Previewing “The Future Is Smart”: Siemens Leads Way In IoT Transformation

Posted on 26th July 2018 in 3-D printing, Augmented Reality, data, design, Essential Truths, Internet of Things, M2M, maintenance, management, manufacturing, paradigm shift, sensors, strategy, transportation

Huzzah!

On August 7th, HarperCollins’ new Leadership imprint (formerly Amacom) will publish The Future Is Smart, my guide to IoT strategy for businesses and the general public.  BTW: write me if you’d like to arrange a speaking engagement/book signing event!

As part of the build-up to the release, here’s another excerpt from the book, drawn from Chapter 5: “Siemens and GE:Old War Horses Leading the IoT Revolution.” It zeroes in on these two industrial companies from the 19th (!!) century that are arguably among the top IoT companies in the world (although, sadly, GE’s transformation, which I’ll detail in the next excerpt, has not resulted — so far — in a return to its former profitability). I highlighted these two companies in part to give comfort to old-line manufacturers that have been reluctant to embrace the IoT, and in part to shame them: if they can do it, why can’t you?

Siemens is a particularly exciting example, applying IoT thinking and technology to gain a competitive edge in the railroad business, which it has been involved in since the 19th century, and because its Amberg “Factory of the Future” is the epitome of the benefits of applying the IoT to manufacturing,  The excerpt is long, but I think the details on Siemens’ IoT transformation will make it worthwhile reading.

 

For all their (referring to Siemens and GE) own distinctive products and services, there are startling parallels between the two that are relevant to this book, particularly for readers whose companies have been unaware of the IoT or are modestly testing the waters. Both Siemens and GE have fully committed to the IoT and are radically reinventing themselves, their products, and their services. 

At the same time, they are not abandoning the physical for the digital: they still make products such as trains (NB: since this book went to press, GE announced it will quit to locomotive business as it struggles to regain momentum) and large medical diagnostic devices that remain necessary in the new economy, and those devices (as well as the new software lines) are used by many other companies in their own manufacturing. Both companies aren’t just testing the IoT: they are on the bleeding edge of innovation in terms of both IoT technology and services.

Siemens and GE embody most of the marks of the IoT company outlined in the first chapter:

  • Unprecedented assembly-line precision and product quality
  • Drastically lower maintenance costs and product failure
  • Increased customer delight and loyalty
  • Improved decision-making
  • Creating new business models and revenue streams

And, while they haven’t formally addressed the sixth IoT hallmark, the circular management organization, both companies exhibit management characteristics consistent with it.

Bottom-line: if these two relics of the early Industrial Age can make the IoT transformation, why can’t you?

(Siemens’) innovations in industrial automation are now associated with the concept of the digital factory. “Siemens set the course for the digital automation of entire production facilities as far back as 1996, when the launch of its Totally Integrated Automation (TIA) Portal enabled companies to coordinate elements of their production operations and to closely intermesh hardware with software.”

Siemens has benefited in recent years from the German government’s formal strategy for what it calls “Industrie 4.0,” to merge physical products with digital controls and communications. The initiative is supported by funding from the German Federal Ministry of Education and Research and the German Federal Ministry of Economic Affairs and Energy and emphasizes the merger of the digital and physical in manufacturing through cyber-physical control systems. Because the U.S. federal government doesn’t weigh in on specific economic plans to the same extent, the concept is more advanced in Europe, and the term has gathered cachet, especially as specific examples have proved profitable.

Factory of the Future:
The shining example of Industrie 4.0 is the previously mentioned Siemens plant in Amberg. It has increasingly computerized over the past 25 twenty-five years, and now is a laboratory for fusion of the physical and digital.

The plant’s 99.99885 percent quality rate would be astounding by any measure, but is even more incredible when you realize that it does not do daily repetitions of the same mass-production product run. Instead, Amberg is where the company makes the Simatic programmable logic controls (PLCs) .. that are the heart of its industrial output and which are used worldwide to allow Machine-to-Machine (M2M) automated assembly line self-regulation. They are made in more than a thousand variations for 60,000 customers worldwide, requiring frequent readjustments of the production line. In one of the ultimate examples of eating your own dog food, a thousand Simatic units are used to control the assembly line. Total output at the factory is 12 million yearly, or approximately one per second.

One downside of the Amberg system’s efficiency is that automation has nearly eliminated assembly line jobs: the only time humans touch one of the products is to put the initial circuit board on the assembly line. The 1,100-person workforce deals almost entirely with computer issues and overall supervision of the assembly line. Nevertheless, Siemens doesn’t visualize a totally automated, workerless factory in the future:

“We’re not planning to create a workerless factory,” says [Plant Manager Professor Karl-Heinz] Büttner. After all, the machines themselves might be efficient, but they don’t come up with ideas for improving the system. Büttner adds that the employees’ suggested improvements account for 40 percent of annual productivity increases. The remaining 60 percent is a result of infrastructure investments, such as the purchase of new assembly lines and the innovative improvement of logistics equipment. The basic idea here, says Büttner, is that “employees are much better than management at determining what works or doesn’t work in daily operation and how processes can be optimized.” In 2013 the [plant] adopted 13,000 of these ideas and rewarded employees with payments totaling around €1 million.

As Siemens develops new IIoT software, it is deployed at the Amberg factory to control the Simatic control units, which generate more than 50 million data points daily for analysis. Among other programs, the factory runs the NX and Teamcenter project lifecycle management software, allowing the staff to share realtime insights on the assembly line and fine-tune its operation.

