Imagine you’ve got this ancient piece of technology in front of you. You clearly understand how the hardware works and you are even able to emulate the hardware on your modern-world computer.
Unfortunately hardware is only one half of the story. Software is the other half. And software at this time of the past was burned into chips which do not easily give their secret software away.
But let’s start with the hardware:
The IBM 5100 Portable Computer is a portable computer (one of the first) introduced in September 1975, six years before the IBM Personal Computer. It was the evolution of a prototype called the SCAMP (Special Computer APL Machine Portable) that was developed at the IBM Palo Alto Scientific Center in 1973. In January 1978, IBM announced the IBM 5110, its larger cousin, and in February 1980 IBM announced the IBM 5120. The 5100 was withdrawn in March 1982.
When the IBM PC was introduced in 1981, it was originally designated as the IBM 5150, putting it in the “5100” series, though its architecture was not directly descended from the IBM 5100.
And now on to the software:
The IBM 5100 portable computer came with some of its built-in programs stored in a read-only memory called the “non-executable ROS”. (ROS = “read-only storage”.) In contrast with the “executable ROS”, which supplies instructions to the 5100’s processor directly, the non-executable ROS is accessed using sequential I/O operations, a bit like a tape.
Most notably, the non-executable ROS holds the interactive interpreters for the APL and BASIC programming languages. These are not “native” 5100 programs but were expressed instead in System/370 mainframe and System/3 minicomputer machine code respectively. The 5100 runs emulator programs for those computers in order to host the interpreters, so perhaps it’s just as well that the non-executable ROS is non-executable.
So this write-up is all about how the bits where pushed to the screen and recorded as pictures of the said screen. The characters in these pictures then where analyzed and with the help of machine learning the data could be successfully extracted. It is mind-boggling. And it is all on Github.
If there is any discussion or argument about electric mobility these days the topic of range and battery-aging is coming up rather quick.
Every once in a while you also hear these awesome stories about electric cars achieving total-driven-distances outrageously huge compared to combustion engine cars…
But what is it then, how does a battery in an electric car age over time and mileage? Given that car manufacturers seem to settle on a ca. 150.000km total-driven-miles baseline for giving a battery-capacity percentage guarantee. Something like…
The future owners of ID. models won’t need to worry about the durability of their batteries either, as Volkswagen will guarantee that the batteries will retain at least 70 per cent of their usable capacity even after eight years or 160,000 kilometres.
So. Guarantees are one thing. Reality another. There’s an interesting user-driven survey set-up where Tesla owners can hand in their cars data thus participate in the survey.
And it yields results (getting updated as you read…):
In a nutshell: It seems there is a good chance that your Tesla car might have an above 90% original-specified-battery-capacity after the guaranteed 100.000 miles and even after 150.000 miles (241.000km)…
Good news that is! Given that the average household will do about or less than 20.000 km/year it would mean over 12 years of use and the car still would hold 90% of battery charge. The battery being the most expensive single component on an electric car this is extremely good news as it’s unlikely that the battery will be the reason for the car to be scraped after this mileage.
There are new micro-projectors coming and they are looking good. After the first availability of really small and low-power but enough-light LED projectors (see here) manufacturers have apparently added a laser to the equation.
It is said that…
Unlike traditional projectors that constantly need to be focussed, the Nebra AnyBeam picture is always perfect. You can project onto curved or irregular surfaces with ease – perfect if you want to use it on the fly, or if you want to try your hand at a bit of projection mapping!
This thing will be available, according to the Kickstarter, as a all-in-one package with power and HDMI inputs. It’s got 720p inputs. Well. Well really?
And it will be available to the maker market as a RaspberryPi Hat…
As the replacement drive for yesterdays hard drive crash was put into place the storage array started to re-silver the newly added empty drive. This process takes a while – about 8 hours for this particular type of array.
Interestingly just 2 minutes into the process another drive dropped a bombshell:
Apparently disk 8 holds together it’s business so far but dropped a couple of parity errors into the equation.
This is bad news. But so far science still is on my side of things and no data has been lost.
But now redundancy is down completely. There’s no redundancy for now – until the replaced hard disk is fully integrated. My policy for these sized drives demands a minimum of 2-disk redundancy and for today this policy saved the day (data).
Actually let’s dive a bit into what it’s doing there to achieve 2-disk redundancy:
Synology Hybrid RAID (SHR) is an automated RAID management system from Synology, designed to make storage volume deployment quick and easy. If you don’t know much about RAID, SHR is recommended to set up the storage volume on your Synology NAS.
