If you don’t live in the Czech Republic, you may not understand this story. A few years ago, when the government wanted to promote tourism in the Czech Republic, it came up with the slogan “land of stories.” The Czech Republic is truly a land of stories. This story is about how a former locksmith created a marketplace serving drug cartels and arms dealers, then disappeared with 5,000 bitcoins and ended up in prison for a few years. And when it seemed that no one wanted him anymore, he offered the Ministry of Justice a gift worth 468 BTC. Just like that. The minister accepted the gift because it was “crystal clear.” Only to find out the next day that it came from the “exit scam” of one of the largest illegal marketplaces, Nucleus Market.

Do you think I made this story up? I wish I were such a good storyteller. Let’s retell it together and put it into context.

Sheep Marketplace

To begin Jiřikovský’s venture into cryptocurrencies, let’s look back to 2011, when the “online marketplace” Silk Road was founded, operating on the “dark web” via the anonymous TOR network.

On Silk Road, you could offer and buy anything, but given the anonymity of both parties and the anonymity of payments via cryptocurrencies (at that time, Bitcoin), the items sold there were mainly things you wouldn’t want to ask for at a corner store. That is, weapons, drugs, stolen data, and often illegal work of all kinds. The Silk Road marketplace ceased operations in 2013 when the FBI arrested its founder, Ross Ulbricht, after identifying him. Incidentally, Ross Ulbricht, who was sentenced to life imprisonment, was pardoned and released by President Trump in January 2025.

The Silk Road case highlighted the potential of such intermediary marketplaces. And so, followers soon appeared on the dark web, in the dark depths of the internet accessible only to “insiders,” but not to Google. In May 2013, even before Ulbricht’s arrest in October 2013, an advertisement promoting Sheep Marketplace was published on the Bitcoin Forum.

The post is written in beginner’s English, but linguists later conclude that it contains errors typical of Slavic languages (missing articles, Slavic word order, problems with prepositions, etc.) — and it also mentions the Czech framework Nette.

Sheep Marketplace gradually grew, gaining the biggest boost in October 2013 when Silk Road was shut down. It is essentially a simple discussion forum where supply and demand are matched, buyers deposit their bitcoins in escrow on the marketplace, and if the transaction is settled to the satisfaction of both parties, the marketplace transfers the funds, retaining a commission.

Everything worked well until November 21, 2013, when a user named EBOOK101 discovered a flaw in the marketplace. This flaw allowed EBOOK101 to repeatedly withdraw Bitcoins from the escrow account without the system properly verifying that the funds had actually been released and the transaction completed. As a result, he was able to transfer far more Bitcoins than he was actually entitled to, draining tens of thousands of BTC from the marketplace. The marketplace subsequently closed money transfers from escrow and shut down completely on December 2, 2013. Its (as yet unknown) operator melted into the role of the victim.

The initial theft of 5,400 Bitcoins was resolved in 2014. The FBI monitored the wallets to which the funds were transferred, and when the funds were transferred to the popular exchange Coinbase, the thieves were identified as Nathan Gibson and Sean Mackert. At the time, they were 24 and 21 years old. They faced 20 years in prison, but I was unable to find out what happened to them. In 2020, they appealed, arguing that they were not “traditional criminals.” The funds and assets that the FBI managed to track down were seized, but many accounts remain “dormant” wallets with no activity for many years.

Jiříkovský is a suspect

On discussion forums, especially on Reddit, users are conducting their own “investigation” of cryptocurrency users, and suspicion has fallen on Tomáš Jiříkovský for a number of reasons. The Czech police are quickly investigating these suspicions — there is a lot of circumstantial evidence, which is enough for the community to be “certain,” but not enough for the Czech courts.

👉 Read the rest of the story…

🐑 Sheep Marketplace — how Tomas Jirikovsky and the Czech Minister of Justice came to Bitcoin was originally published in Technology behind Energy Efficiency on Medium, where people are continuing the conversation by highlighting and responding to this story.

Some mandated information. What are RISC-V processors? They are processors based on the open instruction set architecture (ISA). They were created in 2010 at the University of California, Berkeley, and are now controlled by RISC-V International, for which the original authors have relinquished all rights. The association is now run by its members, and the basic idea and driving force is “communism” — that is, sharing the architecture. This is despite the fact that you can buy commercially licensed RISC-V processor cores. The paradox? Not at all...

RISC-V processors are an open alternative to ARM processors. The open instruction set architecture (ISA) means the underlying, common designs for the various important parts of the processors, but these do not create sufficient opportunities for commercial differentiation. The design and maintenance of these parts takes a lot of time, and that’s why companies designing processors choose one of the existing platforms, nowadays mostly ARM — they have the technical chassis and also the assurance of broad software support, on top of that they stick their own thing to sell: the look, the behavior, the performance and of course the logo … 🙂 It is the openness of RISC-V that means the possibility to customize everything easily, to take advantage of the existing basics and to move in a large ecosystem. Simply put, RISC-V can be considered the Linux of the processor world.