Siemens’s strategy of merging the physical and digital has meant that its software offerings constantly expand, and they facilitate the kind of real and virtual collaborative workstyles that will be discussed at length in Chapter 8. Among others, they include offerings that specifically address key aspects of the IoT:

  • Product Lifecycle Management software programs, which let engineers both model new products and extensively test them virtually, without having to build and test physical models. This both cuts costs and allows more experimentation with “what if” variations on a design, because the risk of creating alternatives is so low. As we will see later, products designed with PLM can reach the market 50 percent faster. One particularly interesting part of the PLM offerings is one specifically for additive manufacturing (i.e., 3-D printing), to capitalize on this emerging option. Siemens has brought all of these programs together under the Teamcenter label, emphasizing that it provides an “open framework for interoperability,” a critical example of the “share the data” Essential Truth discussed in Chapter 2, allowing anyone who needs it companywide to access critical realtime data.
  • Digital Twins used in coordination with PLM, discussed earlier (Chapter 4) as the highest manifestation of the digital/physical synthesis, allow rigorous testing of products before they are launched.
  • Perhaps the most important of these software offerings for full realization of the Industrie 4.0 vision is the new combination of Siemens XHQ Operations Intelligence Software with the open-systems Siemens MindSphere cloud that adds advanced analytics and machine learning. Also, because it is cloud-based, the XHQ data can be ported to other cloud-based applications. If your company is considering an IoT initiative, the cloud-based alternative not only can save money compared to self-storage, but also opens the opportunity for using cloud-based Software as a Service (SaaS).

 

Railigent

Fittingly, some of the most dramatic examples of Siemens’s IoT thinking in action have centered on one of its oldest lines of business: those electric trains invented in the nineteenth century.  The company’s Railigent system (which connects to its IoT Mindsphere platform) can:

  • cut rail systems’ operating costs by up to 10%
  • deliver eye-popping on-time performance (only 1 of 2,300 trains was late!)
  • and assure 99% availability through predictive maintenance.

Its new Mobility Services have taken over maintenance for more than fifty rail and transit programs.

Again, the company’s years of experience building and operating trains pays off in the cyberworld. Dr. Sebastian Schoning, ceo of Siemens’s client Gehring Technologies, which manufactures precision honing tools, told me that it was easier to sell Siemens’s digital services to his own client base because so much of the products they already own include Siemens devices, giving his customers confidence in the new offerings.

The key to Siemens’s Mobility Services is Sinalytics, its platform architecture for data analysis not just for rail, but also for industries ranging from medical equipment to windfarms. More than 300,000 devices currently feed realtime data to the platform. Sinalytics capitalizes on the data for multiple uses, including connectivity, data integration, analytics, and the all-important cyber security. They call the result not Big Data, but Smart Data. The platform also allows merging the data with data from sources such as weather forecasts which, in combination, can let clients optimize operating efficiency on a real-time M2M basis.

Elements of an IoT system on the trains that can be adapted to other physical products include:

  • Sensing. There are sensors on the engines and gearboxes. Vibration sensors on microphones measure noises from bearings in commuter trains. They can even measure how engine oil is aging, so it can be changed when really needed, rather than on an arbitrary schedule, a key predictive maintenance advantage.
  • Algorithms: These make sense of the data and act on it. They read out patterns, record deviations, and compare them with train control systems or with vehicles of the same type.
  • Predictive Maintenance: This replaces scheduled maintenance, dramatically reducing downtime and catastrophic failure. For example: “There’s a warning in one of the windows (of the control center display): engine temperature unusual. ‘We need to analyze the situation in greater depth to know what to do next—we call it root cause analysis,’ (says) Vice-President for Customer Support Herbert Padinger. ‘We look at its history and draw on comparative data from the fleet as a whole.’ Clicking on the message opens a chart showing changes in temperature during the past three months. The increased heat is gradually traced to a signal assembly. The Siemens experts talk with the customer to establish how urgent the need for action is, and then take the most appropriate steps.”8 Padinger says that temperature and vibration analyses from the critical gearboxes gives Siemens at least three days advance notice of a breakdown—plenty of time for maintenance or replacement. Predictive maintenance is now the norm for 70 to 80 percent of Siemens’s repairs.
  • Security: This is especially important given all of the miles of track and large crowds on station platforms. It includes video-based train dispatch and platform surveillance using Siemens’s SITRAIL D system, as well as cameras in the trains. The protections have to run the gamut from physical attacks to cyber-attacks. For security, the data is shared by digital radio, not networks that are also shared by consumers.

When operations of physical objects are digitized, it allows seamlessly integrating emerging digital technologies into the services—making these huge engines showcases for the newest technologies. For example, Siemens Digital Services also included augmented reality (so repair personnel can see manuals on heads-up displays), social collaboration platforms, and—perhaps most important—3-D printing-based additive manufacturing, so that replacement parts can be delivered with unprecedented speed. 3-D printing also allows a dramatic reduction in parts inventories, It allows for replacement of parts that may no longer be available through conventional parts depots. It may even improve on the original part’s function and durability, based on practical experience gained from observing the parts in use. For example, it’s often possible with 3-D printed replacement parts to consolidate three or four separate components into a single one, strengthening and simplifying it. Siemens has used 3-D printing for the past last three years, and it lets them assure customers that they will have replacement parts for the locomotive’s entire lifespan, which can exceed thirty years.

The new Mobility Services approach’s results are dramatic:

  • None of the Velaro trains that Siemens maintains for several operators have broken down since implementing Sinalytics. Among those in Spain only one has left more than fifteen minutes behind time in 2,300 trips: a 0.0004 percent lateness rate.
  • Reliability for London’s West Coast Mainline is 99.7 percent.
  • Perhaps most impressive because of the extreme cold conditions it must endure, the reliability rate for the Velaro service in Russia is 99.9 percent.11

Siemens’s ultimate goal is higher: what the company calls (pardon the pun) 100 percent Railability.