You will learn different types of SHR and their advantages/disadvantages over classic single disk/RAID setups. In the end, you will be able to choose a type of RAID or SHR for the best interest of your storage volume. This article assumes that as the admin of your Synology NAS, you are also an experienced network administrator with a firm grasp of RAID management.
After the sudden death of a hard drive in one of the house’ storage arrays (after 55997 hours of service) beginning of this month it has happened again:
With less than half the runtime of the previously dead disk this one is an early failure. Well within the warranty. Therefore the disk is already en route to be replaced by an RMA (Western Digital RMA process so far is spotless!)
Anyhow: This was a 4 TB drive. It’s in an array with 2-disk redundancy and 8 other drives. So the array still is operating with redundancy right now. Additionally a full backup exists as well as a hot-standby (but slower) offsite mirror.
I am quite confident to not loose data. But this raid-sync is going to take a bit longer. As drives get bigger, syncs get longer.
The CPU/hardware related bugs surfacing the last couple of years have mostly been fixed by adjusting the software that is run. Sometimes only by disabling certain features of a CPU or patching the microcode in the CPU itself.
The issue with this is that by fixing these issues features got disabled and workarounds had been introduced that lowered performance. Dramatically so for some use-cases.
By how much? Well it really depends on your CPU and use-cases. But maybe you want to try yourself. If you want to know the most current parameters to pass to your kernel on boot-up to disable all the performance impacting fixes, go here:
It is not recommended to have this in productive use – as you can imagine. Those bugs where fixed for a reason.
Suica (スイカ Suika) is a rechargeable contactless smart card, electronic money used as a fare card on train lines in Japan, launched on November 18, 2001. The card can be used interchangeably with JR West’s ICOCA in the Kansai region and San’yō region in Okayama, Hiroshima, and Yamaguchi Prefectures, and also with JR Central’s TOICA starting from spring of 2008, JR Kyushu’s SUGOCA, Nishitetsu’s Nimoca, and Fukuoka City Subway’s Hayakaken area in Fukuoka City and its suburb areas, starting from spring of 2010. The card is also increasingly being accepted as a form of electronic money for purchases at stores and kiosks, especially within train stations. As of October 2009, 30.01 million Suica are in circulation.
This time around we really made use of electronic payment and got around using cash whenever possible.
There where only a few occasions when we needed the physical credit card. Of course on a number of tourist spots further away from Tokyo centre cash was still king.
From my first trip to Japan to today a lot has changed and electronic payment was adopted very quickly. Compared to Germany: Lightning fast adoption in Japan!
The single best thing that has happened recently in this regard was that Apple Pay got available in Germany earlier this year. With the iPhone and Watch supporting SUICA already (you can get a card on the phone/watch) the availability of Apple Pay bridged the gap to add money to the SUICA card on the go. As a visitor to Japan you would mostly top up the SUICA card in convenience stores and train stations and mostly by cash. With the Apple Pay method you simply transfer money in the app from your credit card to the SUICA in an instant.
This whole electronic money concept is working end-2-end in Japan. Almost every shop takes it. You wipe your SUICA and be done. And not only for small amounts. Everything up to 20.000 JPY will work (about 150 Euro).
And when you run through a train station gate to pay for your trip it you hold your phone/watch up to the gate while walking past and this is it in realtime screen recorded:
I wish Germany would adopt this faster.
Oh, important fact: This whole SUICA thing is 100% anonymous. You get a card without giving out any information. You can top it up with cash without any link to you.
About a year ago there were some very interesting reports about a german inventor and his invention: a highly futuristic, transforming smartphone airbag.
It would be attached to your phone and when you drop it, it would automatically deploy and dampen the impact.
Impressive, right? There’s now a Kickstarter campaign behind this to deliver it as a product. All very nice and innovative.
I have no usue of a smartphone airbag of some sort. But hear me out on my train of thought:
I do partake in the hobby of quadcopter flying. I’ve built some myself in the past.
Now these quadcopters are very powerful and have very short flight times due to their power-dynamics. 4-5 Minutes and you’ve emptied a LiPo pack.
Model airplanes, essentially everything with wings, flys much much longer.
My thought now: Why not have a convertible drone.
When the pilot wants a switch could be flipped and it would convert a low-profile quadcopter to a low-profile quadcopter with wings. Similar to how the above mentioned smartphone “airbag”.