Is there any chance of another processor family entering the processor world to replace ARM? Well, it is very difficult and lengthy; just like we said in 1995 about the Wintel platform — it was unthinkable.

Above all, RISC-V has one significant disadvantage that is not an option with ARM, and that is the essence of its openness. This is because individual RISC-V processors do not have to be compatible with each other, as designers can change virtually anything. Therefore, RISC-V International decided to ratify and freeze the ISA at the minimum that all RISC-V labeled processors must meet. In reality, however, there is no enforcement mechanism to prevent different implementations of ISA. Yes, leading RISC-V processor designers such as Andes, SiFive, and CodaSIP comply with the ratified ISA, just with more or less attention to the details that burn them. As a result, far from all code will be portable between processors from different manufacturers without modification. And who will do the modifications?

A few years ago, it would have been a stopgap. I wonder who would force Microsoft to recompile its Windows to the new RISC-V models? No one! Well, nobody’s forcing it anymore either. Much of the real software running is more dependent on the cloud and the internet, if the processor can handle it, it wins. This also means that the importance of the operating system has radically decreased, in fact you just need to port some suitable Linux distributions or even embedded systems that support internet connectivity and you’re done. However, many RISC-V processors are also used in the Internet of Things (IoT) or industry for all sorts of data collection — and you don’t really need Windows for anything there.

It’s true that there have been a few IoT operating system designs, but their usefulness has been small. They were (from an IoT perspective) heavyweight systems that supported too much unnecessarily. While sensors are only good for sending data via MQTT, for example, edge devices need to receive and lightly process data before moving it towards the centre or rather the cloud. Customization of single-purpose systems is taken for granted here.

This is where RISC-V processors are strong. They are efficient, variable and, above all, they now have a better pull commercially. In fact, ARM has been severely hamstrung: in the pampering arms of Softbank, it has lost the incentive to acquire new clients, as its licensing policy has put new wedges at a disadvantage. And for some old clients it became an unattractive, even potential competitor at the time of the contemplated acquisition by Nvidia. And so, after a long time, serious processor startups based on RISC-V began to emerge, mainly aimed at the world of IoT, industry and data processing. There, it was to be expected that customers would reach for an independent platform rather than Nvidia’s property, which competes with anyone in data processing. And the fact that now, almost two years later, the deal is being written off due to regulatory disapproval won’t change much. The damage has been done. And let’s leave aside the situation in China. The latter is trying to take a leading role in the processor field, and giving ARM trouble and having their own platform to influence would be good for China. It just might not be RISC-V at all, there are voices that China is creating its own ISA, as hard as that is. Just for automotive, data collection and IoT purposes.

I find it unlikely that big processor companies like Qualcomm or Marvell will make a mass switch from ARM to RISC-V. Just porting development and testing tools would be extremely expensive and time consuming. But it is certain that these companies will also create RISC-V processor families in their offerings, both for side projects and for customers who wish to avoid ARM.

There is a lot going on in the market with RISC-V. Late last year it was confirmed that Google had ported Android to RISC-V, and Apple has also started using the architecture for some additional features. By the end of 2022, more than ten billion RISC-V processor cores have been sold, which is not a small number (but it’s also not a lot).

There are also serious attempts to get RISC-V processors into datacenters and make them into modern server processors. That’s still in a different league than making a processor that pushes collected data somewhere in the cloud. So far, the most serious contenders are Ventana Micro Systems, Tenstorrent, Rivos and Akeana. They’re not croppers, although you probably won’t know their names unless you’re a connoisseur: but Ventana, for example, has designed the first 64-bit ARM core. The Ventana Veyron VT1 is quite comparable to AMD Genoa in high configurations, for example, beating both Intel Ice Lake and Sapphire Rapids. Some of this can even be ordered for home experiments already, such as HiFive Unmatched boards, but these boards are based on cheap versions of RISC-V processors.

The developments in the processor field will be extremely interesting to watch. Incidentally, Codasip has its roots (and development centre) in the Czech Republic, and its boss Karel Masařík is also a member of the technical production steering committee of RISC-V International (article in E15).

The hope of the year: the RISC-V processors was originally published in Technology behind Energy Efficiency on Medium, where people are continuing the conversation by highlighting and responding to this story.

In Western society, the phenomenon is described by Thomas Piketty and Amory Gethin, of the Paris School of economics, when they document the gradual disappearance of political representation of the interests of the working and lower-middle classes in stark contrast to the number of members of that class in society. Piketty and Gethin prove that this class is too easily replaceable, unorganized, not well-off and therefore useless for politicians.

Moreover, the desire of this social class is for “it to be like it used to be”, where their positions were socially respected and well paid, which firstly is unlikely to return and secondly politically and economically a program of return and obsolescence is not something that can be actively exploited socially or politically. That is why only anti-system forces seize on these challenges and do not hesitate to offer preservation of the status quo, not bothering that it is no longer possible today.