When it does reach those previously inconceivable quality benchmarks, Siemens predicts that, as the software and sensors evolve, the next stage will be new business models in which billing will be determined by guaranteeing customers availability and performance. The manufacturing industry is now at the stage where the automation of complete workflows is the only way to ensure a long-term, defendable, competitive position.

Siemens emphasizes that it’s not enough to simply digitize the design process. Everything from design through supply chain, manufacturing, distribution, and service must be linked in a continuous digital web, with “complete digital representation of the entire physical value chain is the ultimate goal.”

 

The fact that Siemens doesn’t just sell these IoT services but makes their own manufacturing the laboratory to develop and test them is an incredible testimonial to the IoT’s transformative potential in every aspect of companies’ operations. So, as I asked above, why are you holding back? Like to think that The Future Is Smart will give you the manual you need to make the transition (why wait for August  7, when you can preorder today?).

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#IoT Sensor Breakthroughs When Lives Are On the Line!

Posted on 7th July 2017 in agriculture, data, defense, energy, Homeland Security, Internet of Things, M2M, maintenance, mobile, security, sensors, smart cities, US government

One of my unchanging principles is always to look to situations where there’s a lot at stake — especially human lives — for breakthroughs in difficult issues.

Exhibit A of this principle for the IoT is sensor design, where needing to frequently service or recharge critical sensors that detect battlefield conditions can put soldiers’ lives at stake (yes, as long-time readers know, this is particularly of interest to me because my Army officer son was wounded in Iraq).

FedTech reports encouraging research at DARPA on how to create sensors that have ultra-low power requirements, can lie dormant for long periods of time and yet are exquisitely sensitive to critical changes in conditions (such as vehicle or troop movements) that might put soldiers at risk in battlefield conditions.

The  N-ZERO (Near Zero RF and Power Operations)  program is a three-year initiative to create new, low-energy battlefield sensors, particularly for use at forward operating bases where conditions can change quickly and soldiers are constantly at risk — especially if they have to service the sensors:

“State-of-the-art military sensors rely on “active electronics” to detect vibration, light, sound or other signals for situational awareness and to inform tactical planning and action. That means the sensors constantly consume power, with much of that power spent processing what often turns out to be irrelevant data. This power consumption limits sensors’ useful lifetimes to a few weeks or months with even the best batteries and has slowed the development of new sensor technologies and capabilities. The chronic need to service or redeploy power-depleted sensors is not only costly and time-consuming but also increases warfighter exposure to danger.”

…. (the project has) the goal of developing the technological foundation for persistent, event-driven sensing capabilities in which the sensor can remain dormant, with near-zero power consumption, until awakened by an external trigger or stimulus. Examples of relevant stimuli are acoustic signatures of particular vehicle types or radio signatures of specific communications protocols. If successful, the program could extend the lifetime of remotely deployed communications and environmental sensors—also known as unattended ground sensors (UGS)—from weeks or months to years.”

A key goal is a 20-fold battery size reduction while still having the sensor last longer.

What cost-conscious pipeline operators, large ag business or “smart city” transportation director wouldn’t be interested in that kind of product as well?

According to Signal, the three-phase project is ahead of its targets. In the first part, which ended in December, the DARPA team created “zero-power receivers that can detect very weak signals — less than 70 decibel-milliwatt radio-frequency (RF) transmissions, a measure that is better than originally expected.” This is critical to the military (and would have huge benefits to business as well, since monitoring frequently must be 24/7 but reporting of background data  (vs. significant changes) would both deplete batteries while requiring processing of huge volumes of meaningless data). Accordingly, a key goal would be to create “… radio receivers that are continuously alert for friendly radio transmissions, but with near zero power consumption when transmissions are not present.” A target is  “exploitation of the energy in the signal signature itself to detect and discriminate the events of interest while rejecting noise and interference. This requires the development of passive or event-powered sensors and signal-processing circuitry. The successful development of these techniques and components could enable deployments of sensors that can remain “off” (that is, in a state that does not consume battery power), yet alert for detecting signatures of interest, resulting in greatly extended durations of operation.”

The “exploitation of .. energy in the signal signature itself sounds reminiscent of the University of Washington research I’ve reported in the past that would harness ambient back-scatter to allow battery-less wireless transmission, another key potential advance in IoT sensor networks.

The following phrases of N-ZERO will each take a year.

Let’s hope that the project is an overall success, and that the end products will also be commercialized. I’ve always felt sensor cost and power needs were potential IoT Achilles’ heels, so that would be a major boost!

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Libelium: flexibility a key strategy for IoT startups

Posted on 8th December 2016 in agriculture, cities, collaboration, data, energy, environmental, government, home automation, Internet of Things, logistics, m-health, M2M, maintenance, manufacturing, mobile, open data, sensors, smart cities, smart home, transportation

I’ve been fixated recently on venerable manufacturing firms such as 169-yr. old Siemens making the IoT switch.  Time to switch focus, and look at one of my fav pure-play IoT firms, Libelium.  I think Libelium proves that smart IoT firms must, above all, remain nimble and flexible,  by three interdependent strategies:

  • avoiding picking winners among communications protocols and other standards.
  • avoiding over-specialization.
  • partnering instead of going it alone.
Libelium CEO Alicia Asin

Libelium CEO Alicia Asin

If you aren’t familiar with Libelium, it’s a Spanish company that recently turned 10 (my, how time flies!) in a category littered with failures that had interesting concepts but didn’t survive. Bright, young, CEO Alicia Asin, one of my favorite IoT thought leaders (and do-ers!) was recently named best manager of the year in the Aragón region in Spain.  I sat down with her for a wide-ranging discussion when she recently visited the Hub of the Universe.

I’ve loved the company since its inception, particularly because it is active in so many sectors of the IoT, including logistics, industrial control, smart meters, home automation and a couple of my most favorite, agriculture (I have a weak spot for anything that combines “IoT” AND “precision”!) and smart cities.  I asked Asin why the company hadn’t picked one of those verticals as its sole focus: “it was too risky to choose one market. That’s still the same: the IoT is still so fragmented in various verticals.”

