Did you notice that most calendars and timers are missing an important feature. Some information that I personally find most interesting to have readily available.
It’s the information about how much time is left until the next appointment is coming up. Even smartwatches, which should should be jack-of-all-trades in regards of time and schedule, do not display the “time until the next event”.
Now I came across this shortcoming when I started to look for this information. No digital assistant can tell me right away how much time until a certain event is left.
But the connected house also is based upon open technologies, so one can add these kind of features easily ourselves. My major use cases for this are (a) focussed work, plan quick work-out breaks and of course making sure there’s enough time left to actually get enough sleep.
As you can see in the picture attached my watch will always show me the hours (or minutes) left until the next event. I use separate calendars for separate displays – so there’s actually one for when I plan to get up and do work-outs.
Having the hours left until something is supposed to happen at a glance – and of course being able to verbally ask through chat or voice in any room of the house how long until the next appointment gives peace of mind :-).
Weekend is laundry time! The smart house knows and sends out notifications when the washing machine or the laundry dryer are done with their job and can be cleared.
Of course this can all be extended with more sensory data, like power consumption measurements at the actual sockets to filter out specific devices much more accurate. But for simple notification-alerting it’s apparently sufficient to monitor just at the houses central power distribution rack.
On the sides this kind of monitoring and pattern-matching is also useful to identify devices going bad. Think of monitoring the power consumption of a fridge. When it’s compressor goes bad it’s going to consume an increasing amount of power over time. You would figure out the malfunction before it happens.
Same for all sorts of pumps (water, oil, aquarium,…).
All this monitoring and pattern matching the smart house does so it’s inhabitants don’t have to.
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:
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?
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.
“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:
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.
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.
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.
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.
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:
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.
There have been several occasions in the past years that I had to quickly change the MAC address of my computer in order to get proper network connectivity. May it be a corporate network that does not allow me to use my notebook in a guest wifi because the original MAC address is “known” or any other possible reasons you can come up with…
Now this is relatively easy on Mac OS X – you can do it with just one line on the shell. But now there’s an App for that. It’s called Spoof:
“I made this because changing your MAC address in OS X is harder than it should be. The Wi-Fi card needs to be manually disassociated from any connected networks in order for the change to apply correctly – super annoying! Doing this manually each time is tedious and lame.
Instead, just run spoof and change your MAC address in one command. Now for Linux, too!”
“Ever notice how people texting at night have that eerie blue glow?
Or wake up ready to write down the Next Great Idea, and get blinded by your computer screen?
During the day, computer screens look good—they’re designed to look like the sun. But, at 9PM, 10PM, or 3AM, you probably shouldn’t be looking at the sun.
f.lux fixes this: it makes the color of your computer’s display adapt to the time of day, warm at night and like sunlight during the day.
It’s even possible that you’re staying up too late because of your computer. You could use f.lux because it makes you sleep better, or you could just use it just because it makes your computer look better.”
I am a frequent podcast live-stream listener. And being that I am enjoying the awesome service called xenim streaming network.
Any Podcast producer can join the xsn and with that can live-stream his own Podcast while recording. It’s CDN is based on voluntarily provided resources and pretty rock-solid as far as my experience with it goes.
Since I am a frequent user of this – and I’ve got that gorgeous SONOS hardware scattered around my house – I thought I need to have that service integrated into my SONOS set.
The SONOS system knows the concept of “Music Services”. There are quite a lot of them but xsn is missing. But SONOS is awesome and they got an API!
Unfortunately the API documentation is hidden behind a NDA wall so that would be a no-go. What’s not hidden is what the SONOS controllers have to discuss with all the existing services. Most of the time these do not use HTTPS so we’re free to listen to the chatters. I did just that and was able, for the sake of interoperability, to reverse engineer the SONOS SMAPI as far as it is necessary to make my little xsn Music Service work.
Step 1:Start your SONOS Controller Application and find out the IP address of your SONOS.
Click on “About My Sonos System” and check the IP address written next to the “Associated ZP”.
Step 2: Add the xsn Music Service.
By opening a browser window and browsing to: http://<your-associated-zp-ip>:1400/customsd.htm
When you’re there – fill out the fields as below. The SID is either 255, or if you used that previously, something between 240-253. The service name is “xenim streaming network”. The Endpoint URL and Secure Endpoint URL both are http://xsn.schrankmonster.de/xsn
Set the Polling interval to 30 seconds. Click on the Anonymous Authentication SOAP header policy and you’re good to go. Click on “send” to finish.
Step 3: Add the new Music Service to your SONOS Controller.
Click on “Add Music Services” and click through until you see “xenim streaming network”. Add the service and you’re set!
p.s.: It’s normal that the service icon is a question mark.