blog maintenance – status

A bit of feedback is in on the plan to revitalize this blog. Thanks for that!

I have spent some more time this weekend on getting everything a bit tidied up.

There is the archive of >3.000 posts that I plan to review and re-categorize.

There is the big number of comments that had been made in the past and that I need to come up with a plan on how to allow/disallow/deal with comments and discussions in general on this website.

There is also the design and template aspects of this website. I switched to a different template and started to adjust it so that it shall make access to the stream of posts as easy as possible. Until then you need to wait or contact me through other means. But contacting is another post for another time.

resilvering …

The last Ubuntu kernel update seemingly kicked two hard disks out of a ZFS raidz – sigh. With ZFS on Linux this poses an issue:

Two hard drives that previously where in this ZFS pool named “storagepool” where reassigned a completely different device-id by Linux. So /dev/sdd became /dev/sdf and so on.

ZFS uses a specific metadata structure to encode information about that hard drive and it’s relationship to storage pools. When Linux reassigned a name to the hard drive apparently some things got shaken up in ZFS’ internal structures and mappings.

The solution was these steps

  • export the ZFS storage pool (=taking it offline for access/turning it off)
  • use the zpool functionality “labelclear” to clear off the data partition table of the hard drives that got “unavailable” to the storage pool
  • import the ZFS storage pool back in (=taking it online for access)
  • using the replace functionality of zpool to replace the old drive name with the new drive name.

After poking around for about 2 hours the above strategy made the storage pool to start rebuilding (resilvering in ZFS speak). Well – learning something every day.

4+ hours to go.

Bonus: I was not immediately informed of the DEGRADED state of the storage pool. That needs to change. A simple command now is run by cron-tab every hour.

zpool status -x | grep state: | tr –delete state: |mosquitto_pub -t house/stappenbach/server/poppyseeds/zpool -l

This pushes the ZFS storage pool state to MQTT and get’s worked on by a small NodeRed flow.

taking the social stream back to this blog

I am currently in the process of reducing my presence on the usual social networks. Here is my reasoning and how I will do it.

Facebook, Twitter, Instagram and alike are seemingly at the peak of their popularity and more and more users get more and more concerned about how their data and privacy is handled by those social networks. So am I.

Now my main concern is not so much on the privacy side. I never published anything on a social network – private or public – that I would not be published or freely distributed/leak. But:

I have published content with the intention that it would be accessible to everyone now and in the future. The increasing risk is that those publishing platforms are going to fade away and thus will render the content I had published there inaccessible.

My preferred way of publishing content and making sure that it stays accessible is this website – my personal blog.

I am doing this since 2004. The exact year that Facebook was founded. And apparently this website and it’s content has a good chance of being available longer than the biggest social network at the present time.

So what does this mean? 3 basic implications:

  1. I will become a “lurker” on the social networks. Now and in the future.
  2. All comments and reactions I will make will be either directly in private or through my personal website publicly available and linkable.
  3. I will minimize my footprint on the social networks as much as possible. This for example means: If I use Twitter, all tweets will live 7 days and automatically be removed after this time. Deleting your tweets automatically is something others do as well.

As you can see: This is not about a cut or abstinence. I get information out of social networks, tweet message flows. But I do not put any trust in the longevity of both the platforms and the content published there.

The next steps for me will be a complete overaul of this website. Get everything up to current standards to streamline my publishing process.

Expect a lot of content and change – and: welcome to my blog!

Converting ひらがな to “hiragana” and カタカナ to “katakana” – Romaji command line tool

I had this strange problem that my car was not able to display japanese characters when confronted with them. Oh the marvels of inserting a USB stick into a car from 2009.

stupid BMW media player without proper font

Now there’s no real option I know of without risking to brick the car / entertainment system of the car to get it to display the characters right.

Needless so say that my wifes car does the trick easily – of course it’s an asian car!

Anyway. I wrote a command line tool using some awesome pre-made libraries to convert Hiragana-Katakana characters to their romaji counterpart. 

You can find it on github: https://github.com/bietiekay/romaji 

Join me implementing a neural network to improve accuracy of an OpenSource indoor location tracking system

To all techies reading this:

GIST: I am looking for interested hackers who want to help me implement a neural network that improves the accuracy of bluetooth low energy based indoor location tracking.

Longer version:

I am currently applying the last finishing touched to a house wide bluetooth low energy based location tracking system. (All of which will be opensourced)

The system consists of 10+ ESP-32 Arduino compatible WiFi/Bluetooth system-on-a-chip. At least one per room of a house.

These modules are very low powered and have one task: They scan for BLE advertisements and send the mac and manufacturer data + the RSSI (signal strength) over WiFi into specific MQTT topics.

There is currently a server component that takes this data and calculates a probable location of a seen bluetooth low energy device (like the apple watch I am wearing…). It currently is using a calibration phase to level in on a minimum accuracy. And then simple calculation matrices to identify the most probable location.

