Smart Aging: Kanega watch for seniors Kickstarter campaign ends today

“Independence with Dignity” is the motto for Jean Anne Booth’s Kanega Watch, which is in the last day of its Kickstarter campaign.

I’m not crazy about it, but in general I like what you see, and hope you get on board.  It addresses three major concerns for the elderly:

Kanega watchlike what I see, and hope you’ll get on board!  It’s designed to deal with three critical aging concerns:

  • falls
  • medication reminders
  • wandering.

I met the woman behind it at a conference in Boston last Summer, and even though the prototype at that point looked very unappealing, this looks more promising.

I’m in the process of creating a list of 10 objective criteria for evaluating devices and apps that fit with my “Smart Aging” paradigm shift, which combines Quantified Self devices to encourage healthy habits and change your relationship with your doctor into a partnership, and smart home devices, which make it easier to manage your home when elderly, so you can “age in place.”  Here’s how it stacks up against my criteria (which, BTW, are still in development — comments welcomed). Bear in mind that I haven’t seen current prototype, and the site doesn’t answer all of my questions. :

Is it easy to use?

  1. Does it give you a choice of ways to interact, such as voice, text or email?
  2. Does it give you reminders?
  3. Is it easy for you to program, or allow someone else to do it remotely?
  4. Does it have a large display and controls?
  5. Is it intuitive?
  6. Does it require professional installation?
  7. Is it flexible: can it be adjusted? Is it single purpose, or does it allow other devices to plug in and create synergies?

YES: voice-activated, rather than requiring buttons. No programming.


Does it protect privacy & security?

  1. Is storage local vs. cloud or company’s servers? Is data encrypted? Anomized?
  2. Do you feel creepy using it?
  3. Does it protect against exploitation by scam artists (such as identifying callers)?
  4. Is it password-protected?
  5. Is security “baked in” or an afterthought?

NO CLUE.


Does it complicate your life, or simplify it?

YES: doesn’t require a smartphone to function, and is voice-activated rather than using buttons.

Does it protect privacy and security?

NO CLUE.

 

Is it affordable?

  1. Are there monthly fees? If so, low or high?
  2. Is there major upfront cost?
  3. Does full functioning require accessories?

IFFY: You can get one by contributing $279 to the Kickstarter campaign. If that’s the retail price, it’s a little pricey, but lower than the Apple Watch base, $349, and probably a good price considering the value added services . Didn’t see anything about a monthly fee for the fall reporting & response service.

Does it stigmatize and/or condescend?

  1. Is it stylish, or does the design” shout” that it’s for seniors?
  2. Is the operation or design babyish?
  3. Would younger people use it?

NO: it doesn’t have a stigmatizing button, & uses a familiar form factor (watch).

Does it use open or proprietary standards?

NO CLUE.

 

Is the information shareable if you choose to do so?

NO CLUE.

 

Can you learn something from it to improve your life and empower yourself?

  1. For example, does health data encourage you to exercise more, or eat better?

NO: doesn’t give you feedback, measure your activity, etc.

Does it help you do something you couldn’t do before?

  1. Does it create a new range of services that were simply impossible with past technologies?

YES: The wandering alert (offers directions home) is new. Otherwise, just does some things such as medication alerts and calling for help that other devices have done.

Is it sturdy?

YES.

 

Does it have “loveability” (i.e., connect with the user emotionally)?

(This term was coined by David Rose in Enchanted Objects, and refers to products that are adorable or otherwise bond with the user)

YES: it has a Siri-like voice, which you can name, which gives reminders about taking meds and gives you directions home if you wander.
I’d give it about a 5 out of 10: I wouldn’t call this a must have — I’d like a little more of a multi-purpose tool that combines smart home and Quantified Self functions — like the Apple Watch (again, disclaimer that I work part time at Apple Store — but don’t have any proprietary info.) The watch is a little too clunky looking for me (prefer the Jony Ive-aesthetics of the Apple Watch), but it looks promising — and doesn’t require coupling to a smartphone, which is befuddling to a lot of seniors.

