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.
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.
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.
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.
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.
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.
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.
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).
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 :-).
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
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.
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.
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).
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.
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.
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.
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
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.
“The internet of things” is a buzzword used more and more. It means that things around you are connected to the (inter)network and therefore can talk to each other and, when combined, offer fantastic new opportunities.
So NodeRed is a NodeJS based toolset that allows you to create so called “flows” (see picture above). Those flows determine what reacts and happens when things happen. Fantastic, told you!
I’ve added Alarming to hacs a while ago and I’ve now extended the built-in SMS gateway providers with the german telekom services called “Global SMS API”.
This API is offered through the Telekom own portal called developer garden and is as easy to use as it can possibly be. You only need to set-up the account with developergarden and after less than 5 minutes you can send and receive SMS and do a lot more. They got APIs for nearly everything you possible want to do … fancy some “talk to your house”-action? Would be easy to integrate into h.a.c.s. using their Speech2Text APIs.
They have a short video showing how to set it all up:
So I’ve added the SMS-send capabilities to the hacs internal alarming system with it’s own JSON configuration file looking like this:
And this simple piece of configuration leads to SMS getting sent out as soon as – in this example – a window opens:
Before the Telekom Global SMS API I’ve used a different provider (SMS77) but since the delivery times of this provider varied like crazy (everything from 30 seconds to 5 minutes) and the provider had a lot of downtimes my thought was to give the market leader a try.
Usually the actors that allow you to switch power on/off and who measure power usage use the 434Mhz or 868Mhz wireless bands to communicate with their base station. Now the german manufacturer AVM came up with a solution that allows you to switch on/off (with an actual button on the device itself and wireless!) and to measure the power consumption of the devices connected to it.
The unspectacular it looks the spectacular are the features:
switch up to 2300 watts / 10 ampere
use different predefined settings to switch on/off or even use Google Calendar to tell it when to switch
measure the energy consumption of connected devices
For around 50 Euro it’s quite an investment but maybe I’ll give it a shot – especially the measurement functionality sounds great. Since I do not have one yet I don’t know anything about how to access it through third party software (h.a.c.s.?)
So first a small video to get an idea what I am implementing right now:
I plan to add a lot more – like for swiping gestures. So this will be – just like h.a.c.s – a continuous project. Since I switched to OS X entirely at home I use the great Coda2 to write and debug the code. It helps a lot to have two browser set-up because for some reason I still not feel that well with the WebKit Web Inspector.
Another great feature of Coda2 is the AirPreview – which means it will preview your current page in the editor on an iOS device running DietCoda – oh how I love those automations.
I was asked if it would be possible to get the ELV MAX! Cube interfacing functionality outside of h.a.c.s. – maybe as a library. Sure! That is possible. And to speed up things I give you the ELV MAX! Cube C# Library called: MAXSharp
It’s a plain and simple library without much dependencies – in fact there’s only some threading and the FastSerializer. Since I am using this library with h.a.c.s. as well I did not remove the serializer implementation.
There’s a small demo program included which is called MAXSharpExample. The library itself contains the abstractions necessary to get information from the ELV MAX! Cube. It does not contain functionality to control the cube – if you want to add, feel free it’s all open sourced and I would love to see pull requests!
The architecture is based upon polling – I know events would make a cleaner view but for various reasons I am using queues in h.a.c.s. and therefore MAXSharp does as well. The example application spins up the ELV MAX interfacing / handling thread and as soon as you’re connected you can access all house related information and get diff-events from the cube.
It’s been some weeks since I wrote a status update on the ELV MAX! cube protocol reverse engineering and integration into my own home automation project called h.a.c.s..