I don’t know anything about mechanics. I have no clue whatsoever. So go figure. But what I do know: the current path of the mini-quad industry is to create more powerful and bigger “mini”-quadcopters. And this is a good direction for some. It’s not for me. Having a 10kg 150km/h 50cm projectile in the air that also delivers a 1kg Lithium-Polymer, highly flammable and explosion-ready battery pack does frighten me.
Why not turn the wheel of innovation into the convertible-in-air-with-much-longer-flight-times direction and make the mini-quadcopters even more interesting?
Last week we were approached by Prof. Dr. Nicole Zillien from Justus-Liebig-University in Gießen/Germany. She explained to us that she currently is working on a book.
In this book an empirical analysis is carried out on “quantified-self” approaches to real life problems.
With the lot of information and data we had posted on our personal website(s) like this blog and the “loosing weight” webpage apparently we qualified for being mentioned. We were asked if it would be okay to be named in the book or if we wanted to be pseudonymized.
Since everything we have posted online and which is publicly accessible right now can and should be quoted we were happy to give a go-ahead. We’re publishing things because we want it to spur further thoughts.
It will be out at the end of 2019 / beginning of 2020. As soon as it is out we hope to have a review copy to talk about it in this blog once again.
We do not know what exactly is being written and linked to us – we might as well end up as the worst example of all time. But well, then there’s something to learn in that as well.
In the interesting field of IoT a lot of buzz is made around the predictive maintenance use cases. What is predictive maintenance?
The main promise of predictive maintenance is to allow convenient scheduling of corrective maintenance, and to prevent unexpected equipment failures.
The key is “the right information in the right time”. By knowing which equipment needs maintenance, maintenance work can be better planned (spare parts, people, etc.) and what would have been “unplanned stops” are transformed to shorter and fewer “planned stops”, thus increasing plant availability. Other potential advantages include increased equipment lifetime, increased plant safety, fewer accidents with negative impact on environment, and optimized spare parts handling.
So in simpler terms: If you can predict that something will break you can repair it before it breaks. This improvse reliability and save costs, even though you repaired something that did not yet need repairs. At least you would be able to reduce inconveniences by repairing/maintaining when it still is easy to be done rather than under stress.
You would probably agree with me that these are a very industry-specific use cases. It’s easy to understand when it is tied to an actual case that happened.
Let me tell you a case that happened here last week. It happened to Leela – a 10 year old white British short hair lady cat with gorgeous blue eyes:
Ever since her sister had developed a severe kidney issue we started to unobtrusively monitor their behavior and vital signs. Simple things like weight, food intake, water intake, movement, regularities (how often x/y/z).
When Leela now visits her litter box she is automatically weighed and it’s taken note that she actually used it.
A lot of data is aggregated on this and a lot of things are being done to that data to generate indications of issues and alerts.
This alerted us last weekend that there could be an issue with Leelas health as she was suddenly visiting the litter box a lot more often across the day.
We did not notice anything with Leela. She behaved as she would everyday, but the monitoring did detect something was not right.
What had happened?
On the morning of March 9th Leela already had been to the litter box above average. So much above average that it tripped the alerting system. You can see the faded read area in the top of the graph above showing the alert threshold. The red vertical line was drawn in by me because this was when we got alerted.
Now what? She behaved totally normal just that she went a lot more to the litter box. We where concerned as it matched her sisters behavior so we went through all the checklists with her on what the issue could be.
We monitored her closely and increased the water supplied as well as changed her food so she could fight a potential bladder infection (or worse).
By Monday she did still not behave different to a degree that anyone would have been suspicious. Nevertheless my wife took her to the vet. And of course a bladder infection was diagnosed after all tests run.
She got antibiotics and around Wednesday (13th March) she actually started to behave much like a sick cat would. By then she already was on day 3 of antibiotics and after just one day of presumable pain she was back to fully normal.
Interestingly all of this can be followed up with the monitoring. Even that she must have felt worse on the 13th.
With everything back to normal now it seems that this monitoring has really lead us to a case of “predictive cat maintenance”. We hopefully could prevent a lot of pain with acting quick. Which only was possible through the monitoring in place.
Health is a huge topic for the future of devices and gadgets. Everyone will casually start to have more and more devices in their daily lifes. Unfortunately most of those won’t be under your own control if you do not insist on being in control.
You do not have to build stuff yourself like I did. You only need to make the right purchase decisions according to things important to you. And one of these things on that checklist should be: “am I in full control of the data flow and data storage”.
