Free Citywide IoT Data Networks Will Catapult IoT Spread to Hyperspeed!

One of the truly exciting things about viral digital phenomena is how rapidly they can take hold, outstripping the slow, methodical spread of innovations in the pre-digital era.  I suspect we may be on the verge of that happening again, with an unlikely impetus: the crowdsourced global movement to create free citywide IoT data networks.

We’re been there before, with the movement to open real-time public access to city data bases, beginning when CTO (and later US CIO) Vivek Kundra did it in DC in 2008, then sponsored the Apps for Democracy competition to spark creation of open-source apps using the data (bear in mind this was at a time when you had to explain to many people what an “app” was, since they, and smart phones, were so new).  From the beginning, Kundra insisted that the apps be open source, so that hackers in other cities could copy and improve on them, as they have — worldwide.

I was doing consulting for him at the time, and remember how incredibly electric the early days of the open data movement were — it inspired my book Data Dynamite, and led to similar efforts in cities worldwide, which in turn set the stage for the “smart city” movement as the IoT emerged.

As detailed in my last post, we’re now launching a crowdsourced campaign to make Boston the first US city, and second worldwide (following Amsterdam) to have a free citywide IoT data network — and plan to up the ante by setting of goal to cover the neighborhoods too — not just the downtown.

The Things Network guys plan to build on their accomplishments, announcing this week that they will advise similar crowdfunded networks on five continents (including our Boston project). They place a major emphasis on grassroots development, to avoid subscription-based infrastructures that could be controlled from above and which would limit l0w-cost innovations, especially on the neighborhood scale.  According to founder Wienke Giezeman:

““If we leave this task up to big telcos, a subscription model will be enforced and we will exclude 99% of the cool use cases. Instead, let’s make it a publicly owned and free network so businesses and use cases will flourish on top of it.”

I’ve been a fan of mesh networks back to my days doing disaster and terrorism because they’re self-organizing and aren’t vulnerable because there isn’t a single point of failure. But it’s as much philosophical as technological, because you don’t have to wait for some massive central authority to install the entire system: it evolves through the decisions of individuals (we’re already finding that in Boston: it turns out that our system will be able to tap a number of LoRaWAN gateways that several companies had already installed for their own uses!) The Amsterdam guys share that perspective. Tech lead Johan Stokking says:

“We make sure the network is always controlled by its users and it cannot break at a single point. This is embedded in our network architecture and in our governance.”

Takes me back to my callow youth in the 6o’s: let a thousand apps bloom! (and, BTW, the great Kevin Kelly made this point in his wonderful Out of Control, back in the mid 90’s, especially with his New Rules for the New Economy (I’m going to take the liberty of posting all the rules here, because they are so important, especially now that we have technology such as LoRaWAN that foster them!):

1) Embrace the Swarm. As power flows away from the center, the competitive advantage belongs to those who learn how to embrace decentralized points of control.

2) Increasing Returns. As the number of connections between people and things add up, the consequences of those connections multiply out even faster, so that initial successes aren’t self-limiting, but self-feeding.

3) Plentitude, Not Scarcity. As manufacturing techniques perfect the art of making copies plentiful, value is carried by abundance, rather than scarcity, inverting traditional business propositions.

4) Follow the Free. As resource scarcity gives way to abundance, generosity begets wealth. Following the free rehearses the inevitable fall of prices, and takes advantage of the only true scarcity: human attention.

5) Feed the Web First. As networks entangle all commerce, a firm’s primary focus shifts from maximizing the firm’s value to maximizing the network’s value. Unless the net survives, the firm perishes.

6) Let Go at the Top. As innovation accelerates, abandoning the highly successful in order to escape from its eventual obsolescence becomes the most difficult and yet most essential task.

7) From Places to Spaces. As physical proximity (place) is replaced by multiple interactions with anything, anytime, anywhere (space), the opportunities for intermediaries, middlemen, and mid-size niches expand greatly.

8) No Harmony, All Flux. As turbulence and instability become the norm in business, the most effective survival stance is a constant but highly selective disruption that we call innovation.

9) Relationship Tech. As the soft trumps the hard, the most powerful technologies are those that enhance, amplify, extend, augment, distill, recall, expand, and develop soft relationships of all types.