So first of all I want to give a short overview over what has been achieved so far:
I wrote a C# library, highly influenced by a PHP implementation from the domotica forum, which allows you to continuesly get status information from the ELV MAX! cube with current (1.3.6) firmware. It is tested so far with a fairly big set-up for the ELV MAX! cube (see below)
I was able to integrate that library into my own home automation project called h.a.c.s. – There the ELV MAX! cube is just another device, alongside a EzControl XS1 and a SolarLog 500. The cube is monitored using my library and diff-sets as well as status information are stored automatically with the h.a.c.s. built-in mechanisms. In fact you can access for example the window shutter contact information just like you would with any other door contact in the EzControl XS1.
You can use events coming from the ELV MAX! cube to create new events – how about switching off/on devices when opening/closing windows?
Every bit of information from all integrated sensor monitoring and actor handling devices come together in h.a.c.s.
I started the reverse engineering with just one shutter contact and one thermostat. After all my test were successful I went for the big package and ordered some more sensors. This is how the setup is currently configured:
I’ve learned a lot of interesting things about the ELV MAX! cube hardware and software. One is that you need to be ready for surprised. The documentation of the cube tells you the following:
Did you spot the funny fact? 50 devices – we’re well below that limit. 10 rooms – holy big mansion batman! We’re well over that. How is that possible? Well take it as a fact – you can create more than 10 rooms. And that is very handy. I’ve created 13 rooms and there are probably more to come because those shutter contacts are quite cheap and can be used for various other home automation sensory games. The tool to set-up and pair those sensors just came up with a notice that said “Oh well, you want to create more than 10 rooms? If you’re sure that you want that we allow you to, but hey, don’t blame us!”. Cool move ELV! – As of now I haven’t found any downside of having more than 10 rooms.
All my efforts started with firmware version 1.3.5. This firmware seemed to have some severe memory leaks – because just by retrieving the current configuration information every 10 seconds the device would stop communicating after more then 48 hours. Only a reboot could revive it – sometimes amnesia set in which led to a house roundtrip for me.
With some changes in the library (like keeping the connection open as long as possible) and a new firmware version 1.3.6. the cube was way more cooperative and hasn’t crashed for about 1 month now (with 10 seconds update times).
So what does my library do? It is designed to run in it’s own thread. When it’s started it opens a connection to the cube and retrieves the current status and configuration information. Those informations are stored in an object called “House”. This house consists of multiple rooms – and those rooms are filled with window shutter contacts and thermostats. All information related to those different intances are stored along with them. The integration into h.a.c.s. allows the library to generate sensor and actor events (like when a temperature changes, a window opens/closes) which are passed back to h.a.c.s. and handled in the big event loop there.
With all that ELV MAX! cube data I wanted to plug a quite nice tool that I am using in the iPhone and the iPad. It’s called “Moni4home” and it allows you to control the EzControl XS1 directly. Because it’s only accessing the EzControl XS1 I used h.a.c.s. to “inject” additional sensor data into the standard EzControl XS1 data. So basically data flow is like this: iPad app accesses h.a.c.s. which acts as a proxy. h.a.c.s. retrieves the EzControl XS1 sensor and actor data and injects additional virtual sensors like those from the ELV MAX! cube. h.a.c.s. then sends that beefed up data to the iPad app. Voilá!
After the successful integration of the ELV MAX! cube I’ve started to work on the next bit of networking home automation equipment in my house – a solar panel data logger called “Solar-Log 500”. This device monitors two solar power inverters and stores the sensory data.
“Funny” story first: this device has the same problem like the ELV MAX! cube. When you start to poll it every 10 seconds (or less) it just stops operating after about 20 hours. Bear in mind: In case of the Solar-Log I just http-get a page that looks like this in the browser:
And by doing so every 10 seconds the device stops working. I am using the current firmware – so one workaround for that issue is to planable reboot the Solar-Log at a time when there is no sun and therefore nothing to log or monitor.
Beside that it’s a fairly easy process: Get that information, log it. Done.
So there you have it – h.a.c.s. interfacing with three different devices and roughly 100 sensors and actors over 434mhz/868mhz, wireless and wired network. There’s still more to come!
A lot of people seem to dive into home automation these days. Apparently Andreas is also at the point of starting his own home automation project. Good to know that he also is using the EzControl XS1 and in the future maybe even the ELV MAX! cube. Party on Andreas!