This all is very nice but since I got interested in neural networks and KI development – and I think many others might as well – I am asking here for also interested parties to join the effort.

I do have an existing set-up as well as gigabytes of log data.

I know about previous works like „Indoor location tracking system using neural network based on bluetooth

Now I am totally new to the overal concepts and tooling and I start playing with TensorFlow right now.

If you want to join, let me know by commenting!

Source: http://ieeexplore.ieee.org/document/7754772/

making your home smarter use case #14 – prevent fires while charging LiPo batteries

Did you know how dangerous Lithium-Polymer batteries can be? Well, if not treated well they literally burst in flames spontaneously.

So it’s quite important to follow a couple of guidelines to not burn down the house.

Since I am just about to start getting into the hobby of FPV quadcopter racing I’ve tried follow those guidelines and found that the smart house can help me tracking things.

Unfortunately there are not a lot of LiPo chargers available at reasonable price with computer interfaces to be monitored while charging/discharging the batteries. But there are a couple of workarounds I’ve found useful.

  1. a proper case. I’ve got myself one of those “Bat-Safe” boxes that fit a couple of battery packs and help me store them safely. Even if one or many burst into flames the case is going to contain any heat and fire as good as possible and with the air / pressure filter it’ll hopefully get rid of most of the very nasty smoke (I hear). Cables go into it, so the actual charging process takes place with everything closed and latched.
  2. the obvious smoke detector which is on it’s own connected to the overall fire alarm is mounted on top, like literally on top. It’ll send out the alert to all other smoke alarms in the house making them go beep as well as sending out high priority push notifications to everyone.
  3. an actual camera is monitoring the box all the time calling on alerts if something is fishy (like making sound, smoke, movement of any sort). When charging is done the charger will beep – this is being caught by the cameras microphones and alerts are sent out.
  4. the temperature inside the case is monitored all the time. The surrounding temperatures are usually pretty stable as this case is stored in my basement and as the charging goes on the temperatures inside the case will climb up and eventually level out and fall when charging / discharging is done. Now the system basically will look at the temperatures, decide wether it’s rising of falling and alerting appropriately.

There’s a couple more things to it, like keeping track of charging processes in a calendar as you can see in the flowchart behind all the above.

making your home smarter use case #13 – correlations happen

There are a lot of things that happen in the smart house that are connected somehow.

And the smart house knows about those events happening and might suggest, or even act upon the knowledge of them.

A simple example:

In our living room we’ve got a nice big aquarium which, depending on the time of the day and season, it is simulating it’s very own little dusk-till-dawn lightshow for the pleasure of the inhabitants.
Additionally the waterquality is improved by an air-pump generating nice bubbles and enriching the water with oxygen. But that comes a cost: When you are in the room those bubbles and the hissing sound of the inverter for the “sun” produces sounds that are distracting and disturbing to the otherwise quiet room.

Now the smart home comes to the rescue:

It detects that whenever someone is entering the room and staying for longer, or powering up the TV or listening to music. Also it will log that regularly when these things happen also the aquarium air and maybe lights are turned off. Moreso they are turned back on again when the person leaves.

These correlations are what the smart house is using to identify groups of switches, events and actions that are somehow tied together. It’ll prepare a report and will recommend actions which at the push of a button can become a routine task always being executed when certain characteristics are lining up.

And since the smart house is a machine, it can look for correlations in a lot more dimensions a human could: Date, Time, Location, Duration, Sensor and Actor values (power up TV, Temperature in room < 22, Calendar = November, Windows closed => turn on the heating).

“making your home smarter” – use case #12 – How much time do I have until…?

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 :-).

 

“making your home smarter”, use case #11 – money money money

The Internet of Things might as well become your Internet of Money. Some feel the future to be with blockchain related things like BitCoin or Ethereum and they might be right. So long there’s also this huge field of personal finances that impacts our lives allday everyday.

And if you get to think about it money has a lot of touch points throughout all situations of our lifes and so it also impacts the smart home.

Lots of sources of information can be accessed today and can help to stay on top of the things going on as well as make concious decisions and plans for the future. To a large extend the information is even available in realtime.

– cost tracking and reporting
– alerting and goal setting
– consumption and resource management
– like fuel oil (get alerted on price changes, …)
– stock monitoring alerting
– and more advanced even automated trading
– bank account monitoring, in- and outbound transactions
– expectations and planning
– budgetting

After all this is about getting away from lock-in applications and freeing your personal financial data and have a all-over dashboard of transactions, plans and status.

“making your home smarter”, use case #10 – Fire and Water alarm system

Water! Fire! Whenever one of those are released uncontrolled inside the house it might mean danger to life and health.

Having a couple of fish and turtle tanks spread out in the house and in addition a server rack in the basement it’s important to know when there’s a leak of water at moments notice.

As the server-room also is housing some water pumps for a well you got all sorts of dangers mixed in one location: Water and Fire hazard.

