smart home use case #4 – being location aware is important

Now that you got your home entertainment reacting to you making a phone call (use case #1) as well as your current position in the played audiobook (use case #3) you might want to add some more location awareness to your house.

If your house is smart enough to know where you are, outside, inside, in what room, etc. – it might as well react on the spot.

So when you leave/enter the house:

– turn off music playing – pause it and resume when you come back
– shutdown unnecessary equipment to limit power consumption when not used and start-back up to the previous state (tvs, media centers, lights, heating) when back
– arm the cameras and motion sensors 
– start to run bandwidth intense tasks when no people using resources inside the house (like backing up machines, running updates)
– let the roomba do it’s thing
– switch communication coming from the house into different states since it’s different for notifications, managing lists and spoken commands and so on.

There’s a lot of things that that benefit from location awareness.

Bonus points for outside house awareness and representing that like a “Weasly clock”…“xxx is currently at work”.

Bonus points combo breaker for using an open-source service like Miataru (http://miataru.com/#tabr3) for location tracking outside the house.

use case #3 – sonos auto bookmarker for audiobooks and podcasts

So you’re listening to this audio book for a while now, it’s quite long but really thrilling. In fact it’s too long for you to go through in one sitting. So you pause it and eventually listen to it on multiple devices.

We’ve got SONOS in our house and we’re using it extensively. Nice thing, all that connected goodness. It’s just short of some smart features. Like remembering where you paused and resuming a long audio book at the exact position you stopped the last time. Everytime you would play a different title it would reset the play-position and not remember where you where.

With some simple steps the house will know the state of all players it has. Not only SONOS but maybe also your VCR or Mediacenter (later use-case coming up!).

Putting together the strings and you get this:

Whenever there’s a title being played longer than 10 minutes and it’s paused or stopped the smart house will remember who, where and what has been played and the position you’ve been at.

Whenever that person then is resuming playback the house will know where to seek to. It’ll resume playback, on any system that is supported at that exact position.

Makes listening to these things just so much easier.

Bonus points for a mobile app that does the same thing but just on your phone. Park the car, go into the house, audiobook will continue playback, just now in the house instead of the car. The data is there, why not make use of it?

p.s.: big part of that I’ve opensourced years ago: https://github.com/bietiekay/sonos-auto-bookmarker

“making your home smarter”, use case #2 – measure how much oil is burned

“making your home smarter”, use case #2

know how much oil your house burns with just measuring the light of the furnace going on/off and calculating oil throughput of the valves with burn-time.

Over the period of 1 year it’s as accurate as +/- 20 liters of oil.

That way you do not have to climb down into the storage space and measure it yourself…smelly job that is.

carbon neutral house – when the sun is shining.

7 day and 30 day graphs for solar power generation, power consumption, oil burn to heat water and outside temperatures to go along with.

Having everything in a time-series-database makes such things a real blast… data wandering around all the telemetry. There are almost 300 topics to pick from and combine.

Yes, generally the solar array produces more than the whole household consumes. Except that one 26th.

Thinking about building a display showing when we are closing in to consume what has been produced in terms of electricity… something like a traffic light getting more red towards the use-up of electricity generated carbon-neutral.

How to weigh your cat! – the IoT version

This is Leela. She is a 7 year old lilac white British short hair cat that lives with us. Leela had a sister who used to live with us as well but she developed a heart condition and passed away last year. Witnessing how quickly such conditions develop and evaluate we thought that we can do something to monitor Leelas health a bit to just have some sort of pre-alert if something is changing.

Kid in a Candystore

As this Internet of Things is becoming a real thing these days I found myself in a candy store when I’ve encountered that there are a couple of really really cheap options to get a small PCB with input/output connectors into my house WiFi network.

One of the main actors of this story is the so called ESP8266. A very small and affordable system-on-a-chip that allows you to run small code portions and connect itself to a wireless network. Even better it comes with several inputs that can be used to do all sorts of wonderful things.

And so it happened that we needed to know the weight of our cat. She seemed to get a bit chubby over time and having a point of reference weight would help to get her back in shape. If you every tried to weigh a cat you know that it’s much easier said than done.

The alternative was quickly brought up: Build a WiFi-connected scale to weigh her litter box every time she is using it. And since I’ve recently bought an evaluation ESP8266 I just had to figure out how to build a scale. Looking around the house I’ve found a broken human scale (electronics fried). Maybe it could be salvaged as a part donor?

A day later I’ve done all the reading on that there is a thing called “load-cell”. Those load cells can be bought in different shapes and sizes and – when connected to a small ADC they deliver – well – a weight value.

I cracked the human scale open and tried to see what was broken. It luckily turned out to have completely fried electronics but the load-cells where good to go.