The best illustration of the company’s strategy in action is its Waspmote sensor platform, which it calls the “most complete Internet of Things platform in the market with worldwide certifications.” It can monitor up to 120 sensors to cover hundreds of IoT applications in the wide range of markets Libelium serves with this diversified strategy, ranging from the environment to “smart” parking.  The new versions of their sensors include actuators, to not simply report data, but also allow M2M control of devices such as irrigation valves, thermostats, illumination systems, motors and PLC’s. Equally important, because of the potentially high cost of having to replace the sensors, the new ones use extremely little power, so they can last        .

Equally important as the company’s refusal to limit itself to a single vertical market is its commitment to open systems and multiple communications protocols, including LoRaWAN, SIGFOX, ZigBee and 4G — a total of 16 radio technologies. It also provides both open source SDK and APIs.

Why?  As Asin told me:

 

“There is not going to be a standard. This (competiting standards and technology) is the new normal.

“I talk to some cities that want to become involved in smart cities, and they say we want to start working on this but we want to use the protocol that will be the winner.

“No one knows what will be the winner.

“We use things that are resilient. We install all the agents — if you aren’t happy with one, you just open the interface and change it. You don’t have to uninstall anything. What if one of these companies increases their prices to heaven, or you are not happy with the coverage, or the company disappears? We allow you to have all your options open.

“The problem is that this (not picking a standard) is a new message, and people don’t like to listen.  This is how we interpret the future.”

Libelium makes 110 different plug and play sensors (or as they call them, “Plug and Sense,” to detect a wide range of data from sources including gases, events, parking, energy use, agriculture, and water.  They claim the lowest power consumption in the industry, leading to longer life and lower maintenance and operating costs.

Finally, the company doesn’t try to do everything itself: Libelium has a large and growing partner network (or ecosystem, as it calls it — music to the ears of someone who believes in looking to nature for profitable business inspiration). Carrying the collaboration theme even farther, they’ve created an “IoT Marketplace,” where pre-assembled device combinations from Libelium and partners can be purchased to meet the specific needs of niches such as e-health,  vineyards, water quality, smart factories, and smart parking.  As the company says, “the lack of integrated solutions from hardware to application level is a barrier for fast adoption,” and the kits take away that barrier.

I can’t stress it enough: for IoT startups that aren’t totally focused on a single niche (a high-stakes strategy), Libelium offers a great model because of its flexibility, agnostic view of standards, diversification among a variety of niches, and eagerness to collaborate with other vendors.

BTW: Asin is particularly proud of the company’s newest offering, My Signals,which debuted in October and has already won several awards.  She told me that they hope the device will allow delivering Tier 1 medical care to billions of underserved people worldwide who live in rural areas with little access to hospitals.  It combines 15 different sensors measuring the most important body parameters that would ordinarily be measured in a hospital, including ECG, glucose, airflow, pulse, oxygen in

It combines 15 different sensors measuring the most important body parameters that would ordinarily be measured in a hospital, including ECG, glucose, airflow, pulse, blood oxygen, and blood pressure. The data is encrypted and sent to the Libelium Cloud in real-time to be visualized on the user’s private account.

It fits in a small suitcase and costs less than 1/100th the amount of a traditional Emergency Observation Unit.

The kit was created to make it possible for m-health developers to create prototypes cheaply and quickly.

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The IoT Can Revolutionize Every Aspect of Small Farming

Posted on 6th August 2015 in agriculture, communication, data, environmental, Essential Truths, Internet of Things, management, marketing, paradigm shift, retail, sensors, strategy

When the New York Times weighs in on an Internet of Things phenomenon, you know it’s about to achieve mainstream consciousness, and that’s now the case with what I like to call “precision agriculture,” enabled by a combination of IoT sensors in the fields and big data analysis tools.

The combination is potent and vital because an adequate supply of safe food is so central to our lives, and meeting that need worldwide depends increasingly on small farms, which face a variety of obstacles that big agribusinesses don’t encounter.

Chris Rezendes, a partner in INEX Advisors, who’s been particularly active with IoT-based ag startups, pointed out to me in a private communication that the problem is world-wide, and particularly matched to the IoT’s capabilities, because food security is such a ubiquitous problem and because (surprisingly to me) the agricultural industry is dominated more by small farms, not agri-biz:

“… most people do not have an understanding of the dimensions of food security beyond calories. Feeding the world demands more than just calories. It demands higher nutritional quotient, safety, affordability and accessibility.

“And all that translates in many models into a need for a more productive, profitable and sustainable small ag industry.

“Most folks do not realize that that there are nearly 700 million farmers on the planet. In the US alone, we have 2.3 million ag operations (and, BTW, the number of millennials entering the field is nearly doubling each year) — and that is not counting processing, packaging, distribution, or anything related to fisheries. Most of those farms are pretty small … less than 500 acres on average, and when you strip out the conglomerates and the hobbyist farmers, you are left with hundreds of thousands of small businesses averaging nearly $4 million per year in revenue.”

As reported by The Times‘ Steve Lohr, Lance Donny, founder of ag technology start-up, OnFarm Systems, said the IoT’s benefits can be even greater outside the US:

“.. the most intriguing use of the technology may well be outside the United States. By 2050, the global population is projected to reach nine billion, up from 7.3 billion today. Large numbers of people entering the middle class, especially in China and India, and adopting middle-class eating habits — like consuming more meat, which requires more grain — only adds to the burden.

“To close the food gap, worldwide farm productivity will have to increase from 1.5 tons of grain per acre to 2.5 tons by 2050, according to Mr. Donny. American farm productivity is already above that level, at 2.75 tons of grain per acre.