10) Opportunities Before Efficiencies. As fortunes are made by training machines to be ever more efficient, there is yet far greater wealth to be had by unleashing the inefficient discovery and creation of new opportunities.”

If you really want to exploit the IoT’s full potential, you gotta read the whole book.

Equally important, the Obama Administration announced it will boost smart city app development with a new $160 million smart cities initiative:

“Among the initiative’s goals are helping local communities tackle key challenge such as reducing traffic congestion, fighting crime, fostering economic growth, managing the effects of a changing climate, and improving the delivery of city services. As part of the initiative, the National Science Foundation will make more than $35 million in new grants and the National Institute of Standards and Technology will invest more than $10 million to help build a research infrastructure to develop applications and technology that ‘smart cities’ can use.”

The LoRaWan gateways used in the Amsterdam project are already low cost: only 10 of the $1,200 units covered the downtown area. However, The Things Network hopes to crowdsource an even cheaper, $200 version through a Kickstarter campaign.  If that happens, even small cities will be able to have their own free citywide IoT data networks, and when that happens, I’m confident the IoT will shift into hyperdrive worldwide!

Are you on board?


 

Oh yeah, did you say what about the risks of privacy and security violations with such a large and open system? The Amsterdam lads have thought of that as well, reaching out to Deloitte from the get-go to design in security:

“To make this initiative grow exponentially, we have to take cyber security and privacy into account from the start of the development. Therefore, we have partnered with Deloitte, who is not only contributing to the network with a Gateway, but will also be the advisor on the security and privacy of the network.

“’We translate technology developments in the field of Digital, Data and Cyber Security into opportunities and solutions for our clients. We are therefore happy to support the Things Network as Security & Privacy advisor’ Marko van Zwam, Head of Deloitte Cyber Risk Services.”

Deloitte provides process for nuanced IoT strategy decisions

So much of the Internet of Things is still in the gee-whiz stage that we haven’t seen much in terms of nuanced IoT strategies. By that I mean ones that carefully weigh tradeoffs between companies and consumers to try to find strategies that are mutually beneficial and recognize there are new factors at play in IoT strategies, such as privacy and data mining, that may have positive or negative consequences for the customer/company interplay.

Deloitte’s “University” has made an important step in that direction with its “Power Struggle: Customers, companies and the Internet of Things” paper, co-authored by Brenna Sniderman and Michael E. Raynor.

In it, they explore how to create sustainable strategies that will be mutually beneficial to the customer and company — which are not always immediately apparent, especially when you explore the subtleties of how these strategies might play out in the new reality of the Internet of Things.

The study’s goal was to understand the factors that can distort IoT’s benefits, and instead create win-win IoT strategies.

Sniderman and Raynor suggest there are four quadrants into which a given strategy might fall:

  1. (the sweet spot!) “All’s well: Sufficient value is created, and that value is shared between customers and companies sufficiently equitably such that both parties are better off and feel fairly treated.
  2. “Hobson’s choice: A Hobson’s choice exists when you’re free to decide but only one option exists; thus, it is really no choice at all…. Even when customers come out ahead compared with their former options, their implied powerlessness can lead to feelings of unfairness.
  3. “Gridlock: In their quest for value capture, both sides are pulled in opposite directions, with neither able to move toward an optimal outcome. Here, both parties recognize IoT enablement as something that should lead to success, but neither party is able to reach it, since their competing interests or different value drivers are working at cross purposes.
  4. “Customer is king: Although particular IoT deployments might make economic sense for companies, customers end up capturing a disproportionate share of the new value created, pulling this outcome more in the customers’ favor; Craigslist is an obvious example.”

According to the authors, a key to finding the win-win, “all’s well” solution is the Information Value Loop (which I first discussed last Spring) that creates value out of the vast increase in information made possible by the IoT.

As I mentioned then, “This fits nicely with one of my IoT ‘Essential Truths,’ that we need to turn linear information flows into cyclical ones to fully capitalize on the IoT.” When you do that, it’s possible to design continuous improvement processes that feed back data from actual users to fine tune products and processes.  GE has found it leads to much shorter iterative loops to design improved versions of its products.

