Remember, this is a disk image, I didn't change anything; it failed right out of the box.  The voice synthesis was really, really hard to understand, and playing over and over again didn't seem to help.  My ears just weren't training to the odd sound.  Sort of like the Pi had a really bad cold and couldn't quite get the words out.

I didn't expect it to work like the movies, but c'mon, it should at least be as good as the videos they produced to show it off.  I even used the exact same microphone they show on their site and some really good powered speakers.  I can't blame the hardware at all.

So, I know there are a number of folk out there that installed this and got it to work.  There always are, but obviously, they didn't build it on their Pi, because that simply doesn't work, and not many people have days to waste compiling thousands of source files.  So, they must have used the image, but what the heck did they do to get it to understand them?  Similarly, how the heck did they understand what was being said by the software.  A series of beeps would have been better.

A few hours spent looking at various things on the web didn't reveal any secrets to make this work.  Instead, I found a significant number of people that hadn't been able to make it perform.  There didn't seem to be any solutions either.  There were a lot of, "I think," or "Maybe you can try," and "Have you tried;" but I discount most of those since they are simply guesses.  I didn't find anyone that was bragging about their success; that is very telling.  I'm not willing to dig into it because the vagaries of ALSA are daunting enough without having to delve into the secret and mysterious world of PocketSphinx (the recognition system they use).  I'm not interested in a new career.

I'm burning my original software back on the Pi's card right now so I can try something else.  For you folk out there that want to try it, I certainly hope you have better luck than I did.

Thursday, May 22, 2014

Hooking HighCharts Into My House

If you prowl around this blog very long you'll run into a bunch of charts.  I've experimented with several cloud services for storing data and shown examples of my own data using their charting provisions.  All of them are cool, but some of them leave a little bit to be desired.  For example, Xively uses Rickshaw <link>, and it's a nice package, but the Xively implementation is too darn complex for my taste.  If you look at the various cloud providers, they all have their favorites.

Up until now I've been using the Google graph API for my own stuff, but the problem is that Google Graph uses Flash.  Cell phones don't like Flash very much.  That means my home graphs don't work on my phone.  I absolutely can't let that continue any longer, and since my favorite cloud provider, Grovestreams <link>, uses HighCharts <link>, I stole their example and developed my own graph using the same library.

Hey, they stole my idea for the SteelSeries gauges, turn about is only fair play.

But, as usual, it was an exercise in patience.  The documentation on HighCharts is voluminous; it goes on forever and ever with tons of examples and links into JFiddle <link> so the ideas and stuff can be experimented with; talk about information overload.  It's also tough to figure out how the set the various properties in the right place to get things done, and none of the examples did exactly what I needed.  That's why patience was required.  I didn't want to get disgusted with it and just give up.

I finally got one working.  If you put your pointer inside the chart, you can get the actual reading of any point.  If you click, drag across the chart, you can zoom in and see it closer.  If you have a touch screen, you can use the 'pinch' and 'expand' to zoom in and out; when your zoomed in, you can slide the chart right and left to see the data.  By clicking on the labels at the bottom, you can turn off one of the series to make the remaining one more clear.  I could put up a lot of things to examine and choose which one by turning the others off.  I'm not sure I like the colors yet, but they're easy to change.

The beauty of this chart is that it's totally javascript.  That means it works on the phone, so I can add it to the Android app I have:

OK, the chart looks silly.  But look what happens when you turn the phone into portrait mode:

Is that slick or what?  Using the touchscreen I can zoom around it and select points to my hearts content.

The data shown is taken from my legacy feed on Xively and was reasonably easy to grab.  The only real problems I had getting it going was prowling through the documentation on HighCharts; it was all there, but like finding a needle in a haystack.

If you want to steal my example and modify it for your own use, it's on GitHub, drop a comment here and I'll post the link.

Wednesday, May 14, 2014

Wemo Devices Are Getting Interesting Now

Previous posts about the Wemo light switch: Part 1, Part 2

I'm not one of those guys that gathers tech news items and reposts them to increase my page views or hits, but this is going to be an exception.  I was prowling around looking for ideas for a particular problem I'm having with the Wemo devices I have and ran across a cool news item <link>.  Basically, it says that Belkin is expanding their line of WiFi controlled devices to include light bulbs, slow cookers, coffee makers, humidfiers, and who knows what else.

This is so cool.  Imagine, a coffee pot with an internet address.

I thought I'd capture a picture from a 'coming soon' article that really caught my eye:

I stole the picture and put it here because the advertisement will probably disappear soon.  The link is from the CrockPot web site <link>, and is for a Wemo based slow cooker that is going on my 'gottahavethatthing' list.  Being a widower, I use a slow cooker a lot and this would be great to have.

But look, space heaters, humidifiers, coffee makers, what will they think of next?  Sure, I use things like this to control or monitor a lot of devices and I could probably build my own remote controlled coffee maker, but the neighbors can't.  Now, they can just buy it.

So, it looks like Belkin is in this marketplace big time.  They actually published their API for Android (yes, I downloaded it) so other people can get into the arena.  With the library work in Python and several other languages, the home hacker can start building nice controls for their own use.  Normal folk can use the free phone app and do much the same with no work (or personal satisfaction).

Home automation is looking better all the time.