Kickstarter backers will begin receiving their Kanega watches in February 2016, with general market availability in summer 2016. The site doesn’t say anything about price.

Only a few hours left to join the Kickstarter campaign!


Yeah, I couldn’t figure out the names either. Turns out it’s from Cherokee: “Unalii” is “friend”, and “Kanega” is “speak.”  You learn something every day….

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The Internet of Things’ Essential Truths

I’ve been writing about what I call the Internet of Things’ “Essential Truths” for three years now, and decided the time was long overview to codify them and present them in a single post to make them easy to refer to.

As I’ve said, the IoT really will bring about a total paradigm shift, because, for the the first time, it will be possible for everyone who needs it to share real-time information instantly. That really does change everything, obliterating the “Collective Blindness” that has hampered both daily operations and long-term strategy in the past. As a result, we must rethink a wide range of management shibboleths (OK, OK, that was gratuitous, but I’ve always wanted to use the word, and it seemed relevant here, LOL):

  1. First, we must share data. Tesla leads the way with its patent sharing. In the past, proprietary knowledge led to wealth: your win was my loss. Now, we must automatically ask “who else can use this information?” and, even in the case of competitors, “can we mutually profit from sharing this information?” Closed systems and proprietary standards are the biggest obstacle to the IoT.
  2. Second, we must use the Internet of Things to empower workers. With the IoT, it is technically possible for everyone who could do their job better because of access to real-time information to share it instantly, so management must begin with a new premise: information should be shared with the entire workforce. Limiting access must be justified.
  3. Third, we must close the loop. We must redesign our data management processes to capitalize on new information, creating continuous feedback loops.
  4. Fourth, we must rethink products’ roles. Rolls-Royce jet engines feed back a constant stream of real-time data on their operations. Real-time field data lets companies have a sustained dialogue with products and their customers, increasingly allowing them to market products as services, with benefits including new revenue streams.
  5. Fifth, we must develop new skills to listen to products and understand their signals. IBM scientists and medical experts jointly analyzed data from sick preemies’ bassinettes & realized they could diagnose infections a day before there was any visible sign. It’s not enough to have vast data streams: we need to understand them.
  6. Sixth, we must democratize innovation. The wildly-popular IFTTT web site allows anyone to create new “recipes” to exploit unforeseen aspects of IoT products – and doesn’t require any tech skills to use. By sharing IoT data, we empower everyone who has access to develop new ways to capitalize on that data, speading the IoT’s development.
  7. Seventh, and perhaps most important, we must take privacy and security seriously. What responsible parent would put an IoT baby monitor in their baby’s room after the highly-publicized incident when a hacker exploited the manufacturer’s disregard for privacy and spewed a string of obscenities at the baby? Unless everyone in the field takes privacy and security seriously, the public may lose faith in the IoT.

There you have ’em: my best analysis of how the Internet of Things will require a revolution not just in technology, but also management strategy and practices. What do you think?

Remember: The IoT Is Primarily About Small Data, Not Big

Posted on 16th March 2015 in data, Internet of Things, M2M, management, manufacturing, open data

In one of my fav examples of how the IoT can actually save lives, sensors on only eight preemies’ incubators at Toronto’s Hospital for Sick Children yield an eye-popping 90 million data points a day!  If all 90 million data points get relayed on to the “data pool,” the docs would be drowning in data, not saving sick preemies.

Enter “small data.”

Writing in Forbes, Mike Kavis has a worthwhile reminder that the essence of much of the Internet of Things isn’t big data, but small. By that, he means:

a dataset that contains very specific attributes. Small data is used to determine current states and conditions  or may be generated by analyzing larger data sets.