If you are not. Do not buy!
By coincidence the idea of having the owner of the data in full control of the data itself is central to my current job at MindSphere. With all the buzz and whistles around the Industry IoT platform it all breaks down to keep the actual owner of the data in control and in charge. A story for another post!
Since 2011 we’ve got this Boogie Board in the household. It’s simply a passive LCD panel on which you can write with a plastic pen. When you do you’re interacting with the liquid crytals and you switch their state. So what was black becomes white.
So we got this tablet and it’s magnetically pinned to our fridge. And whenever we’ve booked the next trip we’re crossing off days by coloring them in a grid.
I recently wrote about how I am using ThinClients in our house to always have a ready-to-use working environment that get’s shared across different desks and work places.
To complete the zoo of devices I wanted to take the chance and write about another device we’re using when the purpose fits: ChromOS devices.
A little bit over a year ago I was given a HP Chromebook 11 G5 and this little thing is in use ever since.
The hardware itself is very average and works just right. The only two things that could be better are the display and the trackpad. With the trackpad you can help yourself with an external mouse.
The display works for the device size but the resolution being 1366×768 is definitely a limiting factor for some tasks.
What is not a limiting factor, astonishingly, is the operating system. I did not have any expectations at all when I first started using the Chromebook but everything just fell into place as expected. A device with almost no local storage and everything on the google cloud as well as a device that you can simply pick up and start using with just your google account may not sound crazy innovative. But let me tell you: if you start living that thin client, cloud stored life these Chrome OS devices hit the spot perfectly.
Everything updates in the background and as long as you are okay with web based applications or Android based applications you are good to go.
Did I miss anything functionwise? Yes. At the beginning there was no real shell or Linux tools available for Chrome OS natively. This has changed.
Would I buy another one or do I recommend it and for whom? I would buy another one and I would recommend it for certain audiences.
I would recommend it for anyone who does not need to game anything not available in the Google Playstore – anything that can be done on the web can be done with the Chromebook. And as long as there is not the requirement of anything native or higher-spec that requires you to have “Windows-as-a-hobby” or a beefy MacOS device sitting around I guess these inexpensive Chrome OS devices really have their niche.
For kids – I guess this would make a great “my-first-notebook” as it works when you need it and does not lock you in too much if you wanted to start exploring. But then again: what do I know – I do not have kids.
When you take a picture with an iPhone these days it does generate haptic feedback – a “kachung” you can feel. And a shutter sound.
Thankfully the shutter sound can be disabled in many countries. I know it can’t be disabled on iPhones sold in Japan. Which kept me from buying mine in Tokyo. Even when you switch the regions to Europe / Germany it’ll still produce the shutter sound.
Anyway: With my iPhone, which was purchased in Germany, I can disable the shutter sound. But it won’t disable the haptic “kachung”.
It’s interesting that Apple added this vibration to the activity of taking a picture. Other camera manufactures go out of their way to decouple as much vibration as possible even to the extend that they will open the shutter and mirror in their DSLRs before actually making the picture – just so that the vibration of the mirror movement and shutter isn’t inducing vibrations to the act of taking the picture.
With mirror less cameras that vibration is gone. But now introduced back again?
Since AVM has started to offer wireless mesh network capabilities in their products through software updates I started to roll it out in our house.
Wireless mesh networks often consist of mesh clients, mesh routers and gateways. Mobility of nodes is less frequent. If nodes constantly or frequently move, the mesh spends more time updating routes than delivering data. In a wireless mesh network, topology tends to be more static, so that routes computation can converge and delivery of data to their destinations can occur. Hence, this is a low-mobility centralized form of wireless ad hoc network. Also, because it sometimes relies on static nodes to act as gateways, it is not a truly all-wireless ad hoc network.
With the rather complex physical network structure and above-average number of wireless and wired clients the task wasn’t an easy one.
To give an impression of what is there right now:
So there’s a bit of almost everything. There’s wired connections (1Gbit to most places) and there is wireless connections. There are 5 access points overall of which 4 are just mesh repeaters coordinated by the Fritz!Box mesh-master.
There’s also powerline used for some of the more distant rooms of the mansion. All in all there are 4 powerline connections all of them are above 100 Mbit/s and one even is used for video streaming.
All is managed by a central Fritz!Box and all is well.
Like without issues. Even interesting spanning-tree implementations like from SONOS are being properly routed and have always worked without issues.