Here’s the gussied-up version of the cool hand-drawn visualization from the Deloitte brainstorming session that led to the Information Value Loop (print it & place it on your wall next to the one on privacy and security that I wrote about a while ago):

Deloitte Information Value Loop

The information no longer flows in linear fashion: it’s created from using sensors to record how things act in the real world, then goes through the various stages of the loop, each of which is made possible by one of the new technologies enabling the IoT.  The goal is either enhanced M2M integration among things, or improved actions by humans, and, to be sustainable over time:

“A value loop is sustainable when both parties capture sufficient value, in ways that respect important non-financial sensibilities. For example, retailer-specific and independent shopping apps can use past browsing and purchasing history—along with other behaviors—to suggest targeted products to particular customers, rather than showing everyone the same generic products, as on a store shelf. Customers get what they want, and companies sell more.

…  “The amount of value created by information passing through the loop is a function of the value drivers identified in the middle. Falling into three generic categories—magnitude, risk, and time—the specific drivers listed are not exhaustive but only illustrative. Different applications will benefit from an emphasis on different drivers.”

OK, so how does this theory play out?

Sniderman and Raynor picked a range of IoT-informed strategies to illustrate the concept, some of which may include unintended consequences that would harm/turn off customers or companies. For example, “An ill-considered push for competitive advantage could well overreach and drive away skittish customers. Alternatively, building too dominant an advantage may leave customers feeling exploited or coerced, a position unlikely to prove viable in the long term.”

Understanding the underlying structure of each type of loop is critical, because they naturally pull an IoT strategy in a particular, divergent way.

The example they pick to illustrate the “all’s well” quadrant of results is the dramatic increase in built-in diagnostic technology in cars.  This is of great personal interest: genetic testing has revealed that I am one of the approximately 10% of men who are missing the male car gene: I can’t stand the things, and view them as a big block of metal and plastic just waiting to develop problems (or, ahem, get hit by deer …), so I need all the help I can get. Sniderman and Raynor zero in on maintenance as one area for win-win benefits for drivers and dealers through the IoT:

“Customers often have little understanding of which repairs are necessary, feel inconvenienced by having to go without their car during maintenance periods, and are frustrated by potential overcharges. In response, automakers are embedding sensors that can run a wide range of reliable diagnostics, allowing a car to “self-identify” service issues, rather than relying on customers (“Where’s that squeaking coming from?”) or mechanics (“You might want to replace those brake pads, since I’ve already got the wheels off”). This creates a level of objectivity of obvious customer value and enables automakers to differentiate their products. Interactive features that work with customers’ information can further add value by, for example, potentially syncing with an owner’s calendar to schedule a dealership appointment at a convenient time and reserving a loaner vehicle for the customer, pre-programmed with his preferences to minimize the frustration of driving an unfamiliar car.

In this scenario, both parties collaborate to provide and act on data, in a mutual exchange of value. The customer captures value in multiple ways: He enjoys increased convenience and decreased frustration, improved vehicle performance and longer operating life, reduced maintenance charges, and—since almost everything about this interaction is automated—fewer occasions for perceived exploitation at the hands of unscrupulous service providers.

Value capture extends to companies in the form of ongoing customer interaction. Linking maintenance programming to the dealership encourages customers to return for tune-ups rather than go elsewhere, ideally leading to continued purchases in the long term. OEMs can also access data regarding vehicle maintenance issues and may be able to identify systematic malfunctions worthy of greater attention. Dealers also have an opportunity to make inroads into an untapped market: Currently, just 30 percent of drivers use the dealer for routine maintenance…”

Kumbaya! But then there’s the opposite extreme, according to Sniderman and Raynor, represented by smart home devices, which would lead to the lose-lose, gridlock scenario.  I think they seriously underestimate the understanding already by manufacturers in the field that they need to embrace open standards in order to avoid a range of competing standards (Zigbee, Bluetooth, etc.) that will force consumers to invest in a variety of proprietary, incompatible hubs, and therefore discourage them from buying anything at all.  All you have to do is look at new hubs, such as Amazon’s Echo, which can control devices from WeMo, Hue, Quirky, Wink — you name ’em, to realize that sharing data is already the norm with smart home devices.