“’But you can’t take the U.S. model and transport it to the world,’ Mr. Donny said, noting that American farming is both highly capital-intensive and large scale. The average farm size in the United States is 450 acres. In Africa, the average is about two acres.

“’The rest of the world has to get the productivity gains with data,’ he said.”

The marketplace and entrepreneurs are responding to the challenge. The Times piece also reported that IoT-enabled ag is now big business, with a recent study by AgFunder (equity crowdfunding for ag tech!) reporting start-ups have snared $2.06 billion in 228 deals so far this year (compared to $2.36 billion in all of 2014, which was itself a record).  When you add in the big funding that companies such as Deere have done in IoT over the last few years (in case you didn’t know it, this 178-year old company has revolutionized its operations with the IoT, creating new revenue streams and services in the process) and the cool stuff that’s even being produced here in Boston, and you’ve got a definite revolution in the most ancient of industries.

Rezendes zeros in on the small farmers’ need for data in order to improve every aspect of their operations, not just yields, and their desire to control their data themselves, rather than having it owned by some large, remote conglomerates. Most of all, he says, they desperately needed to improve their profitability, which is difficult with smaller farms:

“Those 2.3 million farmers will deploy IoT in their operations when they know that the data is relevant, actionable, profitable, secure and theirs.

“They are not going to deploy third-party solutions that capture farmers’ operational intelligence, claim ownership of it, and leverage the farmers’ livelihood for the solution vendors’ strategic goals.

“For example, we went into a series of explorations with one ag co-op in the East this spring, after going into the exploration thinking that we might be able to source a number of productivity enhancement solutions for vegetable growers and small protein program managers. We were wrong.

“These farmers in this one part of a New England state had been enjoying years of strong, if uneven growth in their output. That was not their challenge: their challenge was with profitability.”

Think of small farms near you, which must be incredibly nimble to market their products (after toiling in the fields!) relying heavily on a mix of CSAs, local restaurants that feature locally-sourced foods, and on farmers’ markets. Rezendes says the small farmers face a variety of obstacles because of their need (given their higher costs) to attract customers who would pay prevailing or (hopefully) premium prices, while they face perceptual problems because small farmers must be jacks-of-all-trades:

“They have only one ‘route.’ They market, sell, and deliver in the same ‘call,’ so their stops are often longer than your typical wholesale food routes. They also have only one marketing, sales and delivery team – and that is often the same team that is tilling, planting, watering, weeding, harvesting and repairing, so they often show up on accounts wearing clothes, driving vehicles, and carrying their inventory in containers that aren’t in any manual for slick brand development manual!

“To complicate things, many of their potential customers could not accept the shipment for insurance purposes, because the farmers didn’t have labels that change with exposure to extreme temperature, sunlight or moisture, or digital temperature recorders.”

Who would think that the IoT might provide a work-around for the perceptual barriers and underscore local farms’ great advantage, the quality of the product?  The farmers suggested to the INEX team once they understood the basics of IoT technology that:

“if we could source a low-cost traceability solution that they could attach to their reusable transport items, they thought they could use that data for branding within the co-op and the regional market. This would reduce the time needed to market and sell, document and file.  The farmers also told us that if the solution was done right, it might serve their regulatory, permitting and licensing requirements, even across state lines.”

Bottom line: not only can sensors in the field improve yields and cut costs for fertilizing and water use through precision, but other sensors can also work after the food is harvested, providing intelligence that lets producers prove their safety, enhance their sales productivity, and drive profit that enables re-investment.

What a great example of the IoT at work, and how, when you start to think in terms of the IoT’s “Essential Truths,” it can revolutionize every aspect of your company, whether a 50-acre farm or a global manufacturer!  

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Energy to Power the #IoT: it’s really just a matter of child’s play

Posted on 12th June 2015 in energy, environmental, Internet of Things, M2M, mobile, sensors, wearables

Saving the Earth from global warming is going to require reducing our use of fossil fuels, yet we keep coming up with new technologies, such as the Internet of Things, that will require even more energy. So how do we reconcile the two needs?

In part, through harvesting ambient energy, and, most cleverly, kinetic energy generated in the process of doing something else, from moving liquids through pipelines, wheels as vehicles move, or even as we humans move about in our daily lives.

As you’ll see from the examples below, there’s enough projects in the field that I’m confident a growing number of sensor networks will be powered through ambient energy in the future. Equally important, in the not-too-distant future we’ll laugh that we once plugged in our smartphone and watches to charge them, rather than harvesting the energy we generate every day simply by moving around.

I saw an incredible example at the recent Re-Work IoT Summit in Boston, courtesy of Jessica O. Matthews of Uncharted Play. By my calculations, Matthews’ own energy output would allow shutting down 2.3 nukes: before her session began, I saw this striking woman on the stage — Matthews –skipping rope.

In high heels!

Then the fun began. Or should I say, the energy production.

Matthews, an MIT grad, works largely in Africa, creating very clever playthings that — ta da! — harvest energy, such as the very cool Soccket ball shown in the video above (you can see here how it’s made).  It has a battery built in that’s charged by the large amount of kinetic energy created by kids on the playground who are just having fun.  At night, they take the ball home and, voila, plug a socket into the side of the ball and they have precious light to read by. How incredibly cool is that?

The Pulse jump rope powers two lights

Matthews’ jump rope (“The Pulse”)? The kinetic energy from that  powers TWO lights!

