IoT for Gamechangers: Talkin’ Smart Cities

Pope Francis wasn’t the only one speaking truth to power at 10 AM this morning: I was a guest again on SAP’s “Coffee Break With Game Changers” (you can catch a rebroadcast in a few hours), talking with hostess Bonnie Graham and SAP’s Ira Berk about smart cities.

Having just read the great bio of Elon Musk, I contrasted the top-down, I-gotta-sign-off-on-every-purchase-over-$10,000 style of Musk (and Steve Jobs, for that matter) with the out-of-control (in the best sense of the term!), bottoms-up approach needed in gigantic, complex, ever-changing cities (blogged on this earlier this week) to make them “smart.” IMHO, smart cities will evolve from a wide range of small, incremental changes, both public and private.

One of my favorite examples that I mentioned was announced today by Mayor Marty Walsh here in the Home of the Bean and the Cod.  The city has already been partnering with Waze for months: it informs Waze of any planned road work and detours, and, in return, Waze gives the city its real-time data to respond to traffic jams. Today the mayor announced that bike-riding Traffic Enforcement Officers will be able to swoop in on double-parking miscreants using Waze data.  Oh yeah, there’s another party to this collaboration: you and I, who make Waze work by reporting traffic and obstacles that we encounter while driving the city’s streets. Perfect example of my IoT “Essential Truth” that we must share data.

There was a lot more on the show: hope you can tune in!

BTW: when Bonnie asked at the end of the show if we’d dust off our crystal balls and predict how the IoT will make smart cities by 2020 — I stuck my neck out and said it would much quicker for the reasons I cited in the above-mentioned post on smart cities, especially the free citywide IoT data network movement spearheaded by Amsterdam.  If you’re in Greater Boston and would like to be in the vanguard of this movement, meet us next Wednesday night at the kewl new InTeahouse space in Cambridge, to plan our strategy to launch the free, citywide (including neighborhoods!) Boston IoT Data Network!


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? 

Share It (Data) and They Will Come: Crowdsourced Citywide IoT Network

I haven’t been as excited about anything for a long time as I am about a global revolution that began last week in Amsterdam!

Cities are rapidly becoming the very visible and innovative laboratories for IoT innovation, which is logical, because they’ve been in the forefront of open data — as I saw first-hand when I was consulting for Vivek Kundra when he opened up vast amounts of real-time data as CTO for the District of Columbia as part of its Apps for Democracy initiative in 2008 that was part of the larger democratizing data movement.

Now there’s an exciting new development in Amsterdam, that really is bringing power to the people: The Things Network, the first crowdsourced free citywide IoT district. Astonishingly, volunteers brought the whole system to launch in only four weeks!

So far, the creators are visualizing a wide range of uses, but I particularly liked a particularly local one for a city synonymous with canals:

“A pilot project to demonstrate the Things Network’s potential will see boat owners in the city (there are many, thanks to its network of canals) able to place a small bowl in the base of their vessel. If the boat develops a leak and starts taking on water, the bowl will use the network to send an SMS alert to a boat maintenance company that will come along and fix the problem.”

How cool is that?  It also illustrates what I think is one of the key intangibles about the IoT: when you empower everyone (and I mean that literally!) by opening up data, people will find more and more innovative IoT devices and services, stimulated by their own particular needs, desires — and sometimes, even pain (that’s why I think even the most optimistic views of the IoT’s impact will be dwarfed as it becomes ubiquitous!).

Even more exciting, the group’s goal is to bring the technology to every city in the world! That, my friends, will be an incredible global game-changer. Think of it: EVERY city will become an open laboratory for change.

The Things Network uses low-power, low-bandwidth LoRaWAN technology to create the network: ten $1,200 hubs covered the whole city!  Having been hiding under a rock, I must admit I’d never heard of LoRaWan. Here are the benefits:

  • don’t need 3G or WiFi to connect with the Internet — no WiFi passwords, mobile subscriptions
  • no setup costs
  • low battery usage
  • long range
  • low bandwidth.

The whole scheme reminds me of the old Andy-Hardy-it’s-crazy-enough-it-might-work thinking:

“Dutch entrepreneur Wienke Giezeman came up with the idea for the Things Network just six weeks ago when he came across a €1,000 ($1,100) LoRaWAN gateway device and realized that with 10 such devices, the whole of Amsterdam could be covered. He pitched his idea at an Internet of Things meetup in the city and received a positive response.

“Work then began to create a community-owned data network that developers could build on top of without any proprietary restrictions. Companies including The Next Web and accountancy giant KPMG have agreed to host gateway devices at their premises, and the City of Amsterdam local authority is enthusiastic about the idea.”

How’s this for a vision?

“Because the costs are very low, we do not have to rely on large telco corporations to build such a network. Instead, we can crowdsource the network and make it public without any form of subscription. Our mission is to enable a network by the users for the users.” (my emphasis)

Most important from a democratizing data standpoint, it will all be open source:

“Our goal is to make the network architecture as decentralized as possible. And avoid any points of failure or control. We already have a community of 10 developers writing network software and equipment firmware.”

Giezeman wants to cut the cost before launching his plan of making the concept worldwide. He will soon launch a Kickstarter campaign to fund production of a smaller, €200 ($220) LoRaWan (vs. the $1,200 current ones). He may offer consulting services to capitalize on the idea, but that’s not the current priority.