Because this missive is getting long, I’ll leave it to you, dear reader, to investigate Sniderman & Raynor’s examples of the “customer is king” scenario, in which the customer grabs too much of the benefit (have to admit, a lot of the location-based IoT retail incentives still give me the creeps: I hate shopping under the best of circumstances, and having something pop up on my phone offering me an incentive based on my past purchases makes a bad experience even worse. How about you?); and the “Hobson’s choice” one, in which usage-based car insurance runs amok and insurers begin to charge unsafe drivers a surcharge — as documented by the devices such as Progressive’s “Snapshot” (I was dismayed to read in the article that Progressive is in fact doing that in Missouri, although I guess it’s a logical consequence of having objective evidence that someone consistently drives unsafely).

I can’t help thinking that the 800-pound gorilla in the room in many of these situations are the Scylla and Charybdis of the IoT, threats to privacy and security, and that makes it even more important that your IoT strategies are well thought out.

They conclude that, from my perspective, data isn’t just enough, you also need the decidedly non-technical tools of judgment and wisdom (aided by tools such as their Information Value Loop) to come up with a sustainable, mutually advantageous IoT strategy:

“Identifying where the bottlenecks lie (using the Information Value Loop), how each party is motivated to respond, and seeking to shape both incentives and the value loop itself puts companies more in control of their destinies.

“Second, taking a hard look at who benefits most from each IoT-enabled transaction, understanding when a lopsided value-capture outcome tips too far and becomes unsustainable, and taking steps to correct it may also lead to long-term success.

“Lastly, an honest assessment of where IoT investments may not have an appreciable benefit—or may decrease one’s potential for value capture—is just as crucial to a company’s IoT strategy as knowing the right places to invest.”

I may quibble with some of their findings, such as those about smart homes, but bravo to Sniderman and Raynor for beginning what I hope is a spirited and sustained dialogue about how to create sustainable, mutually-advantageous IoT strategies!  I’ve weighed in with my Essential Truths, but what are you thinking about this critical issue, often overlooked in our concentration on IoT technologies? 

The IoT Will Reinvent Replacement Parts Industry

Of all the Internet of Things’ revolutionary impacts on industry, perhaps none will be as dramatic as on replacement parts, where it will team with 3-D printing to reduce service time, inventory and costs.

I came to that realization circuitously, upon noticing Warren Buffett’s blockbuster purchase of Precision Castparts, the major precision parts supplier to the aeronautics industry.  Having read last year about yet another breakthrough innovation by Elon Musk, i.e., the first totally 3-D printed rocket engines, I was curious to see what Precision was doing in that area.  Unless my search of their website was flawed, the answer is zip, and that suggests to me that Buffett, who famously once said he doesn’t invest in technology because he doesn’t understand it, may have just bought …. a rather large dinosaur.

I noticed that one of Precision’s biggest customers is GE, which not only is using 3-D jet fuel nozzles on its engines but also ran a high-profile contest to design a 3-D printed engine mount that was open to you, me and the kids trying out the new 3-D printer at our little town’s library (note to Mr. Buffett: might be good to schedule a sit-down with Jeff Immelt before one of your biggest customers takes things in-house). As I’ve written before, not only is GE a world leader in the IoT and 3-D printing, but also in my third magic bullet, nanotech: put all three together, and you’re really talking revolution!

OK, I know 3-D printing is sloow (in its current state), so it’s unlikely to replace traditional assembly lines at places such as Precision Castparts for large volumes of parts, but that doesn’t mean it won’t rapidly replace them in the replacement parts area.  I talked to a friend several years ago whose biz consists of being a broker between power plants that need replacement parts yesterday and others with an excess on hand, and couldn’t help thinking his days were numbered, because it was predicated on obsolete technology — and thinking.

Think of how the combined strengths of the IoT and 3-D printing can help a wide range of industries get replacement parts when and where they need them, and at potentially lower cost:

  • sensors in IoT-enabled devices will give advance notice of issues such as metal fatigue, so that repairs can be done sooner (“predictive maintenance“), with less disruption to normal routine, cheaper and reducing the chance of catastrophic failure.
  • because data can be shared on a real-time by not only your entire workforce, but also your supply chain, you can automate ordering of replacement parts.
  • perhaps most important, instead of a supplier having to maintain a huge inventory of replacement parts on the possibility they may be needed, they can instead be produced only when needed, or at least with a limited inventory (such as replacing a part in inventory as one is ordered). This may lead to “re-shoring” of jobs, because you will no longer have to deal with a supplier on the other side of the globe: it might be in the next town, and the part could be delivered as soon as printed, saving both delay and money.
  • your company may have your own printer, and you will simply pay the OEM for the digital file to print a part in-house, rather than having to deal with shipping, etc.