But there’s a lot of other neat stuff going on in terms of capturing kinetic energy that could also power IoT devices:

  • Texas Instruments has harvested energy to run sensors from changes in temperature, vibrations, wind and light.  I knew about harvesting the energy from pipeline vibrations, but hadn’t thought about getting it from the temperature differential between the interior of pipes carrying hot water and the outside air. TI says that yields a paltry 300-400 millivolts, but they’ve figured out how a DC-to-DC switching converter can increase it to 3-5 volts — enough to charge a battery.
  • TI is also researching how kinetic energy could charge your phone:”To power wearables, the company has demonstrated drawing energy from the human body by using harvesters the size of wristwatch straps.. It has worked with vibration collectors, for instance, about the same size as a key.”It’s possible that a smartwatch could use two harvested power sources, light and heat, from the body. These sources may not gather enough power to keep a smartwatch continuously operating without action by the user to charge it, but it may give the user’s device a lot more battery life.”
  • Perhaps most dramatically of all, as I reported before, there’s some incredible research on ambient energy underway at the University of Washington, where they use “ambient backscatter,” which: ‘…leverag[es] existing TV and cellular transmissions, rather than generating their own radio waves. This novel technique enables ubiquitous communication where devices can communicate among themselves at unprecedented scales and in locations that were previously inaccessible.’”

    PoWiFi, harvesting ambient energy

    Now, a member of that team,Vamsi Talla, has harvested energy from ambient wi-fi,  “PoWiFi,” as it’s called, to power a temperature sensor and to let a surveillance camera take a picture every 35 minutes (given how pervasive surveillance cameras are today, that could really be a godsend — or a nightmare, depending on your perspective). “For the experiment, hot-spots and routers were modified to broadcast noise when not being used for data transmission. This is because Wi-Fi signals are broadcast in bursts across different frequencies which makes the energy too intermittent to be useful.”  (TY 2 Jackie Bassett of  SealedSpeed for this one).

Bottom line: forget those charging pads that are starting to crop up. In the future, you’ll be powering your phone, and the very devices that sensors are monitoring will be powering them. A win for the IoT — and the environment!

PS: jury’s still out on whether we’ll all have to register with FERC as utilities….

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Intel’s IoT tech improves its own manufacturing efficiency

Posted on 10th June 2015 in data, Essential Truths, Internet of Things, M2M, management, manufacturing, sensors

This demonstration IoT manufacturing project hits my buttons!

I love IoT-enabled manufacturing (what I call “precision manufacturing“) and I REALLY love companies (such as GE, at its Durathon battery plant) that eat their own dogfood by applying their IoT technology internally.  Gotta walk the talk!

 

That’s why I was happy to learn how Intel is  applied its own IoT technology to its own factories. In the accompanying video, Intel VP for IoT operations and group marketing Frank James says:

“The real opportunity is how to combine … data differently, which will ultimately give you insights not only into how your factory is running but, what’s more important, will let you predict how your factory will run the next minute, the next hour, the next shift, the next day.”

The pilot factory automation project is a collaboration with Mitsubishi Electric (more points for a key IoT “Essential Truth” — collaboration!).  The project, at Intel’s Malaysia manufacturing facility, combines two critical components, end-to-end IoT connectivity and big data analytics. The benefits were impressive: $9 million in cost avoidance and improved decision making, plus:

  • improved equipment uptime
  • increased yield and productivity
  • predictive maintenance
  • reduced component failures.

That hard-to-quantify improved decision making, BTW, is one of the things that doesn’t get enough discussion when we talk about IoT benefits: decision-making improves when there is more data to consider, more people to analyze and discuss it simultaneously (not sequentially, as in the past), and when you’ve got tools such as data dashboards to allow visualizing the data and its patterns.

The companies plan to roll out the services commercially this year.

Here are the specs:

“Using an Intel® Atom™ processor-based IoT gateway called the C Controller from Mitsubishi Electric’s iQ-Platform, Intel was able to securely gather and aggregate data for the analytics server. Data was then processed using Revolution R Enterprise* software from Revolution Analytics*, an analytics software solution that uses the open source R statistics language, which was hosted on Cloudera Enterprise*, the foundation of an enterprise data hub.”

 

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Sensors remain critical to spread of Internet of Things

Posted on 22nd May 2015 in automotive, energy, health, Internet of Things, M2M, maintenance, management, manufacturing, retail, security, sensors, transportation, wearables

What happens with sensor design, cost, and security remains front-and-center with the Internet of Things, no matter how much we focus on advanced analytical tools and the growing power of mobile devices.

That’s because, on one hand, truly realizing the IoT’s full potential will require that at least some sensors get to the low-power, tiny size and cheap costs needed to realize Kris Pister’s dream of “smart dust” sensors that can be strewn widely.

On the other hand, there’s the chance that low-end sensors that don’t include adequate security firmware can’t keep up with the changing nature of security risks and may give hackers access to the entire network, with potentially disastrous effects.

That’s why several reports on sensors caught my eye.

PWC released a report, Sensing the Future of the Internet of Things, zeroing in on sensor sales as a proxy for increased corporate investment in the IoT, and concluding that by that measure, “the IoT movement is underway.” Based on its 2014 survey of 1,500 business and technology leaders worldwide, there was one eye-popping finding: the US lags behind the entire rest of the world in planned spending on sensors this year: 26% of Asian and almost as many from South America (percentage not given)  followed closely by Africa, with 18%.  The surprising laggards? Europe with 8% and North America, dead last at only 7%.  Hello?????