That kind of openness and lack of strings attached, IMHO, is going to really lead to incredible innovation!  We’re holding a Boston IoT MeetUp hackathon next month to try to bring similar innovation to The Hub, and wouldn’t it be wonderful if cities everywhere launched a virtuous competition to speed smart cities’ adoption (and, don’t forget: this has huge implications for companies as well: there’s nothing to stop smart companies from creating new products and services to capitalize on the shared data!).

I note Amsterdam is 84 square miles, and The Hub of the Universe is 89 sq. miles, so I suspect the costs would be similar here.  I’m throwing down the gauntlet: let’s make Boston the second IoT city!

Let a thousand neighborhoods bloom!


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!  

Give It Up, People: Government Regulation of IoT Is Vital

Could this be the incident that finally gets everyone in the IoT industry to — as I’ve said repeatedly in the past — make privacy and security Job 1 — and to drop the lobbying groups’ argument that government regulation isn’t needed? 

I hope so, because the IoT’s future is at stake, and, frankly, not enough companies get it.

I’m referring to the Chrysler recall last week of 1.4 million Jeeps for a security patch after WIRED reported on an experiment in which two white-hat hackers remotely disabled a Jeep on an Interstate from miles away, exploiting a vulnerable link between its entertainment and control systems.  Put yourself in the place of reporter Andy Greenberg, then tell me with a straight face that you wouldn’t be out of your mind if this happened to you:

“As the two hackers remotely toyed with the air-conditioning, radio, and windshield wipers, I mentally congratulated myself on my courage under pressure. That’s when they cut the transmission.

Immediately my accelerator stopped working. As I frantically pressed the pedal and watched the RPMs climb, the Jeep lost half its speed, then slowed to a crawl. This occurred just as I reached a long overpass, with no shoulder to offer an escape. The experiment had ceased to be fun.

At that point, the interstate began to slope upward, so the Jeep lost more momentum and barely crept forward. Cars lined up behind my bumper before passing me, honking. I could see an 18-wheeler approaching in my rearview mirror. I hoped its driver saw me, too, and could tell I was paralyzed on the highway.

“You’re doomed!” Valasek [one of the hackers] shouted, but I couldn’t make out his heckling over the blast of the radio, now pumping Kanye West. The semi loomed in the mirror, bearing down on my immobilized Jeep.”

OK: calm down, get a cool drink, and, when your Apple Watch says your heart beat has returned to normal, read on….

But, dear reader, our industry’s leaders, assumedly knowing the well-publicized specifics of the Chrysler attack, had the hubris to still speak at a hearing of the Internet Subcommittee of the House of Representatives Judiciary Committee last week and claim (according to CIO) that that government regulation of the IoT industry wasn’t needed.

CEA CEO Gary Shapiro said in calling for government “restraint”:

“It’s up to manufacturers and service providers to make good decisions about privacy and security, or they will fail in the marketplace….. Industry-driven solutions are best to promote innovation while protecting consumers.”

Sorry, Gary: if someone dies because their Jeep got spoofed, the survivors’ attorneys won’t be content with the company’s failure in the marketplace.

There are some important collaborative efforts to create privacy and security standards for the IoT, such as the AllSeen Alliance. However, as I’ve written before, there are also too many startups who defer building in privacy and security protections until they’ve solved their technology needs, and others, most famously TRENDnet, who don’t do anything at all, resulting in a big FTC fine.  There are simply too many examples of hackers using the Shodan site to hack into devices, not to mention academics and others who’ve showed security flaws that might even kill you if exploited.

One local IoT leader, Paddy Srinivasan of LoMein, gets it, as reported today by the Boston Globe‘s Hiawatha Bray:

“‘I think it is a seminal moment…. These new devices need a fresh approach and a new way of thinking about security, and that is the missing piece.'”

But it’s too late to just talk about self-policing.

Massachusetts’ own Ed Markey and his Connecticut counterpart, Richard Blumenthal, have called the associations’ bluff, and filed legislation, The Security and Privacy in Your Car Act (AKA SPY Car, LOL)  that would require the National Highway Traffic Safety Administration (NHTSA) and the Federal Trade Commission (FTC) to establish federal standards to secure cars and protect drivers’ privacy. It would also create a rating system — or “cyber dashboard”— telling drivers about how well the vehicle protects drivers’ security and privacy beyond those minimum standards. This comes in the wake of the Markey study I reported on last Winter documenting car companies’ failure to build in adequate cyber-hacking protections.

Guess what, folks?  This is only the beginning.  Probably the only thing I’ve ever agreed with Dick Cheney on (ok, we agree it’s cool to have been born in Wyoming and that Lynne Cheney is a great writer), is that it wouldn’t be cool for the Veep to have his pacemaker hacked, so you can bet there will be legislation and regulations soon governing privacy and security for wearables as well.

As I’ve said before, I come at this issue differently from a lot of engineers, having earned my keep for many years doing crisis management for Fortune 100 companies that bet the farm by doing dumb things that could destroy public trust in them overnight. Once lost, that trust is difficult, if not impossible, to regain.  Even worse, in this case, cavalier attitudes by even one IoT company, if the shock value of the results is great enough, could make everyone in the industry suffer.

So, if you’re arguing for no regulation of the IoT industry, I have just one suggestion: shut up,clean up your act and take a positive role in shaping regulations that would be performance-based, not prescriptive: the horse has already left the barn.

Now I have to check my Apple Watch to see when my heart rate will get back to normal.


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:

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.”


Virtual Sensor Networks: a key #IoT tool?

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?

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…