And, as I mentioned in the  earlier post about GE’s leadership in this area, there are other benefits as well:

  • “We’ll no longer do subtractive processes, where a rough item is progressively refined until it is usable.  Instead, products will be built atom-by-atom, in additive processes where they will emerge exactly in the form they’re sold.
  • “Products will increasingly be customized to the customer’s exact specifications. The products will be further fine-tuned based on a constant flow of data from the field about how customers actually use them.”

Sooo, Mr. Buffett, it’s time that you come to terms with 21-st century technology or Berkshire Hathaway’s financial slide may continue.

 

The IoT Can Revolutionize Every Aspect of Small Farming

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!  

The IoT Can Improve Safety and Profitability of Inherently Dangerous Job Sites

You may remember I wrote several months ago about a collaboration between SAP and SK Solutions in Dubai (interesting factoid: Dubai is home to almost 25% of the world’s cranes [assume most of the rest nest at Sand Hill, LOL], and they are increasingly huge, and that makes them difficult to choreograph.

I’m returning to the subject today, with a slightly broader emphasis on how the IoT might manage a range of dangerous job sites, such as mining and off-shore oil rigs, allowing us to do now that we couldn’t do before, one of my IoT Essential Truths.

I’m driven in part by home-town preoccupation with Boston’s bid for the 2024 Olympics, and the inevitable questions that raises on the part of those still smarting from our totally-botched handling of the last big construction project in these parts, the infamous “Big Dig” tunnel and highway project.

I’m one of those incurable optimists who think that part of ensuring that the Olympics would have a positive “legacy” (another big pre-occupation in these parts) would be to transform the city and state into the leading example of large-scale Internet of Things implementation.

There are a couple of lessons from SAP and SK Solutions’ collaboration in Dubai that would be relevant here:

    • The system is real-time: the only way the Boston Olympic sites could be finished in time would be through maximizing efficiency every day. Think how hard that is with a major construction project: as with “for want of a nail the kingdom was lost,” the sensitive interdependence between every truck and subcontractor on the site — many of which might be too small to invest in automation themselves — is critical. If information about one sub being late isn’t shared, in real-time, with all the other players, the delays — and potential collisions — will only pile up. The system includes an auto-pilot that makes immediate adjustments to eliminate operator errors. By contrast, historical data that’s only analyzed after the fact won’t be helpful, because there’s no do-overs, no 2025 Olympics!
    • The data is shared: that’s another key IoT Essential Truth.  “Decision-makers using SK Solutions on a daily basis span the entire organization. Besides health and safety officers, people responsible for logistics, human resources, operations and maintenance are among the typical users.”  The more former information silos share the data, the more likely they are to find synergistic solutions.
    • The system is inclusive, both in terms of data collection and benefits: SK Solutions’ Founder and Inventor Séverin Kezeu, came up with his collision-avoidance software pre-IoT, but when the IoT became practical he partnered with SAP, Cisco, and Honeywell to integrate and slice and dice the data yielded by the sensors they installed on cranes and vehicles and other sources.  For example, the height of these cranes makes them vulnerable to sudden weather changes, so weather data such as wind speed and direction must be factored in, as well as the “machinery’s position, movement, weight, and inertia…. The information is delivered on dashboards and mobile devices, visualized with live 3-D images with customizable views. It’s also incredibly precise.”As a result, by using SAP’s HANA platform, a system developed to reduce construction accidents also makes predictive maintenance of the cranes and other equipment, and lets the construction companies monitor Key Performance Indicators (KPIs) such as asset saturation, usage rates, and collisions avoided.  McKinsey reports that construction site efficiency could improve dramatically due to better coordination: “One study found that buffers built into construction project schedules allowed for unexpected delays resulting in 70 to 80 percent idle time at the worksite.Visibility alone can allow for shorter buffers to be built into the construction process.”