“When we talk about smart devices being deployed on wind turbines, small packages, on valves and pipes, or attached to drones, we are talking about collecting small datasets. Small data tell us about location, temperature, wetness, pressure, vibration, or even whether an item has been opened or not. Sensors give us small datasets in real time that we ingest into big data sets which provide a historical view.”

Usually, instead of aggregating  ALL of the data from all of the sensors (think about what that would mean for GE’s Durathon battery plant, where 10,000 sensors dot the assembly line!), the data is originally analyzed at “the edge,” i.e., at or near the point where the data is collected. Then only the data that deviates from the norm (i.e., is significant)  is passed on to to the centralized data bases and processing.  That’s why I’m so excited about Egburt, and its “fog computing” sensors.

As with sooo many aspects of the IoT, it’s the real-time aspect of small data that makes it so valuable, and so different from past practices, where much of the potential was never collected at all, or, if it was, was only collected, analyzed and acted upon historically. Hence, the “Collective Blindness” that I’ve written about before, which limited our decision-making abilities in the past. Again, Kavis:

“Small data can trigger events based on what is happening now. Those events can be merged with behavioral or trending information derived from machine learning algorithms run against big data datasets.”

As examples of the interplay of small and large data, he cites:

  • real-time data from wind turbines that is used immediately to adjust the blades for maximum efficiency. The relevant data is then passed along to the data lake, “..where machine-learning algorithms begin to understand patterns. These patterns can reveal performance of certain mechanisms based on their historical maintenance record, like how wind and weather conditions effect wear and tear on various components, and what the life expectancy is of a particular part.”
  • medicine containers with smart labels. “Small data can be used to determine where the medicine is located, its remaining shelf life, if the seal of the bottle has been broken, and the current temperature conditions in an effort to prevent spoilage. Big data can be used to look at this information over time to examine root cause analysis of why drugs are expiring or spoiling. Is it due to a certain shipping company or a certain retailer? Are there re-occurring patterns that can point to problems in the supply chain that can help determine how to minimize these events?”

Big data is often irrelevant in IoT systems’ functioning: all that’s needed is the real-time small data to trigger an action:

“In many instances, knowing the current state of a handful of attributes is all that is required to trigger a desired event. Are the patient’s blood sugar levels too high? Are the containers in the refrigerated truck at the optimal temperature? Does the soil have the right mixture of nutrients? Is the valve leaking?”

In a future post, I’ll address the growing role of data scientists in the IoT — and the need to educate workers on all levels on how to deal effectively with data. For now, just remember that E.F. Schumacher was right: “small is beautiful.”

 

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Apple ResearchKit will launch medical research paradigm shift to crowd-sourcing

Amidst the hoopla about the new MacBook and much-anticipated Apple Watch, Apple snuck something into Monday’s event that blew me away (obligatory disclaimer: I work part-time at The Apple Store, but the opinions expressed here are mine).

My Heart Counts app

Four years after I proselytized about the virtues of democratizing data in my Data Dynamite: how liberating data will transform our world book (BTW: pardon the hubris, but I still think it’s the best thing out there about the attitudinal shift needed to capitalize on sharing data), I was so excited to learn about the new ResearchKit.

Tag line? “Now everybody can do their part to advance medical research.”

The other new announcements might improve your quality of life. This one might save it!

As Senior VP of Operations Jeff Williams said in announcing the kit,  the process of medical research ” ..hasn’t changed in decades.” That’s not really true: as I wrote in my book, the Quantified Self movement has been sharing data for several years, as well as groups such as CureTogether and PatientsLikeMe. However, what is definitely true is that no one has harnessed the incredible power of the smartphone for this common goal until now, and that’s really incredible. It’s a great example of my IoT Essential Truth of asking “who else could use this data?

A range of factors cast a pall over traditional medical research.