But with the advent of artificial intelligence, the situation is changing. The new changes in the labour market threaten even the most educated, people with university degrees, who were supposed to be immune to market changes. If artificial intelligence replaces graphic designers, writers, analysts, and even doctor-diagnostics, it will take jobs away from people who have devoted a significant portion of their lives to self-employment, who have been in the labor market for a shorter period of time than the average worker, who may be saddled with real (student loans) or moral debts (to their parents), and who had considerable hope of earning a superior income. However, this is beginning to disappear. Soon it will no longer be enough to be a well-educated graphic designer and probably a mediocre medical diagnostician or a good lawyer.

Yet these are the professions that drive politics today. In the US, graduating from law school is the best stepping stone to a super-standard income or a political career. In the Czech Republic, a law degree, together with a medical position and, somewhat unusually, a teaching position, is a good start for a political career. Also, three (of the nine) post-war German chancellors had a law degree, three others studied political science, and Angela Merkel (a physicist) in particular broke from tradition. Also, half of the German presidents were lawyers. The situation is similar in France, where the post of prime minister has been occupied mainly by lawyers or graduates of the political science institute SciencesPo or ENA. Also, four out of fourteen Polish post-revolutionary prime ministers were lawyers.

What will happen when artificial intelligence starts to displace jobs that now have strong political representation? Will these jobs be eliminated as easily as when globalisation outsourced workers’ jobs to Asia? Do you really need a lawyer to write a contract when it will be written just as well by an AI and, moreover, in most cases, by the counterparty’s AI? And will you really be willing to pay a substantial premium for human operators?

According to a Goldman Sachs analysis, nearly half of legal activity in the US can be taken over by AI. This will further widen the income scissors among lawyers in the US, with great lawyers taking on average three times the income of ordinary lawyers. Only the best will win jobs against AI. But what about the rest?

In the long run, AI will surely become the boon that automated weaving machines have become. In the short term, however, it has the potential to destabilise political and social structures and thereby significantly change the direction of human civilisation. I devoted a large part of my book Myths and Hopes of the Digital World to this topic, and a year later I see this problem as increasingly urgent and pressing.

Could this reflection have been the reason why someone decided to raise their hand to remove Sam Altman as head of OpenAI and attempt to return the company to a less collisionist social trajectory? They say maybe. We don’t know.

And that’s one of the bad lessons to be learned from the events surrounding OpenAI: it was probably not just Sam Altman who was being honest, but the entire OpenAI leadership. At least about the reasons that led to Altman’s removal. And that’s not exactly reassuring with all the uncertainty surrounding the impact of AI on society. It doesn’t seem like those in charge are the honest and/or responsible and smart ones…

When AI comes for those with political power… was originally published in Technology behind Energy Efficiency on Medium, where people are continuing the conversation by highlighting and responding to this story.

Why does the best part of wearable electronics and devices using Internet of Things exist? The reason could be to make access to limited resources more efficent by motivating us to change our behavior. In the Fitbit case, the rare resource is our health and Fitbit tries to motivate us to move and increase the health. Energomonitor motivates the user to better use the limited resource — energy — and it makes the user behave in a more economical way or automatize the use. The key word in both cases is the “motivation” because only through change of user behavior can a goal be reached because it depends on the user behavior. And that is my topic: How to use the motivation strategy to change and automate the user behavior in the wanted direction.

Let’s take a look at two concrete examples. I know Energomonitor very well, I participate at its development — it is about connecting software and hardware in order to measure and control energy consumption and security in household or small or middle business. I use Fitbit from its inception, I follow closely its functions and try to think about them — would it be suitable to use in energy sector for Energomonitor, because I suspect those functions are results of serious pondering.

What does psychology tell about motivation of people? There are several reasons: feeling good, desire to reach this feeling, desire to conform, reward and punishment. Fitbit would not sell in society where being fat is a norm. Why does it sell in USA where the percentage of obesity is elevated? Because the cult of skinny beauty and fitness exists there also, therefore there is desire (and hope) to reach and keep a good physical appearance.

Energy savings are different. On some market the energy saving is popular (Germany, Italy, Holland) and on others it’s not in the interest of users, even though it could result in important savings (Czech and Slovak republic). This complicates the sale and marketing of the device, the motivation of user itself is still the same.

In order for devices like Fitbit or Energomonitor to function properly, they must be used in the long term and therefore be interesting for its user. The client can’t put it away as “boring” after a week. How to make it interesting? If all the client gets is a bunch of raw data, he loses the motivation really quickly because the number of steps or consumed watthours does not explain to the user what is going on. That is also a difference between the market position of FitBit and Garmin. Fitbit manufactures a device for low-motivated people who want to move a bit more, Garmin for sport people who are already motivated, know the measured values or are able to study those and want also dive into the raw data analysis. FitBit is not suitable to serious running, while Garmin Fenix/Forerunner is the ideal choice for amateur or professional runners even though both work with same data.