Several other great IoT solutions come to mind at the same time, both relating to dangerous industries. Off-shore oil rigs and mining were treated at length in the recent McKinsey omnibus IoT forecast, “The Internet of Things: Mapping the Value Beyond the Hype:”

  • off-shore rigs: “Much of the data collected by these sensors [30,000 on some rigs] today is used to monitor discrete machines or systems. Individual equipment manufacturers collect performance data from their own machines and the data can be used to schedule maintenance. Interoperability would significantly improve performance by combining sensor data from different machines and systems to provide decision makers with an integrated view of performance across an entire factory or oil rig. Our research shows that more than half of the potential issues that can be identified by predictive analysis in such environments require data from multiple IoT systems. Oil and gas experts interviewed for this research estimate that interoperability could improve the effectiveness of equipment maintenance in their industry by 100 to 200 percent.” (my emphasis). 
  • mining: “In one mining case study, using automated equipment in an underground mine increased productivity by 25 percent. A breakdown of underground mining activity indicates that teleremote hauling can increase active production time in mines by as much as nine hours every day by eliminating the need for shift changes of car operators and reducing the downtime for the blasting process. Another source of operating efficiency is the use of real-time data to manage IoT systems across different worksites, an example of the need for interoperability. In the most advanced implementations, dashboards optimized for smartphones are used to present output from sophisticated algorithms that perform complex, real-time optimizations. In one case study from the Canadian tar sands, advanced analytics raised daily production by 5 to 8 percent, by allowing managers to schedule and allocate staff and equipment more effectively. In another example, when Rio Tinto’s (one mine) crews are preparing a new site for blasting, they are collecting information on the geological formation where they are working. Operations managers can provide blasting crews with detailed information to calibrate their use of explosives better, allowing them to adjust for the characteristics of the ore in different parts of the pit.”
 In all of these cases, the safety and productivity problems — and solutions are intertwined.  As McKinsey puts it:
“Downtime, whether from repairs, breakdowns, or maintenance, can keep machinery out of use 40 percent of the time or more. The unique requirements of each job make it difficult to streamline work with simple, repeatable steps, which is how processes are optimized in other industries. Finally, worksite operations involve complex supply chains, which in mining and oil and gas often extend to remote and harsh locations.”
Could it be that the IoT will finally tame these most extreme work situations, and bring order, safety, and increased profitability?  I’m betting on it.

McKinsey IoT Report Nails It: Interoperability is Key!

I’ll be posting on various aspects of McKinsey’s new “The Internet of Things: Mapping the Value Beyond the Hype” report for quite some time.

First of all, it’s big: 148 pages in the online edition, making it the longest IoT analysis I’ve seen! Second, it’s exhaustive and insightful. Third, as with several other IoT landmarks, such as Google’s purchase of Nest and GE’s divestiture of its non-industrial internet division, the fact that a leading consulting firm would put such an emphasis on the IoT has tremendous symbolic importance.

McKinsey report — The IoT: Mapping the Value Beyond the Hype

My favorite finding:

“Interoperability is critical to maximizing the value of the Internet of Things. On average, 40 percent of the total value that can be unlocked requires different IoT systems to work together. Without these benefits, the maximum value of the applications we size would be only about $7 trillion per year in 2025, rather than $11.1 trillion.” (my emphasis)

This goes along with my most basic IoT Essential Truth, “share data.”  I’ve been preaching this mantra since my 2011 book, Data Dynamite (which, if I may toot my own horn, I believe remains the only book to focus on the sweeping benefits of a paradigm shift from hoarding data to sharing it).

I was excited to see that the specific example they zeroed in on was offshore oil rigs, which I focused on in my op-ed on “real-time regulations,” because sharing the data from the rig’s sensors could both boost operating efficiency and reduce the chance of catastrophic failure. The paper points out that there can be 30,000 sensors on an rig, but most of them function in isolation, to monitor a single machine or system:

“Interoperability would significantly improve performance by combining sensor data from different machines and systems to provide decision makers with an integrated view of performance across an entire factory or oil rig. Our research shows that more than half of the potential issues that can be identified by predictive analysis in such environments require data from multiple IoT systems. Oil and gas experts interviewed for this research estimate that interoperability could improve the effectiveness of equipment maintenance in their industry by 100 to 200 percent.”