Look at this load cell:

Hardware

That brought down the part list of this project to:

  • an ESP8266 – an Adafruit Huzzah in my case
  • a HX711 ADC board to amplify and prepare the signal from the load-cells
  • a human scale with just enough space in the original case to fit the new electronics into and connect everything.

The HX711 board was the only thing I had to order hardware wise – delivered the next day and it was a matter of soldering things together and throwing in a small Arduino IDE sketch.

My soldering and wiring skills are really sub-par. But it worked from the get-go. I was able to set-up a small Arduino sketch and get measurements from the load-cells that seemed reasonable.

Now the hardware was all done – almost too easy. The software would be the important part now. In order to create something flexible I needed to make an important decision: How would the scale tell the world about it’s findings?

Software

Two basic options: PULL or PUSH?

Pull would mean that the ESP8266 would offer a webservice or at least web-server that exposes the measurements in one way or the other. It would mean that a client needs to poll for a new number in regular intervals.

Push would mean that the ESP8266 would connect to a server somewhere and whenever there’s a meaningful measurement done it would send that out to the server. With this option there would be another decision of which technology to use to push the data out.

Now a bit of history: At that time I was just about to re-implement the whole house home automation system I was using for the last 6 years with some more modern/interoperable technologies. For that project I’ve made the decision to have all events (actors and sensors) as well as some additional information being channeled into MQTT topics.

Let’s refer to Wikipedia on this:

“MQTT1 (formerly MQ Telemetry Transport) is an ISO standard (ISO/IEC PRF 20922) publish-subscribe-based “lightweight” messaging protocol for use on top of the TCP/IP protocol. It is designed for connections with remote locations where a “small code footprint” is required or the network bandwidth is limited. The publish-subscribe messaging pattern requires a message broker. Thebroker is responsible for distributing messages to interested clients based on the topic of a message. Andy Stanford-Clark and Arlen Nipper of Cirrus Link Solutions authored the first version of the protocol in 1999.”

Something build for oil-pipelines can’t be wrong for your house – can it?

So MQTT uses the notation of a “topic” to sub-address different entities within it’s network. Think of a topic as just a simple address like “house/litterbox/weight”. And with that topic MQTT allows you to set a value as well.

The alternative to MQTT would have been things like WebSockets to push events out to clients. The decision for the home-automation was done towards MQTT and so far it seems to have been the right call. More and more products and projects available are also focussing on using MQTT as their main message transport.

For the home automation I had already set-up a demo MQTT broker in the house – and so naturally the first call for the litterbox project was to utilize that.

The folks of Adafruit provide the MQTT library with their hardware and within minutes the scale started to send it’s measurements into the “house/litterbox/weight” topic of the house MQTT broker.

Some tweaking and hacking later the litterbox was put together and the actual litterbox set on-top.

Since Adafruit offers platform to also send MQTT messages towards and create neat little dashboards I have set-up a little demo dashboard that shows a selection of data being pushed from the house MQTT broker to the Adafruit.io MQTT broker.

These are the raw values which are sent into the weight topic:

You can access it here: https://io.adafruit.com/bietiekay/stappenbach

So the implementation done and used now is very simple. On start-up the ESP8622 initialises and resets the weight to 0. It’ll then do frequent weight measurements at the rate it’s configured in the source code. Those weight measurements are being monitored for certain criteria: If there’s a sudden increase it is assumed that “the cat entered the litterbox”. The weight is then monitored and averaged over time. When there’s a sudden drop of weight below a threshold that last “high” measurement is taken as the actual cat weight and sent out to a /weight topic on MQTT. The regular measurements are sent separately to also a configurable MQTT topic.

You can grab the very ugly source code of the Arduino sketch here: litterbox_sourcecode

And off course with a bit of logic this would be the calculated weight topic:

Of course it is not enough to just send data into MQTT topics and be done with it. Of course you want things like logging and data storage. Eventually we also wanted to get some sort of notification when states change or a measurement was taken.

MQTT, the cloud and self-hosted

Since MQTT is enabling a lot of scenarios to implement such actions I am going to touch just the two we are using for our house.

  1. We wanted to get a push notification to our phones whenever a weight measurement was taken – essentially whenever the cat has done something in the litterbox. The easiest solution: Set-Up a recipe on If This Than That (IFTTT) and use PushOver to send out push notifications to whatever device we want.
  2. To log and monitor in some sort of a dashboard the easiest solution seemed to be Adafruits offer. Of course hosted inside our house a combination of InfluxDB to store, Telegraf to gather and insert into InfluxDB and Chronograf to render nice graphs was the best choice.