How to create useful gadget

In order for the gadget to be “interesting” and therefore beneficial for its user, it needs to comply with these points:

• Catch the attention
• Persuade
• Keep
• Make the user change

To catch the attention means to offer attractive appearance (and probably price also) and promise interesting results. Technically-oriented people do not like the term “promise” but to promise means to know what you promise and also needs to have clear understanding of the benefits for the customer. Fitbit has a motto “Track activity and sleep. Make health a habit.” It promises you to create healthy habits and it helps you do it. It does not force you to overextend yourself and it is very important for lots of people because they do not want to work out too hard. Sport watch Garmin has slogan “beat yesterday” as in having better results than yesterday, therefore working harder. Energomonitor has slogan “When every watt counts, bill goes down”, because as FitBit it is a tool for a common users who wants to maintain their standard of living and change their habits, continuously, not for a professional energy specialists. Catch the attention means to promise a set of functions tailored to the needs of target group.

To persuade is the second phase. Interested costumers get a set of functions to use and slowly explore them. The learning curve needs to be taken into account because the majority of clients, if they are supposed to use complicated functions, they need to be highly motivated or need to learn them slowly.

To keep is the third phase. User has already explored the gadget and the question is now: will they use it long-term? Without long-term use the desired changes (i.e. losing weight, gaining physical strength or lowering the energy bill) cannot occur.

To make the user change is the last phase. User has enough data to make an informed decision which change is beneficial and within his possibilities and offer it to him. Lose weight? What about 5 kilos in 3 months? Or slightly faster? This is goal setting. In the ideal case, you want to advise the user which goal is realistic and appropriate. Your neighbors with the house of same size as you can save 40 dollars monthly on electricity, why not you also? It is necessary to advise on the ways how to reach the goal: turn off the air-conditioning when leaving the house. And it is necessary to control him, give information and try to motivate him to reach the goal. There are several sub-phases to make the user change:

1. Recommendation of realistic goal
2. Advice on how to reach the goal
3. Information on the process of change and approaching the goal
4. Information when reaching the goal
5. Feedback control loop preventing the relapse (i. e yoyo effect)

Those points may be combined — depending on the goal and quality of data used to the evaluation. Some data are inherently imprecise or instable (the weight changes during the day) so one-time weight dip under the set limit does not mean the weight will stabilize at this value. We need to remember the yoyo effect which takes place after every loss — of weight or the energy consumption. After reaching the goal, the user will no longer be aware of it and it can all revert to the starting point. We need a feedback control loop with a longer interval, warning against weight gain or electricity consumption increase to the initial level.

What stimuli can motivate the user in our opinion?

StimulusUser benefitUser gainOverviewInfo about cost of consumptionStateControlHistory view, control of previousImprovementComparsionComparison with other customersEffectivenessGoalsGuesstimating and setting of realistic goalsOpportunitiesWarningInformation about unusual statesSafety

Those stimuli need to be translated in the user communication and motivation. Let us see concrete approaches stemming from the Energomonitor experience and how Fitbit approaches similar problem.

Specific ways how to make users change their behavior

The application has two ways to initiate change. Firstly, the application is sometimes able to carry out the change itself, for example, it can turn off your air conditioner when you are not at home, and the application can be also automated. It cannot exercise instead of you, though. We will not study the automation in this article, although it would be interesting for the energy sector.

The second example is the motivation to change user behavior. The application communicates with the users and motivates them to modify their behavior according to above described procedures. But how should it be done? Apparently it is not enough to write on web “do not eat, you will lose weight”. If that was enough all dieticians would be suddenly jobless. This communication must be more sophisticated.

Users should be given primarily continuous data to assure him that measuring is being done and that they can check their status anytime. In Fitbit’s case it is the display on a wristband, where you can see the steps, pulse and other current values. For Energomonitor the display is the homebase where the actual quantities of consumption are displayed. The user is assured that everything is under control.

The users also need to have immediate information on the occurrence of any unexpected situation. For example, that they have met the limit of steps on Fitbit or indeed, that they may not reach it. Fitbit does not notify the users on the danger of not meeting the goal at this point. In case of Energomonitor, it may be consumption or costs too large or devices running that are not supposed to run or temperature in the living room reaching 640 ° C and thus suspicion of fire. A typical platform for such notifications is the phone screen, where people are accustomed to receive all sorts of warnings.

Thirdly, analytically processed data should be available so users can immerse themselves in it if they are interested in the situation. We do not talk about processed raw data, but about some interpretation, in which, unfortunately, Fitbit and Energomonitor are still lagging behind. They are currently able to tell you whether you are improving or getting worse, both, however, for an annual fee. It is a welcome part of the monetization of content.