The only other-than-default configuration I had made to the Fritz!Box is that all well-known devices have set their v4 IPs to static so they are not frequently switching around the place.
How do I know it works? After enabling the Mesh things started working that have not worked before. Before the Mesh set-up I had several accesspoints independently from each other on the same SSID. Which would lead to hard connection drops if you walked between them. Roaming did not work.
With mesh enabled I’ve not seen this behavior anymore. All is stable even when I move actively between all floors and rooms.
Ever since we had changed our daily diet we started to weigh everything we eat or cook. Like everything.
Quickly we found that those kitchen scale you can cheaply buy are either not offering the convenience we are looking for or regularly running out of power and need battery replacements.
As we already have all sorts of home automation in place anyway the idea was born to integrate en ESP8266 into two of those cheap scales and – while ripping out most of their electronics – base the new scale functionality on the load cells already in the cheap scale.
So one afternoon in January 2018 I sat down and put all the parts together:
After the hardware portion I sat down and programmed the firmware of the ESP8266. The simple idea: It should connect to wifi and to the house MQTT broker.
It would then send it’s measures into a /raw topic as well as receive commands (tare, calibration) over a /cmd topic.
Now the next step was to get the display of the measured weights sorted. The idea for this: write a web application that would connect to the MQTT brokers websocket and receive the stream of measurements. It would then add some additional logic like a “tare” button in the web interface as well as a list of recent measurements that can be stored for later use.
An additional automation would be that if the tare button is pressed and the weight is bigger than 10g the weight would automatically be added to the measurements list in the web app – no matter which of the tare buttons where used. The tare button in the web app or the physical button on the actual scale. Very practical!
Here’s a short demo of the logic, the scale and the web app in a video:
If you ever traveled on a train or plane with good active noise cancellation headphones you might agree how much more pleasant the trip was with much less noise reaching your ears.
When I tried active noise cancellation for the first time I had that weird sensation as if the pressure around suddenly changed. Like being in a very fast elevator or going for a quick dive. It felt weird but luckily it went away and the aww of joy replaced it. Quietness. Bliss.
Now there seem to be people for whom that feeling won’t go away. They get headaches and cannot stand the feeling when using active noise cancellation.
I’ve never had any explanation to this phenomena – until now. I ran across an article on SoundStage describing that in fact the feeling is not caused by actual changes of pressure but…
According to the engineer, eardrum suck, while it feels like a quick change in pressure, is psychosomatic. “There’s no actual pressure change. It’s caused by a disruption in the balance of sound you’re used to hearing,” he explained.
Aha! The brain gets confused by signals reaching your ears that naturally would not exists. Those signals make no sense so the brain tries to make sense of it. And voilá something is sucking your ear drum!
In 2017 Texas Instruments had released a line of cheap industry grade LED projectors meant to be used in production lines and alike:
DLP® LightCrafter Display 2000 is an easy-to-use, plug-and-play evaluation platform for a wide array of ultra-mobile and ultra-portable display applications in consumer, wearables, industrial, medical, and Internet of Things (IoT) markets. The evaluation module (EVM) features the DLP2000 chipset comprised of the DLP2000.2 nHD DMD, DLPC2607 display controller and DLPA1000 PMIC/LED driver. This EVM comes equipped with a production ready optical engine and processor interface supporting 8/16/24-bit RGB parallel video interface in a small-form factor.
After I had learned about the existence of those small projectors I had to get a couple and try for myself. There would be so many immediate and potential applications in our house.
After having them delivered I did the first trial with just a breadboard and the Raspberry Pi 3.
The projector module has a native resolution of 640×360 – so not exactly high-pixel-density. And of course if the image is projected bigger the screen-door effect is quite noticeable. Also it’s not the brightest of images depending on the size. For the usual use-cases the brightness is definitely sufficient.
too low brightness for large projection size – no daylight projection
low resolution is an issue for text and web content – it is not so much of an issue for moving pictures as you might think. Video playback is well usable.
flimsy optics that you need to set focus manually – works but there is no automatic focus or alike.
very low powered – 2.5A/5V USB power supply is sufficient for Pi Zero + Projector on full brightness (30 lumen)
low brightness is not always bad – one of our specific use cases requires an as dim as possible image with fine grain control of thr brightness which this projector has.
extremely small footprint / size allows to integrate this device into places you would not have thought of.
almost fully silent operation – the only moving part that makes a sound is the color wheel inside the DLP module. You have to put your ear right onto it to hear anything.
passive cooling sufficient – even at full brightness an added heat sink is enough to dissipate the heat generated by the LED.