Yet, the researchers found that only about 1% of the rig data was being used, because it rarely was shared off the rig with other in the company and its ecosystem!

The section on interoperability goes on to talk about the benefits — and challenges — of linking sensor systems in examples such as urban traffic regulation, that could link not only data from stationary sensors and cameras, but also thousands of real-time feeds from individual cars and trucks, parking meters — and even non-traffic data that could have a huge impact on performance, such as weather forecasts.  

While more work needs to be done on the technical side to increase the ease of interoperability, either through the growing number of interface standards or middleware, it seems to me that a shift in management mindset is as critical as sensor and analysis technology to take advantage of this huge increase in data:

“A critical challenge is to use the flood of big data generated by IoT devices for prediction and optimization. Where IoT data are being used, they are often used only for anomaly detection or real-time control, rather than for optimization or prediction, which we know from our study of big data is where much additional value can be derived. For example, in manufacturing, an increasing number of machines are ‘wired,’ but this instrumentation is used primarily to control the tools or to send alarms when it detects something out of tolerance. The data from these tools are often not analyzed (or even collected in a place where they could be analyzed), even though the data could be used to optimize processes and head off disruptions.”

I urge you to download the whole report. I’ll blog more about it in coming weeks.

Every IoT office needs this graphic on privacy and security

Long-time readers know that I frequently rant that privacy and security are Job 1 when it comes to the IoT.  

No apologies: it’s because I spent many years in corporate crisis management, and I learned the hard way that public trust is hard to earn, easy to lose, and, once lost, difficult or impossible to regain.

That’s why I was so glad to see this really informative, attractive, and scary infographic from Zora Lopez at Computer Science Zone, because it lays everything out so vividly.  Among the key points:

  1. (seen this before, but it still astounds me) In 2011, 20 typical households generated as much data as the entire Internet did as recently as 2008.
  2. the number of really-large (on scale of e-Bay, Target, etc.) data thefts grow annually.
  3. the bad guys particularly go after extremely sensitive data such as health, identity and financial.

It concludes with a particularly sobering reminder (you may remember my comment on the enthusiastic guys who presented at Wearables + Things and cheerfully commented that they would eventually get around to privacy and security — NOT!):

The barrier to entry in tech has never been lower, leaving many new organizations to later grapple with unsatisfactory security.” (my emphasis)

So: print a copy of the following for every employee and new hire, and put it on the cube’s wall immediately (here’s the original URL: http://www.computersciencezone.org/wp-content/uploads/2015/04/Security-and-the-Internet-of-Things.jpg#sthash.c6u2POMr.dpuf)

IoT Privacy and Security, from Computer Science Zone

Intel’s IoT tech improves its own manufacturing efficiency

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.”

 

Incredible example of rethinking “things” with Internet of Things

Ladies and gentlemen, I give you the epitome of the IoT-enabled product: the trash can!

My reader statistics do not indicate this blog has a heavy readership among trash cans, but let me apologize in advance to them for what I’m about to write: it’s not personal, just factual.

I’m sorry, but you municipal trash cans are pathetic!

Dented. Chipping paint. Trash overflowing. Smelly. Pests (ever seen any of those prize city rats? Big!!!) Sometime even knocked over. And, worst of all, you are so…. DUMB. You just sit there and don’t do anything.

BigBelly trash compactor and recycling center

But that was then, and this is now.

I have seen the future of trash cans, and, equally important, perhaps the best example I’ve seen of how smart designers and company strategists can –and must — totally rethink products’ design and how they are used because of the Internet of Things! 

At last week’s Re-Work Internet of Things Summit there were many exciting new IoT examples (I’ll blog others in coming weeks) but perhaps the one that got more people talking was the BigBelly trash compactor & recycling system, high-tech successor to the lowly trash can.

The company’s motto is that they are “transforming waste management practices and contributing to the Smart Cities of tomorrow.” Indeed!