And fourth — the “big picture” — long-term assessment, which summarizes the results and shifts in trends. It serves the user not only as a periodic statement, but also as a confirmation of investment in equipment. Energomonitor prepares seasonal quarterly report (paid), which also tells the customer what to prepare before the next season. Fitbit does not have similar feature, and it bets on continuous Premium reports, but I believe that after the acquisition of exercise application FitStar they will introduce summarizing long-term results.

Let us review therefore, what data types and when are displayed.

ContinuousImmediateAnalyticalPlanningDataRawProcessedInterpretedIn relationsData accessibility Device DisplayMobile ComputerLetter / EmailData content Immediate state Change info Change controlSeasonal Attention User-activated NeededUser-activated Optional Purpose Functionality control Warning before change or damage Effectiveness evaluation Savings and change proposal Motivation Overview Control and warning Comparisons and goals Comparisons and goals Frequency of use DailyWeeklyMonthly Quartal

Now let’s look at the existing situation and how the displaying of the data is handled by Fitbit and Energomonitor.

While the display on the device itself is rather for control (also due to its size and price), the vast majority of communication is conducted through some type of push messages (email, SMS, push into mobile applications) to attract attention and bring users into the phone apps. In the phone app user can quickly verify a daily or weekly goal, saving or number of steps, for deeper data analysis he must go to the web application. The hierarchy of information complies with the limits of individual types of equipment when on the wrist display of Fitbit it is not possible to display any large graphs.

In the case of Energomonitor, there is also an external display. That is the equivalent of wearing Fitbit on the wrist, the possibility to have current and ongoing data visible at the very moment when the user wants or needs them. It helps the user to keep track of what is happening at the consumption point.

Motivation: do not let go of the users and do not bother them

The above are mainly technological conditions, how to reach people with a message on the site where it would be expected and where their frequency is not annoying.

As you can see, both Fitbit and Energomonitor solved the situation very similarly, just with regard to the form-factor of the product which is inherent to the gadget. While in the case of fitness wristbands it is possible to assume that users will be willing to carry a device that only informs about the physical activities, in the case of energy consumption we do not think that would be possible and practical to construct such a dedicated device. In the long term, it seems that there is a connection between the mobile phone or watch and fitness features, as is indeed already happening today.

In the case of Energomonitor, the logical link is the mobile phone display and an external display placed in a suitable place in the house. The users then have all the data at their fingertips.

… will be continuing (if somebody will be interested in) …

Strategy of motivation to change the behavior in the wearable and Internet of Things world —… was originally published in Technology behind Energy Efficiency on Medium, where people are continuing the conversation by highlighting and responding to this story.

The reasons for diversity

Why would a standard be good? So, the devices can easily connect to other manufacturers devices. You bought a NetAtmo weather station. Do you need a thermostat of the same company or will a thermostat of another brand work with the NetAtmo forecast? Why does a radio-controlled thermostatic valves need other radio interface and why can’t the box, managing the video camera system, also do the valves management? However, these cameras are not connected with an electronic safety system of other brand.

There are valid reasons.

Business problems: struggle for domination on the market

I am going to discuss the business reason just briefly. Companies want to dominate the market. When their format becomes the de facto standard, they get income from patents; they can shape the market according to their wishes and even block the entry of competitors. You may think that modern online companies do not behave this way but that is just a myth. They do, and very often, when they can, they go as far as the law will allow them. Smaller companies can’t do as the bigger ones because they do not have the necessary size and budget.

Technical: the demands are quite heterogeneous

There are also technical reasons. A standard would need to be in fact very complex, including not only the radio and cable communication, but also the application interface. The fact that there are several radio interfaces is caused by different needs. Some sensors send very little data, with a low frequency: a sensor for a door opening transmits its state only several times a day. Others send very little data very often: a sensor for the electricity meter sends a signal once every 1–90 seconds with several KB of data. Others sensors send a lot of data but not very often — i. e. wireless camera in the security system, sending picture just in case of emergency. And there are even sensors sending lots of data all the time, for example video cameras in security systems, which send almost the rate of the data on the internet. Take into account also the fact that some are used on a short distance, while others are used for longer distances and some need to emit the signal for hundreds of meters or more. Therefore more frequencies are used, not only 2,4GHz, but also 433 and 868 MHz range.

The solution is “simple”: create a universal radio protocol for all those uses. ZigBee tried this approach but with a lot of limitations. The biggest limitation was the financial one: license fees. But there were lots of technical ones also. Other protocols, which are planned or suggested in Bluetooth, WiFi or Google Thread, are just conglomerates enveloping several protocols (Bluetooth vs LE) under one name and “profiles”. In fact they are independent radio protocols. The costs for running and identification of more protocols at once are not negligable. You need much more powerful hardware, which is not very pleasant in the IoT architecture (because of dimensions and price), or because you need more power and therefore the battery life suffers.

That is our issue at Energomonitor, too. We employ an older radio protocol C2 (used by Current Cost before they bancrupted and moved in to the new Current Cost company in Hongkong) and our proprietary Chirp which is better, more robust etc.