I had a couple of hours to tinker with my ELV MAX! Cube and there is some progress with the protocol reverse engineering.
Of course there is the domotica forum helping out with some information the guys over there have found but in addition to their very helpful findings I want it to be integrated into h.a.c.s. – and along with it I maybe want to have a way to find eventual protocol changes quick and easy in the future.
So yesterday I partied on the ‘first contact’ – today I am a bit deeper into the protocol itself:
Here are some explanations to the picture:
When a tcp connection to the cube is opened you can immediately read from it – the cube is throwing information at you. There’s always a character at the beginning of each line which marks the type and beginning of the message.
There seem to be these types of messages in the first package of information:
H – Header maybe?
it contains the serial number of your cube, the RF address, the firmware version and several other things like time information
M – Metadata?
this seems to be some kind of global metadata list, containing the rooms with their IDs (it’s the %) in the screenshot). Furthermore it contains the serial numbers and names of the devices in that room – at the moment there’s just a window-state-sensor in that first room called “Fensterkontakt 1”
C – Configuration?
since there are multiple C messages these seem to contain detailed configuration data specific to a device in the MAX! network. Each device seems to be addressed by a RF Address and it’s serial number.
the first C message in the screenshot is associated to the cube itself
the second C message is associated to the window-state-sensor – you can clearly see in there the room id “%)” and the serial of the window-state-sensor.
L – live status?
this message seems to contain room status information. In our case there is only the room with id “%)”. When the window-state-sensor changes state the last byte changes value – interesting, eh?
On the coding side I’ve got several things set-up in my little debug tool. I’ve wrapped those message types into various classes to handle them more easily later on in h.a.c.s.. Furthermore I used a little decompiler-wisdom to extract some more information from the included ELV MAX! cube software.
Thanks to german UrhG paragraph § 69e (german copyright law) I am allowed to decompile the included software in order to achieve interoperability (and only that). That’s exactly what I would like to achieve: Interoperability. And for the record: besides that I also filed a support request to ELV in which I ask them if I could get access to a presumably existing documentation of that protocol.
While waiting on that documentation I am using JD-GUI as a decompiler user interface for java – since the software of the cube is written in java.
There are many interesting things in there but it’s a slow process to get ahold of all the things necessary. There are already some very nice things showing up. Like when you want to know if there’s a cube (or more) in the network you just need to send a multicast ip packet containing a characteristic signature and all the cubes in your network will try to connect back to you with some basic information – nice, isn’t it? Or what about that AES Encryption/Decryption that seems to be built into the cube? Yes that’s right! It seems to be possible to send commands to either encrypt or decrypt according to the AES. Thoughtfully these commands are marked with ‘e’ and ‘d’. Or that if you send “l:” as a command with CR+LF at the end you get a device listing with all stats… and so on.
Some open question to EQ-3/ELV for the end of this article:
Why this strange protocol? Why all the work on both sides? Just because an HTTP server implementation with a RESTful service would have been that more difficult?
Base64 encoded data? The 90s called, they want their 8th bit back.
why that complex local webserver approach when you could have done everything in a java app anyways?
That’s it for today, I just pushed a feature to the Git repository which allows you to run whatever command you like on your cube with the debugging tool:
For several years now I am building my own home automation tools by putting together existing hardware and self-written software. As the central software core of my home automation system I use h.a.c.s. – “home automation control server” which I put up as open source software on GitHub.
Throughout the years I was able to embedd a lot of daily tasks and measurements in one place which can be accessed by a simple web page. It currently looks like this:
You can find some articles on this blog about h.a.c.s. if you want to know more about it.
As of today I can control and measure the states of switches, windows, doors, temperature and humidity and power consumption. Scenarios like “when this door opens, switch on that light” are easy things to do with h.a.c.s.