Equally interesting was the company’s listing of the industry segments leading the deployment of sensors and examples of the sensors they’re using:

  • Energy & Mining: 33%. “Sensors continuously monitor and detect dangerous carbon monoxide levels in mines to improve workplace safety.”
  • Power and Utilities: 32%.  Instead of the old one-way metering, “Internet-connected smart meters measure power usage every 15 minutes and provide feedback to the power consumer, sometimes automatically adjusting the system’s parameters.”
  • Automotive: 31%.  “Sensors and beacons embedded in the road working together with car-based sensors are used for hands-free driving, traffic pattern optimization and accident avoidance.”
  • Industrial: 25%. “A manufacturing plant distributes plant monitoring and optimization tasks across several remote, interconnected control points. Specialists once needed to maintain, service and optimize distributed plant operations are no longer required to be physically present at the plant location, providing economies of scale.”
  • Hospitality: 22%. “Electronic doorbells silently scan hotel rooms with infrared sensors to detect body heat, so the staff can clean when guests have left the room.”
  • Health Care: 20%. “EKG sensors work together with patients’ smartphones to monitor and transmit patient physical environment and vital signs to a central cloud-based system.”
  • Retail: 20%. “Product and shelf sensors collect data throughout the entire supply chain—from dock to shelf. Predictive analytics applications process this data and optimize the supply chain.”
  • Entertainment: 18%. “In the gaming world, companies use tracking sensors to transfer the movements of users onto the screen and into the action.”
  • Technology: 17%. “Hardware manufacturers continue to innovate by embedding sensors to measure performance and predict maintenance needs before they happen.”
  • Financial Services: 13%. “Telematics allows devices installed in the car to transmit data to drivers and insurers. Applications like stolen vehicle recovery, automatic crash notification, and vehicle data recording can minimize both direct and indirect costs while providing effective risk management.”

The surprises there were that health care penetration was so low, especially because m-health can be so helpful in diagnosis and treatment, while the examples of telematics seemed off the mark in the financial services category. Why not examples such as ApplePay?

More compelling were the relatively high rates of sensor deployment in high-stakes fields such as energy, utilities, and automotive: those are such huge industries, and the benefits of real-time data are so compelling that they show the IoT is really maturing.

Finally, the percentage of companies investing in sensors grew slightly, from 17% to 20%, with 25%of what PWC labels “Top Performers” are investing in them compared to 18% the previous year. Surprisingly, most companies don’t get it about sensors’ importance: only “14% of respondents said sensors would be of the highest strategic importance to their organizations in the next 3–5 years, as compared to other emerging technologies.”

Most important, 54% of those “Top Performers” said they’d invest in sensors this year.

 

Sensors’ promise as the size decreases — radically — and functionality increases was highlighted by The Guardian.  It focused on PragmaticIC Printing, a British firm that prints tiny, hairlike sensors on plastics. CEO Scott White’s hope is that:

” the ultra-thin microcircuits will soon feature on wine bottles to tell when a Chablis is at the perfect temperature and on medication blister packs to alert a doctor if an elderly patient has not taken their pills.

“With something which is slimmer than a human hair and very flexible, you can embed that in objects in a way that is not apparent to the user until it is called upon to do something. But also the cost is dramatically lower than with conventional silicon so it allows it to be put in products and packaging that would never justify the cost of a piece of normal electronics,” said White.

 

These uses certainly meet my test of real innovation: what can you do that you couldn’t do before. Or, as White puts it, “It is the combination of those factors [price and size] which allows us to start thinking about doing things with this which wouldn’t even be conceivable with conventional silicon based electronics.”

Another article that really caught my eye regarded a new category of “hearable” — and perhaps even, more radically, “disappearables” –sensors which the headline boldly predicted “As Sensors Shrink, Wearables Will Dis-appear.” But they were barely here in the first place, LOL!  The article mentioned significant breakthroughs in reducing sensors’ size and energy requirements, as well as harvesting ambient energy produced by sources such as bodily movement:

“Andrew Sheehy of Generator Research calculates that, for example, the heat in a human eyeball could power a 5 milliwatt transmitter – more than enough, he says, to power a connection from a smart contact lens to a smartphone or other controlling device.”

 The same article mentioned some cutting-edge research such as a Google/Novartis collaboration to measure glucose levels in tears via a contact lense, and an edible embedded microchip — the size of a grain of sand — and powered by stomach juices, which would transmit data by Bluetooth.
Elsewhere, a sampling of sensor design breakthroughs in recent months show the potential for radical reductions in costs and energy needs as well as increased sensitivity and data yield:

HOWEVER, as I said above, here’s what worries me. Are developers paying enough attention to security and privacy? That could be a real downfall for the IoT, since many sensors tend to be in place for years, and the nature of security challenges can change dramatically during that time.  Reducing price can’t be at the expense of security.

Let me know what steps you’re taking to boost sensor security, and I’ll mention them in a future post!

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Virtual Sensor Networks: a key #IoT tool?

Posted on 7th May 2015 in collaboration, data, Essential Truths, Internet of Things, M2M, management, privacy, security, smart cities

I was once again honored to be a guest on Coffee Break With Game Changers Radio today with David Jonker and Ira Berk of SAP — it’s always a delight to have a dialogue on the Internet of Things with these two brainy guys (and hats off as well to moderator/host Bonnie Graham!).

Toward the end of the show, Ira brought up a concept that was new to me: virtual sensor networks.

I’ve got sensors on the brain right now, because I’m frankly worried that sensors that don’t have adequate baked-in security and privacy protections and which can’t be ungraded as new opportunities and threats present themselves may be a threat to the IoT because they typically remain in use for so many years. Ah, but that’s a topic for another post.

According to Wikipedia, Virtual sensor networks are an:

“… emerging form of collaborative wireless sensor networks. In contrast to early wireless sensor networks that were dedicated to a specific application (e.g., target tracking), VSNs enable multi-purpose, collaborative, and resource efficient WSNs. The key idea difference of VSNs is the collaboration and resource sharing….
“… A VSN can be formed by providing logical connectivity among collaborative sensors. Nodes can be grouped into different VSNs based on the phenomenon they track (e.g., rock slides vs. animal crossing) or the task they perform. VSNs are expected to provide the protocol support for formation, usage, adaptation, and maintenance of subset of sensors collaborating on a specific task(s). Even the nodes that do not sense the particular event/phenomenon could be part of a VSN as far as they are willing to allow sensing nodes to communicate through them. Thus, VSNs make use of intermediate nodes, networks, or other VSNs to efficiently deliver messages across members of a VSN.”