Enabling them concurrently is painful, the device needs to detect and wait. It lowers the performance and brings no real profit. We decided in the end not to implement them both, we use only the newer one and if somebody needs to use the device within an older network, we equip the device with the older protocol.

Missing application interface

Last, but not least a very important issue is letting the gateway know what to do with the data from an unknown device. It sounds awesome, to have a gate (or “edge router”) for the IoT included in the WiFi router and being able to operate all the interconnected devices. Nowadays you need to have a different gate for every device of one manufacturer, which is not practical.

The gate is not only a receiver of the data through the radio interface; it also processes the data and sends it onwards to the internet. In the case of Energomonitor, the data from the sensor the gate registers is encrypted and forwarded to our servers, through the older internal protocol or standardized MQTT. It is embedded in our firmware and it is not easy to make it happen without it. I can imagine an “Appstore” for different routers that can let you use the Energomonitor app which would offer the same functionality. There are several issues, though. The sensors manufacturer should support as many “appstores” as the router suppliers (they won’t agree on a standard in the near future), it should be tested extensively. The most data compact sensors of Energomonitor send the data once every second. How do you want to make sure that this is done by a router fulfilling other tasks that our coders are even not aware of?

We are leaving the world of single-purpose devices and entering the realm of full-fledged embedded operating systems and problems, which their servicing and developing for real-time systems involves — it is called “edge computing” and I wrote an another article about it.

That is not something the small teams in IoT can afford. There is some progress, though. Google and Samsung are developing their proprietary IoT operating systems focused on parallel running of several different tasks and bridging the manufacturers. Some other companies, including IBM, are also working with a different progress and level of seriousness for this coquetry. There will be so much happening in this field, but who wants to sell today needs to stay with the tested and proven — single-purpose devices with a low price. Organic technological development, including the lowering of hardware prices and increase in performance, will solve lots of problems during this time.

Borders of IoT philosophy

My last topic is the philosophy itself. In fact, the great technological interconnection of the IoT world is not important. Gathering the data about the energy consumption is a different task than telling the blinds to lower themselves or gathering camera and security sensor data. It is difficult to find a simple and beneficial concept, which would need such an interconnection. Of course, it is possible to lower the blinds every time when the lights in the living room are turned on — but why? If you want to do this, you can do it manually. If you want to solve this problem, you should be interested in data interconnection, when you take a state of one system (light control) and forward it to another system (order to lower the blinds). For this purpose you do not need to connect the device on the hardware level, but with an API bridge, as offered by IFTTT or Zapier.

Business rules

What is the decisive factor in the end? The business suitability of the chosen solution. Nowadays there is a shortage of real customer scenarios, which would justify a bigger integration of components of IoT. Geeks are leading the demand but they are not a customer group that would be interesting in long term. Therefore a single standard for IoT is still a matter of dreams. There would be several partial solutions, practices and procedures, widespread and maybe even widely accepted in a group of sensors (as KNX in automated parts) but there will be lots of reasons to use the proprietary solution.

What is important for user is the extent to which will the solution perform as promised…

You will find more about IoT and Energomonitor on our Medium blog Technology behind Energy Efficiency, Facebook, LinkedIn and on Twitter.

The fairy tale about a single standard for the Internet of Things was originally published in Technology behind Energy Efficiency on Medium, where people are continuing the conversation by highlighting and responding to this story.

Well, except for the fact that Czechs don’t consider energy savings worth it, which contrasts with the approach of Dutch or Spanish customers?

Our biggest issue is to communicate to the customers ways of getting the most out of Energomonitor.

When someone from our team looks at readings on a energy consumption graph and after taking into account “the kind of heating and kind of property”, they can find out where there is room for improvement. Most customers aren’t able to do this and we cannot interpret the graphs for everybody. So the struggle is with how to communicate to the customers, ways of getting better performance.

Let’s look at ways to make energy savings. We have created a list in which we follow these parameters:

• the amount of potential savings
• investment
• interference with the user’s convenience, habit and repetition
• the possibility of automation

There are several different approaches in this list. Take, for example insulation of non-insulated house. It is capital-intensive, it is significant intervention into the user’s convenience, it’s a one-off and there is a high amount of savings in heating. The insulation is always worth the money, but not everyone wants to do. Here are some simple tips and tricks how to change things get savings and do it with very little work.

The numbers we used here are made up. We did this so anybody, even with very little knowledge of energy, can understand what we are doing.

Minimal electricity consuption

Let’s look at the example of minimal consumption. We have defined minimal consumption as the lowest continuous power consumption, which is in the measured property reaches.

It would seem that the lowest electricity consumption is zero watts, but that’s not true. In households and small businesses there are number of appliances that are in stand-by mode, or permanently draw some current. Doing so throughout the day to a considerable amount of energy used. If the customer does not heat with electricity minimal consumption can easily be over half the cost of electricity.
Firstly, you won’t be able to measure your minimal consumption without Energomonitor or some other smart metering device. Your tool has to be able to measure this minimum consumption and any consumption from repeating process.