So what are these use cases that require such a projector you ask?
Night status display:
For the last 20+ years I am used to sleep with a “night playlist” running. So far a LED TV was used at the lowest brightness possible. Still it was pretty bright. The projector module allows to dim the brightness down to almost “moon brightness” and also allows to adjust the color balance towards the reds. This means: the perfect night projection is possible! And the power consumption is extremely low. A well watchable lowest brightness red-shifted image also means much lower temperatures on the projector module – it’s crazy how low powered, low temperature.
Season Window Projection:
Because the projector is small, low-powered and bright enough for back-lit projection we tried and succeeded with a Halloween window projection scene the last season.
It really looks funky from the outside – funky enough to have several people stop in front of the house and point fingers. All that while power consumption was really
House overall status projections:
When projecting information is that cheap and power efficient it really shines when used to display overall status information like house-alarm status, general switch maps, locations of family members and so on. I’ve left those to your imagination as these kind of status displays are more or less giving away a lot of personal information that isn’t well suited for the internet.
Not having time for a full-day-of-focus I postponed the upgrade to this saturday. With the agreement of the family as they are suffering through the maintenance period as well.
The upgrade would need cautious preparation in order to be doable in one sitting. And this was also meant to be some sort of disaster-recovery-drill. I would restore the house central docker and service infrastructure from scratch along this.
And this would need to happen:
all services, zfs pools, docker containers, configurations needed to be double checked for full backup – as this would be used to restore all (ZFS snapshots are just the bomb for these things!)
the main central docker server would have to go down
get a fresh Ubuntu 18.04 LTS set-up and booting from ZFS on a NVMe SSD (bios update(s)!, secure boot disabling, ahci enabling, m.2 instead of sata express switching…you get the idea)
get the network set-up in order: upgrading from Ubuntu 16.04 to 18.04 means ifupdown networking was replaced by netplan. Hurray! Not.
get docker-ce and docker-compose ready and set-up and all these funky networkings aligned – figure out in this that there are major issues with IPv6 in docker currently.
pull in the small number of still needed mechanical hard disks and import the ZFS pools
start the docker builds from the backup (one script \o/)
start the docker containers in their required order (one script \o/)
Apart from some hardware/bios related issues and the rather unexpected netplan introduction everything went fairly good. It just takes ages to see data copied.
Bandwidth was the only real issue with this disaster recovery. All building blocks seemed to fall into place and no unplanned measure had to be taken. The house systems went partially down at around 12:30 and were back up 10 hours later 22:00. Of course non-automated things like internet kept working and all switches were only manual push-buttons. So everything could be done still but with a lot less convenience.
All in all there are more than 40 vital docker container based services that get started one after the other and interconnect to deliver a full house home automation. With the added SSD performance this whole ship is much much more responsive to activities. And hopefully less prone to mechanical defects.
Backup and Disaster-Preparations showed to be practical and working well. There was no beat missed (except sensor measure values during the 10 hours downtime) and no data lost.
What could be done better: It could be much more straight forward when there were less dependencies on external repositories / docker-hub. Almost all issues that came up with containers where from the fact that the maintainers had just a day before introduced something that kept them from spinning up naturally. Bad luck. But that can be helped! There’s now a multi-page disaster-recovery-procedure document that will be used and updated in the future.
Oh and what speeds am I seeing? The promissed 3 Gbyte/s read and write speeds are real. It’s quite impressive to see 4-digit megabyte/s values in iotop frequently.
I almost forgot! During this exercise I had been in the server room less than 30 minutes. But I was on a warm and nice work-desk set-up I am using in the house as much as I can – and I will tell you about it in another article. But the major feature of this work-desk set-up is that it is (a) a standing desk and (b) has a treadmill under it. Yes. Treadmill.
You will get pictures of the set-up in that mentioned article, but since I had spent more than 10 hours walking on saturday doing the disaster recovery I want to give you a glimpse of what such a set-up means:
This large amount of spinning disks means that there are also failing drives that stop spinning once every while. Backblaze saw the need to take note about what hard-drive series fails more of less often and started to generate a yearly report on the reliability of these hard drives.
Yesterday they published their report for 2018 – if you got storage requirements or if you are in the market to purchase storage space for your operation – it probably is very helpful to take a look at the report.
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 :-).
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.
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
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.