Since most of the above can be done in the cloud (as of: outside the house with MQTT being the channel out) or inside the house with everything self-hosted. Some additional articles will cover these topics on this blog later.

There’s lots of opportunity to add more logic but as far as our experiments and requirements go we are happy with the results so far – we now regularly get a weight and the added information of how often the cat is using her litterbox. Especially for some medical conditions this is quite interesting and important information to have.

the xenim streaming network SONOS integration now plays recent shows!

 

 

 

Since I am frequently using the xenim streaming network service but I was missing out on the functionality to replay recent shows. With the wonderful functionality of Re-Live made available through ReliveBot  I have now added this replay feature and I am using it a lot since.

Within the SONOS controller app it looks like this:

Screen Shot 2015-07-31 at 14.22.13

IMG_3551

To set-up this service with your SONOS set-up just follow the instructions shown here: a new Music Service for SONOS

Source 1: xenim streaming network
Source 2: ReliveBot
Source 3: Download the Custom Service
Source 4: a new Music Service for SONOS

Stitch Panoramic Views like a pro

I am using this for more several years now. Even though all my workflow happens on Macintosh computers these days I’ve kept this tool in my toolbox: Microsoft Image Composite Editor.

Screen Shot 2015-03-08 at 19.00.47

 

Now after along while with the 1.0 version Microsoft Research decided to release a new version of the free tool with even more features and a new streamlined user interface. This is so much better than before.

[youtube]https://www.youtube.com/watch?v=zhdXLH2GYPA[/youtube]

“Image Composite Editor (ICE) is an advanced panoramic image stitcher created by the Microsoft Research Computational Photography Group. Given a set of overlapping photographs of a scene shot from a single camera location, the app creates a high-resolution panorama that seamlessly combines the original images. ICE can also create a panorama from a panning video, including stop-motion action overlaid on the background. Finished panoramas can be shared with friends and viewed in 3D by uploading them to the Photosynth web site. Panoramas can also be saved in a wide variety of image formats, including JPEG, TIFF, and Photoshop’s PSD/PSB format, as well as the multiresolution tiled format used by HD View and Deep Zoom.”

Source 1: http://research.microsoft.com/en-us/um/redmond/projects/ice/

I wish there was: cheap network microphones with open source speech recognition

I was on a business trip the other day and the office space of that company was very very nice. So nice that they had all sorts of automation going on to help the people.

For example when you would run into a room where there’s no light the system would light up the room for you when it senses your presence. Very nice!

There was some lag between me entering the room, being detected and the light powering up. So while running into a dark room, knowing I would be detected and soon there would be light, I shouted “Computer! Light!” while running in.

That StarTrek reference brought an old idea back that it would be so nice to be able to control things through omnipresent speech recognition.

I am aware that there’s Siri, Cortana, Google Now. But those things are creepy because they involve external companies. If there are things listening to me all day every day, I want them to be within the premise of the house. I want to know exactly down to the data flow what is going on and sent where. I do not want to have this stuff leave the house at any times. Apart from that those services are working okayish but well…

Let alone the hardware. Usually the existing assistants are carried around in smart phones and such. Very nice if you want to touch things prior to talking to them. I don’t want to. And no, “Hey Siri!” or “OK Google” is not really what I mean. Those things are not sophisticated enough yet. I was using “Hey Siri!” for less than 24 hours. Because in the first night it seemed to have picked up something going on while I was sleeping which made it go full volume “How can I help!” on me. Yes, there’s no “don’t listen when I am sleeping” thing. Oh it does not know when I am sleeping. Well, you see: Why not?

Anyway. What I wish there was:

  • cheap hardware – a microphone(-array) possibly to put into every room. It either needs to have WiFi or LAN. Something that connects it to the network. A device that is carried around is not enough.
  • open source speech recognition – everything that is collected by the microphone is processed through an open source speech recognition tool. Full text dictation is a bonus, more importantly heavy-duty command recognition and simple interactions.
  • open source text to speech – to answer back, if wanted

And all that should be working on a basic level without internet access. Just like that.

So? Any volunteers?

31st Chaos Communication Congress

 

Like every year the Chaos Communication Congress gathered thousands of people in one place between the Christmas-Holidays and NewYears.

Since I was out-of-order this year to attend I’ve opted for the Attending-by-Stream option. All Lectures are live-streamed by the awesome CCC Video Operations Center (C3VOC) and made available as recordings afterwards.

Since the choice of topics is enormous here are some I can recommend:

Source 1: http://events.ccc.de/congress/2014/wiki/Static:Main_Page
Source 2: http://en.wikipedia.org/wiki/Chaos_Communication_Congress
Source 3: http://c3voc.de/
Source 4: http://media.ccc.de/browse/congress/2014/