What can we do about?

You can check the individual appliances and determine whether it is necessary to have them on or even in stand-by mode. Usually this is the case with old appliances like grandpa’s old radio that is still plugged in but nobody uses it. The transformers of bigger appliances usually consume something, even if the device appears to be disabled. Appliances produced up to 2003 are very problematic is this regard and devices produced up to 2006 also have many issues with stand-by consumption.

Then came the cursed EU regulations that penalized the sale of appliances that consumed in stand-by mode.

When you bought an appliance the last time, did you check if it consumed energy in stand-by mode?

After optimizing the minimal consumption, you should get below 30 % of total consumption. How does such a difference translate into the budget? The figure below shows a typical family house, where the electricity is not used to heat the house, but it is used only for heating water.

(30 Kč is 1 Euro)

Before optimization the minimal consumption was about 40% of the bill and after optimization it has fallen below 25%. The difference in the cost of electricity including the dividing rate and using the actual consumption is about € 200 per year, household savings by not connecting appliances that are not used.

However, this does not mean that the DVD player or television are not plugged in. These appliances should be in Saving mode and only take 5 seconds longer to start. But the rarely used desktop computer should be unplugged.

Problem of permanent consumption is that there is not a one time solution.

It is necessary to check the consumption, regularly. The next graph shows that minimal consumption over a year at the house is slightly increasing.

Red regressive line says that growth is statistically permanent and is increasing with connection of new appliances. You should ask yourself if this 25 W increase about 30EUR year, is returned at least in personal comfort. Or if you are just throwing money out the window? Are you returning to your original habits (desktop used once and plugged back in the socket), or if you have new appliances that are causing the higher cost. That is something you have to decide yourself.

The energomonitor tasks are in this case as follows:

• prepare an understandable metrics and explain it to you
• offer you a comparison for the measured values
• advise you on how to achieve better results
• motivate you to have a better result
• a long term monitoring whether the result has not worsened and possibly help to improve it or make an assessment that financial deterioration led to improving your personal comfort, or has other benefits.

It was my intention to show at least partially, in what direction and manner of data analysis we can do. In fact, the subject is much broader…

WTF of Energy Efficiency: A Quest for the Right Metrics was originally published in Technology behind Energy Efficiency on Medium, where people are continuing the conversation by highlighting and responding to this story.

On the Edge of a Network, or in the Fog Inside

Why is it called so? The name refers to the fact that, unlike cloud solutions, which imply storing of the content (data, apps, etc.) in a data centre, the points of contact in the Fog are shifted to the edge of a network (therefore it is called edge computing), or, in other words, they are spread out amongst their users just like fog (and now you get the fog thing). Both of the metaphors describe the very same thing. The cloud is up, while the fog comes down amongst us, the users, as fog computing fans like to say.

Let’s take a closer look at fogging. What is this all about? As already mentioned, fog computing involves moving data interface as close to the user as possible. The data is not forwarded in several network hops, to the central cloud located on the other side of the globe, but in just one hop, directly to the closest network component. The component is in charge of processing and assessing the data, answering to it, if possible, or getting back to the cloud. It resembles of CDN networks a bit, except the fact that a CDN merely stores prearranged data and sends it to the customer who picked a particular piece of it, from the closest repository. Unlike CDNs, the fog is able not only to store but also to process the data, plus it creates and sends its own that may be asynchronously updated via cloud.

Why is the Internet of Things so Close to the Edge?

What is the main advantage of the fog is speeding up feedback coming from a remote data centre. It is crucial for 5G mobile networks in particular, since the quicker the response the lower the latency and jitter. Are the fog and the cloud comparable at all?

Let me put this in practical terms. The context I deal with the Edge mostly, are smart cities and the business we do at Energomonitor.

Every time we do some measuring at Energomonitor (temperature, consumption, or any other readings), our meter sensors must be directly connected to the Internet, or, to be more precise, to the “homebase”. If we take it from the perspective of a network structure, the homebase means the edge. We went for this soultion for practical as well as economical reasons in the first place; it would be really expensive to connect every single sensor to the Internet. It would be also hard to maintain and manage, not to mention the problems with power supply, battery lifespan, and, last but not least, with complex installation. However, then it turned out that a HAN star network (Home Area Network), which is concentrated around a homebase, brings a lot of further benefits.

Homebase Functions

Homebase as an edge device does all the stuff that a sensor is not able to do, since it is fitted with a simple (which means: cheap) processor. The homebase counts up meter sensor readings, multiplies them by the price of a particular unit, downloaded via cloud, so that it shows energy consumption and expenses on a local screen. It is also able to react to measure value exceeding, if needed. This feature is used by the latest generation of homebase devices, fitted with red illuminated displays that indicate excessive energy consumption.