Researchers have had to cast a broad net even to get 50-100 volunteers for a clinical trial (and may have to pay them, to boot, placing the results validity when applied to the general population in doubt).  The data has often been subjective (in the example Williams mentioned, Parkinson’s patients are classified by a doctor simply on the basis of walking a few feet). Also, communication about the project has been almost exclusively one way, from the researcher to the patient, and limited, at best.

What if, instead, you just had to turn on your phone and open a simple app to participate? As the website says, “Each one [smartphone] is equipped with powerful processors and advanced sensors that can track movement, take measurements, and record information — functions that are perfect for medical studies.” Suddenly research can be worldwide, and involve millions of diverse participants, increasing the data’s amount and validity (There’s a crowdsourcing research precedent: lot of us have been participating in scientific crowdsourcing for almost 20 years, by installing the SETI@Home software that runs in the background on our computers, analyzing data from deep space to see if ET is trying to check in)!

Polymath/medical data guru John Halamka, MD wrote me that:

“Enabling patients to donate data for clinical research will accelerate the ‘learning healthcare system’ envisioned by the Institute of Medicine.   I look forward to testing out Research Kit myself!”

The new apps developed using ResearchKit harvest information from the Health app that Apple introduced as part of iOS8. According to Apple:

“When granted permission by the user, apps can access data from the Health app such as weight, blood pressure, glucose levels and asthma inhaler use, which are measured by third-party devices and apps…. ResearchKit can also request from a user, access to the accelerometer, microphone, gyroscope and GPS sensors in iPhone to gain insight into a patient’s gait, motor impairment, fitness, speech and memory.

Apple announced that it has already collaborated with some of the world’s most prestigious medical institutions, including Mass General, Dana-Farber, Stanford Medical, Cornell and many others, to develop apps using ResearchKit. The first five apps target asthma, breast cancer, cardiovascular disease, diabetes and Parkinson’s disease.  My favorite, because it affects the largest number of people, is the My Heart Counts one. It uses the iPhone’s built-in motion sensors to track participants’ activity, collecting data during a 6-minute walk test from those who are able to walk that long. If participants also have a wearable activity device connecting with the Health app (aside: still don’t know why my Jawbone UP data doesn’t flow to the Health app, even though I made the link) , they are encouraged to use that as well. Participants will also enter data about their heart disease risk factors and their lab tests readings to get feedback on their chances of developing heart disease and their “heart age.” Imagine the treasure trove of cardiac data it will yield!

 A critical aspect of why I think ResearchKit will be have a significant impact is that Apple decided t0 make it open source, so that anyone can tinker with the code and improve it (aside: has Apple EVER made ANYTHING open source? Doubt it! That alone is noteworthy).  Also, it’s important to note, in light of the extreme sensitivity of any personal health data, that Apple guarantees that it will not have access to any of the personal data.

Because of my preoccupation with “Smart Aging,” I’m really interested in whether any researchers will specifically target seniors with ResearchKit apps. I’ll be watching carefully when the Apple Watch comes out April 24th to see if seniors buy them (not terribly optimistic, I must admit, because of both the cost and the large number of seniors I help at The Apple Store who are befuddled by even Apple’s user-friendly technology) because the watch is a familiar form factor for them (I haven’t worn a watch since I got my first cell phone, and most young people I know have never had one) and might be willing to use them to participate in these projects.

N0w, if you’ll excuse me, I just downloaded the My Heart Counts app, and must find out my “heart age!”


 

Doh!  Just after I posted this, I saw a really important post on Ars Technica pointing out that this brave new world of medical research won’t go anywhere unless the FDA approves:

“As much as Silicon Valley likes to think of itself as a force for good, disrupting this and pivoting that, it sometimes forgets that there’s a wider world out there. And when it comes to using devices in the practice of medicine, that world contains three very important letters: FDA. That’s right, the US Food and Drug Administration, which Congress has empowered to regulate the marketing and research uses of medical devices.

“Oddly, not once in any of the announcement of ResearchKit did we see mention of premarket approval, 510k submission, or even investigational device exemptions. Which is odd, because several of the uses touted in the announcement aren’t going to be possible without getting the FDA to say yes.”