Makes sense to me: collaboration is a critical basic component of the human aspect of the IoT (one of my IoT “Essential Truths), so why shouldn’t that extend to the mechanics as well?). If you have a variety of sensors already deployed in a given area, why should you have to deploy a whole new set of single-purpose ones to monitor a different condition if data could be synthesized from the existing sensors to effectively yield the same needed information?

A 2008 article on the concept said the virtual sensor networks are particularly relevant to three categories where data is* needed:

“Firstly, VSNs are useful in geographically overlapped applications, e.g., monitoring rockslides and animal crossing within a mountainous terrain. Different types of devices that detect these phenomena can relay each other for data transfer without having to deploy separate networks (Fig. 1). Secondly, VSNs are useful in logically separating multipurpose sensor networks, e.g., smart neighborhood systems with multifunctional sensor nodes. Thirdly, VSNs can be used to enhance efficiency of systems that track dynamic phenomena such as subsurface chemical plumes that migrate, split, or merge. Such networks may involve dynamically varying subsets of sensors.”

That article went on to propose a flexible, self-organizing “cluster-tree” approach to create the VSN, using tracking of a pollution plume as an example:

“…  a subset of nodes organizes themselves to form a VSN to track a specific plume. Whenever a node detects a relevant event for the first time it sends a message towards the root of the cluster tree indicating that it is aware of the phenomenon and wants to collaborate with similar nodes. The node may join an existing VSN or makes it possible for other nodes that wish to form a VSN, to find it. Use of a cluster tree or a similar structure guarantees that two or more nodes observing the same phenomenon will discover each other. Simulation based results show that our approach is more efficient and reliable than Rumor Routing and is able to combine all the nodes that collaborate on a specific task into a VSN.”

I suspect the virtual sensor network concept will become particularly widespread as part of “smart city” deployments: cash-strapped municipalities will want to get as much bang for the buck possible from already-deployed sensors, without having to install new ones. Bet my friends in Spain at Libellium will be in the forefront of this movement!

Thanks, Ira!

*BTW: if any members of the Grammar Police are lurking out there (I’m a retired lt. colonel of the Mass. State Grammar Police myself), you may take umbrage at “data is.”  Strictly speaking, the proper usage in the past has been “data are,” but the alternative is becoming so widespread that it’s becoming acceptable usage. So sue me…

 

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IBM picks for IoT trends to watch this year emphasize privacy & security

Posted on 23rd February 2015 in collaboration, data, Internet of Things, M2M, management, privacy, security, strategy, Uncategorized

Last month Bill Chamberlin, the principal analyst for Emerging Tech Trends and Horizon Watch Community Leader for IBM Market Development (hmmm, must have an oversized biz card..) published a list of 20 IoT trends to watch this year that I think provide a pretty good checklist for evaluating what promises to be an important period in which the IoT becomes more mainstream.

It’s interesting to me, especially in light of my recent focus on the topics (and I’ll blog on the recent FTC report on the issue in several days), that he put privacy and security number one on the list, commenting that “Trust and authentication become critical across all elements of the IoT, including devices, the networks, the cloud and software apps.” Amen.

Most of the rest of the list was no surprise, with standards, hardware, software, and edge analytics rounding out the top five (even though it hasn’t gotten a lot of attention, I agree edge analytics are going to be crucial as the volume of sensor data increases dramatically: why pass along the vast majority of data, that is probably redundant, to the cloud, vs. just what’s a deviation from the norm and probably more important?).

Two dealing with sensors did strike my eye:

“9.  Sensor fusion: Combining data from different sources can improve accuracy. Data from two sensors is better than data from one. Data from lots of sensors is even better.

10.  Sensor hubs: Developers will increasingly experiment with sensor hubs for IoT devices, which will be used to offload tasks from the application processor, cutting down on power consumption and improving battery life in the devices”

Both make a lot of sense.

One was particularly noteworthy in light of my last post, about the Gartner survey showing most companies were ill-prepared to plan and launch IoT strategies: “14.  Chief IoT Officer: Expect more senior level execs to be put in place to build the enterprise-wide IoT strategy.” Couldn’t agree more that this is vital!

Check out the whole list: I think you’ll find it helpful in tracking this year’s major IoT developments.

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Another Personal IoT Story: my next car will have auto braking

Posted on 16th January 2015 in automotive, Essential Truths, transportation

Sorry to burden you with another personal Internet of Things story, especially since this one’s nowhere near as nice as how car_crashsmart sockets made peace in my house!

For the second time in less than a month, I was hit by a deer at night on Rt. 27 in Medfield, MA. If you know our area, its in the outer suburbs, and plagued by deer, who are mating at this time of year, and are absolutely nuts. Two hours later, I’m still shaking, and extremely lucky to have escaped a serious injury.

I don’t know if  it would have avoided a collision, because they were running sooo fast, but you can be sure that my next car with be a smart one, with sensors and an automatic braking system like the ones on TMercedes, BMWs and high-end Hyundai‘s.  Here’s something where the smart version wouldn’t just simplify something, but would observe one of my “Essential Truths” of the IoT, “what can you do now that you couldn’t do before.”

No driver who was focused on the road ahead could have possibly seen these deer rushing out of the pitch-black woods on the other side of the road (or, if he did, he would have crashed into something else because of taking his eyes off the road), but a motion-sensor coupled to the brakes would have detected motion in time to apply the brakes and maybe avoid the crash.

Tonight was one of the most traumatic events of my life, between the accident and the first time I’ve ever heard a gunshot up close, as the police put the doe out of her misery. If I can invest in IoT technology to avoid it happening again, I’ll be at the head of the line!

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