Native cloud devices were not able to provide the calculation by themselves, they needed to be connected to the cloud server, which was not that useful though, in standalone emergency operations for instance. Semi-standalone operations, provided by a homebase, i.e. by an edge device, turned out to be crucial for autonomous thermostats. Another advantage of the edge solutions form the perspective of an end user is that a homebase device might stay tucked away somewhere on the wall, while the user makes do with an access to a thermostat regulator, equipped with a display and a keyboard. The user controls the heating via the regulator, as simple as it is. The data is forwarded to the homebase device and further, if needed. The user can also control the heating online, via an app. The data is forwarded to the homebase device via the cloud, and to the display then, so the user is kept updated about the temperature on a regular basis. The device may also operate in an automatic mode, which means that the temperature curve is generated partly by the cloud, partly by the homebase, on the basis of current weather conditions as well as the regulator requirements. What is crucial here is the fact that he heating works, even if the Internet does not, since the homebase “knows” what to do. The only problem is that, in case it is not provided with the latest readings on weather conditions, it keeps heating, regardless of the fact that the temperature outside has been rising for the last half an hour or so. The device is not fully dependent on working Internet connection but still it needs to be updated with the data to stay “smart”. I hope that this example has been clear enough to explain what the fog and the edge device are, and what are the benefits of the concept. It is obvious that, in the world of the IoT, they have been discovered in the course of many years by many different developers, on the trial-and-error basis.

Why are that many IT companies, such as Dell, so optimistic when it comes to the edge computing? Why do they support it so actively? And why do they expect it to be profitable? Speaking of Dell, as we will see, it would be happy to sell its own servers as edge devices.

The Holy Grail of the Universal Homebase

The edge device might be provided with an API, able to register many different IoT devices that would share their profiles with the edge device. The profiles downloaded from the cloud would contain data necessary to set up and provide services via API, which translates into all the operations an edge device should be able to perform, i.e. what to forward to the cloud, what to get back to the sensor or another IoT device. The main pracitcal benefit of this solution is clear: it would be enough to have only one device operating numerous systems. The very same device would control Energomonitor, Hue, NetAtmo, etc. That would involve more transparent structure, easier to control and to be networked, as well as much faster wireless network, and lower prices of course. Last but not least, it would translate into a secured market for the edge hardware providers, such as Dell. Now the dots are connected!

Everything has its pros and cons though. First off, it seems really hard to create and provide an environment to the third parties, which would be safe, stable and automated enough for the turbulent world of the Internet of Things. That is the reason why all the IoT companies make edge devices by their own (such as we do) and why there are tons of various smart “boxes” in your house, instead of just one. It makes sense, if we take that it is significantly cheaper to build a single-purpose hardware device than a multi-purpose, both SW and HW-compatible, versatile one. Anyway, we are in a fair way to versatility, it is going to take some time though. Plus it involves politics. Companies do not want to give up on a chance to be a kind of an “edge hub” in the future. At other times, they are not ready or technologically advanced enough to meet the challenge. This year, some of the companies, such as Samsung, LG, or Google, will be trying to change it. They already have presented first home router-connected “edge hubs” on trade fairs but all of them have their cons, for instance, Google stubbornly insists on their own Thread radio protocol, plus they keep staying incompatible with the Nest thermostat, which aims for the same position. Actually, what cause the most of the problems with building a truly versatile edge box, are those various radio protocols and a really wide range of functions IoT covers nowadays.

Truly “versatile” edge devices find their use in complex industry installations nowadays, rather than in households, as there are more predictable scenarios and technological procedures involved. However, there is an unwritten rule that most of the solutions well-tried in industry come down to the mass market. One of few examples from the local market is Turris Omnia, a multi-tasking home router supporting various IoT devices. Those guys set really high goals and we keep our fingers crossed for them.

How Much Does it Pay?

The importance of edge devices and fog networks will be increasing hand in glove with an increasing number of IoT devices, more and more available, smarter and smarter. Their smooth operation will be interfered by many heterogenic and incompatible transfer protocols, such as HTTP/S, MQTT, STOMP, AMQP Zigbee, Zwave, BTSmart, wmbus, and many more (our proprietary ChiRP included). It will take much time to harmonize it, since each radio protocol is used for different purposes, just as each message transfer protocol finds its own use.

For now, it appears that the importance of API in edge devices will be increasing, and it is a perfect time to catch the wave and start building the environment for embedded devices. In fact, there are still a lot of unknowns in the game played by many bigwigs, such as Google/Nest, Apple, Samsung, LG, or router manufacturers, D-Link, Netgear Ubiquit, Cisco/Linksys, or Synology, who notice increasing demand for smart routers and will not let the chance to slip by for sure. What we definitely can expect in the nearest future is an overcrowded edge device market hard to deal with.

PS: More about Energomonitor technology/architecture is on our website, just there are old pictures of old homebases…

Edge Computing and Fog Computing; or, on the Benefits of Fogging was originally published in Technology behind Energy Efficiency on Medium, where people are continuing the conversation by highlighting and responding to this story.