Now “Winter’s coming!”. And therefore I want to take control of the heating of each and every room in the house. I want to set a goal for a temperature and I want the heating to fire up or cool down with that goal. And of course I want to monitor manual changes of each and every radiator in the house.
Last week then I stumbled upon a piece of kit called “ELV MAX! Cube”. It’s a white cube (as the name implies) which offers a USB port from which it is powered and an RJ-45 ethernet port which connects the cube to the home network.
The cube itself does not draw much power and it can be powered by the routers USB port easily. It allows you to connect some peripherals using 868 mhz rf. Those peripherals can be: window state sensors (closed/open) and thermostats to control the radiators (and a switch but, well… hopefully not necessary).
It comes with it’s own user interface – a java application that connects to the device and allows you to configure it. Quite nice – it runs on Windows and Mac. You can use a cloud service to control the device over the internet, but I have no intention in trying that out right now.
My plan is to extend h.a.c.s. to get information from the cube and handle them and in the end even control the cube by setting temperatures and controlling the outcome of those changes.
I’ve worked on my little holiday project for a while now and it’s making great progress. Since logging is working for almost two weeks now I got some data that should be visualized. One main goal of the project is to have a great UI to browse the sensor data.
The logging server now included an internal http server which serves some pages and RESTful services already. One of those services is the sensor data service which can be asked to output JSON formatted sensor data. If you take that data using jQuery and the flot jQuery plugin you’ll get something like that:
This EzControl XS1 device is a complex thing. And currently I am playing with more than 10 sensors and more than 10 actuators. Since poking around with such a device will most certainly lead to a condition where that configuration might get lost (like a power down for more than 30 minutes).
Therefore I was in need of a backup and restore tool. Because there isn’t one I had to write one myself. Here it is:
I can haz backup tool
My tool is available as opensource as part of the h.a.c.s. toolkit here. Enjoy!
My holiday project is progressing: Today it was hardware delivery day!
So this is the hardware which is ready to be used:
1x EzControl XS1 controller
2x Temperature and Humidity sensor
8x Remote Power Switch
The EzControl XS1 is easy to use as far as I had the time to give it a try. After the network setup the XS1 offers a simple web interface and REST service. Built upon that REST service there is also a configuration application and a visualization application available. Those two applications are apparently built using the GWT framework.
I poked around a bit with the sensor and actor configuration screens and everything just worked. Those applications are great for the easy tasks. And for everything else hacs is what is going to be the tool of choice (to be written).
In the last 10+ years I was fiddling with different home automation concepts. Mostly without broad use cases because at that time no one seemed to be interested in having sensors and actors like crazy at home. In fact not that many people seem to care these days.
Having more and more hardware and software around us creates the use cases for a broader audience people like me have for 10+ years. Mainstream is a bitch for nerds
That said I found a nice plastic box I want to use in a winter project. This plastic box is called “EzControl XS1”. It comes with several visible and “invisible” interfaces.
The visible and obvious ones are: power, 100 mbit ethernet, sd card slot. So it takes some power and does something on the network. The not so obvious and therefore “invisible” interfaces are the most interesting ones: the EzControl XS1 comes with the ability to send and receive on 433 Mhz and 868 Mhz.
Yes that are the ranges used by switchable and dimable power sockets, temperature sensor and AMR. The EzControl XS1 is not that cheap (coming at 189 Euros for the base version and additional 65 Euros per upgrade option). I do not own one yet so it’s the plan to acquire at least one and start of with dimable power sockets and add more sensors and actors on the way
One great feature of the EzControl XS1 is the embedded WebServer with which the users application (the one I want to write) can interact using a HTTP/JSON Protocol. Oh dear: Sensor data and Actor control using JSON. How great is that!
There is some example code available (even a proprietary iPad/iPhone client) but since I want to have some custom features I do not currently see to be available in software I am going to write a set of tools which will get and protocol sensor data and run scripts to controls actors. Oh it’ll be all available as open source (license not yet chosen).
P.S.: If some one from Rose+Herleth is reading this and wants to help – send me a test unit