To detect water leaks all tanks and the pumps for the well are equipped with water sensors which send out an alerting signal as soon as water is detected. This signal is picked up and pushed to MQTT topics and from there centrally consumed and reacted upon.

Of course the server rack is above the water level so at least there is time to send out alerts while even power is out for the rest of the house (all necessary network and uplink equipment on it’s own batteries).

For alerting when there is smoke or a fire, the same logic applies. But for this some loud-as-hell smoke detectors are used. The smoke detectors interconnect with each other and make up a mesh for alerting. If one goes off. All go off. One of them I’ve connected to it’s very own ESP8266 which sends a detected signal to another MQTT topic effectively alerting for the event of a fire.

In one of the pictures you can see what happened when the basement water detector did detect water while the pump was replaced.

“making your home smarter”, use case #9 – weights about to drop

A lot of things in a household have weight, and knowing it’s weight might be crucial to health and safety.

Some of those weight applications might tie into this:

– your own body weight over a longer timespan
– the weight of your pets, weighed automatically (like on a kitty litter box)
– the weight of food and ingredients for recipes as well as their caloric and nutrition values
– keeping track of fill-levels on the base of weights

All those things are easily done with connected devices measuring weights. Like the kitty-litter box at our house weighing our cat every time. Or the connected kitchen-scale sending it’s gram measurements into an internal MQTT topic which is then displayed and added more smarts through an App on the kitchen-ipad consuming that MQTT messages as well as allowing recipe-weigh-in functions.

It’s not only surveillance but pro-active use. There are beekeepers who monitor the weight of their bee hives to see what’s what. You can monitor all sorts of things in the garden to get more information about it’s wellbeing (any plants, really).

“making your home smarter”, use case #8 – it’s all about the power consumption

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.

“make your home smarter”, use case #7 – hear that doorbell ringing!

We love music. We love it playing loud across the house. And when we did that in the past we missed some things happening around.

Like that delivery guy ringing the front doorbell and us missing an important delivery.

This happened a lot. UNTIL we retrofitted a little PCB to our doorbell circuit to make the house aware of ringing doorbells.

Now everytime the doorbell rings a couple of things can take place.

– push notifications to all devices, screens, watches – that wakes you up even while doing workouts
– pause all audio and video playback in the house
– take a camera shot of who is in front of the door pushing the doorbell

And: It’s easy to wire up things whatever those may be in the future.

“make your home smarter”, use case #6 – calendars and scheduls

So how do you manage all these sensors and switches, and lights, and displays and speakers…

One way has proven to be very useful and that is by using a standard calendar. 
Yes, the one you got right on your smartphone or desktop.

A calendar is a simple manifestation of events in time and thus it can be used to either protocol or schedule events.

So the smart house uses calendars to:

  • schedule on/off times for switches, alarms, whatever can be switched
  • notes down locations and can react upon locations on schedule or when members of the household arrive/leave those locations based on calendar events
  • reminds members in the house on upcoming events
  • protocols media playback (what song,…) for later search
  • lets members of the house set events through different means like voice, smartphone, …

So what am I using this calendar(s) for? Simple. It’s there to track travelling since I know when I was where by simply searching the calendar (screenshot). It’s easy to make out patterns and times of things happening since a calendar/timeline view feels natural. Setting on/off times and such is just a bliss if you can make it from your phone in an actual calendar rather than a tedious additional app or interface.

And of course: the house can only be smart about things when it has a way to gather and access that data. Reacting to it’s inhabitants upcoming and previous events adds several levels of smartness.

“make your home smarter”, use case #5 – the submarine light (it’s red!)

We all know it: After a long day of work you chilled out on your bean bag and fell asleep early. You gotta get up and into your bed upstairs. So usually light goes on, you go upstairs, into bed. And there you have it: You’re not sleepy anymore.

Partially this is caused by the light you turned on. If that light is bright enough and has the right color it will wake you up no matter what.

To fight this companies like Apple introduced things like “NightShift” into iPhones, iPads and Macs.

“Night Shift uses your computer’s clock and geolocation to determine when it’s sunset in your location. It then automatically shifts the colors in your display to the warmer end of the spectrum.”

Simple, eh?. Now why does your house not do that to prevent you being ripped out of sleepy state while tiptoeing upstairs?

Right! This is where the smart house will be smart.

Nowadays we’ve got all those funky LED bulbs that can be dimmed and even their colours set. Why none of those market offerings come with that simple feature is beyond me:

After sunset, when turned on, default dim to something warmer and not so bright in general.

I did implement and it’s called appropriately the “U-Boot light”. Whenever we roam around the upper floor at night time, the light that follows our steps (it’s smart enough to do that) will not go full-blast but light up dim with redish color to prevent wake-up-calls.

The smart part being that it will take into account:

– movement in the house
– sunset and dawn depending on the current geographic location of the house (more on that later, no it does not fly! (yet))
– it’ll turn on and off the light according to the path you’re walking using the various sensors around anyways

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?