I was first attracted to the BigBelly systems because of my alternative energy and environmental passions: they featured PV-powered trash compactors, which can quintuple the amount a trash container can hold, eliminating overflowing containers and the need to send trucks to empty them as frequently. Because the containers are closed, there’s no more ugly banana peels and McDonald’s wrappers assaulting your delicate eyes — or noses! Equally important, each is paired with a recycling container, which are almost never seen on city streets, dramatically reducing the amount of recyclables that go into regular trash simply because no recycling containers are accessible downtown.  These features alone would be a noteworthy advance compared to conventional trash cans.

But BigBelly wasn’t content to just improve the efficiency of trash and recyclable collection: they decided to make the containers smart.

The company worked with Digi to add wireless communications to the bins. This is a critical part of BigBelly’s broader significance: when the IoT first started to creep into corporate consciousness, of course designers thought about smart versions of high-value products such as cars, but lowly trash cans? That deserves real praise, because they fundamentally re-examined not only the product as it existed, but also realized that an IoT-based version that could also communicate real-time data would become much more versatile and much more valuable.

Here’s what has resulted so far (and I suspect that as the BigBellys are more widely deployed and both city administrators and others become aware of their increased functionality, other features will be added: I see them as “Smart City Hubs!”):

  • heatmap of trash generation in Lower Manhattan using real-time data from BigBellys and CLEAN dashboard

    instead of traditional pickup routes and schedules that were probably based on sheer proximity (or, as BigBelly puts it a little more colorfully, “muscle memory and gut instincts”), they now offer a real-time way to monitor actual waste generation, through the “CLEAN Management Console,” which allows DPW personnel to monitor and evaluate bins’ fullness, trends and historical analysis, for perspective. Collections can now be dynamic and driven by current needs, not historical patterns.

  • For those cities that opt for it, the company offers a Managed Services option where it does the analysis and management of the devices — not unlike the way jet turbine manufacturers now offer their customers value-added data that allows them to optimize performance — and generates new revenue streams for the manufacturers.
  • You may remember that I blogged a while ago about the “Collective Blindness” analogy: that, until the IoT, we humans simply couldn’t visualize much about the inner workings of the material world, so we were forced to do klugy work-arounds.  That’s not, strictly speaking, the case here, since trash in a conventional can is obviously visible, but the actual volume of trash was certainly invisible to those at headquarters. Now they can see — and really manage it.
  •  They can dramatically increase recycling programs’ participation rate and efficiency. As BigBelly says, the system provides “intelligent infrastructure to support ongoing operations and free up staffing and resources to support new and expanded recycling programs. Monitoring each separate stream volumes, days to fullness, and other activities in CLEAN enables you to make changes where needed to create a more effective public recycling program. Leverage the stations’ valuable sidewalk real estate to add messaging of encouraging words to change your users’ recycling behaviors.”Philadelphia is perhaps the best example of how effective the system can be. The city bought 210 of the recycling containers in 2009. On average, each collected 225 pounds of recyclables monthly, resulting in 23.5 tons of material diverted from landfills. Philly gets $50 per ton from the recycling — and avoiding $63 in landfill tipping fees, with a total benefit to the city of $113 per ton, or $2599 per month.

Here’s where it really gets neat, in my estimation.

Because the BigBellys are connected in real time, the devices can serve a number of real-time communication functions as well (enabled by an open API and an emphasis by BigBelly on finding collaborative uses). That includes making them hubs for a “mesh network” municipal wi-fi system (which, by the way, means that your local trash container/communications hub could actually save your life in a disaster or terror attack, when stationary networks may be disrupted, as I explained years ago in this YouTube video).

The list of benefits goes on (BigBelly lists all of them, right down to “Happy Cities,” on its web site). Trust me: if my premise is right that we can’t predict all of the benefits of the IoT at this point because we simply aren’t accustomed to thinking expansively about all the ways connected devices can be used, there will be more!

So here’s my take-away from the BigBelly:

If something as humble and ubiquitous as a municipal trashcan can  be transformed into a waste-reduction, recycling collection, municipal communication hub, then to fully exploit the Internet of Things’ full potential, we need to take a new, creative look at every material thing we interact with, no longer making assumptions about its limited role, and instead looking at it creatively as part of an interconnected network whose utility grows the more things (and people!) it’s connected with!

Let me know your ideas on how to capitalize on this new world of possibilities!

Sensors remain critical to spread of Internet of Things

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!