I remember reading that Apple had reached out to the FDA during development of the Apple Watch, so I’m sure none of this comes as a surprise to them, and any medical researcher worth his or her salt is also aware of that factor. However, the FDA is definitely going to have a role in this issue going forward, and that’s as it should be — as I’ve said before, with any aspect of the IoT, privacy and security is Job One.

 

 

FTC report provides good checklist to design in IoT security and privacy

FTC report on IoT

FTC report on IoT

SEC Chair Edith Ramirez has been pretty clear that the FTC plans to look closely at the IoT and takes IoT security and privacy seriously: most famously by fining IoT marketer TrendNet for non-existent security with its nanny cam.

Companies that want to avoid such actions — and avoid undermining fragile public trust in their products and the IoT as a whole — would do well to clip and refer to this checklist that I’ve prepared based on the recent FTC Report, Privacy and Security in a Connected World, compiled based on a workshop they held in 2013, and highlighting best practices that were shared at the workshop.

  1. Most important, “companies should build security into their devices at the outset, rather than as an afterthought.” I’ve referred before to the bright young things at the Wearables + Things conference who used their startup status as an excuse for deferring security and privacy until a later date. WRONG: both must be a priority from Day One.

  2. Conduct a privacy or security risk assessment during design phase.

  3. Minimize the data you collect and retain.  This is a tough one, because there’s always that chance that some retained data may be mashed up with some other data in future, yielding a dazzling insight that could help company and customer alike, BUT the more data just floating out there in “data lake” the more chance it will be misused.

  4. Test your security measures before launching your products. … then test them again…

  5. “..train all employees about good security, and ensure that security issues are addressed at the appropriate level of responsibility within the organization.” This one is sooo important and so often overlooked: how many times have we found that someone far down the corporate ladder has been at fault in a data breach because s/he wasn’t adequately trained and/or empowered?  Privacy and security are everyone’s job.

  6. “.. retain service providers that are capable of maintaining reasonable security and provide reasonable oversight for these service providers.”

  7. ‘… when companies identify significant risks within their systems, they should implement a defense-in -depth approach, in which they consider implementing security measures at several levels.”

  8. “… consider implementing reasonable access control measures to limit the ability of an unauthorized person to access a consumer’s device, data, or even the consumer’s network.” Don’t forget: with the Target data breach, the bad guys got access to the corporate data through a local HVAC dealer. Everything’s linked — for better or worse!

  9. “.. companies should continue to monitor products throughout the life cycle and, to the extent feasible, patch known vulnerabilities.”  Privacy and security are moving targets, and require constant vigilance.

  10. Avoid enabling unauthorized access and misuse of personal information.

  11. Don’t facilitate attacks on other systems. The very strength of the IoT in creating linkages and synergies between various data sources can also allow backdoor attacks if one source has poor security.

  12. Don’t create risks to personal safety. If you doubt that’s an issue, look at Ed Markey’s recent report on connected car safety.

  13. Avoid creating a situation where companies might use this data to make credit, insurance, and employment decisions.  That’s the downside of cool tools like Progressive’s “Snapshot,” which can save us safe drivers on premiums: the same data on your actual driving behavior might some day be used become compulsory, and might be used to deny you coverage or increase your premium).

  14. Realize that FTC Fair Information Practice Principles will be extended to IoT. These “FIPPs, ” including “notice, choice, access, accuracy, data minimization, security, and accountability,” have been around for a long time, so it’s understandable the FTC will apply them to the IoT.  Most important ones?  Security, data minimization, notice, and choice.

Not all of these issues will apply to all companies, but it’s better to keep all of them in mind, because your situation may change. I hope you’ll share these guidelines with your entire workforce: they’re all part of the solution — or the problem.

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Real-time data sharing critical to “Smart Aging” and collaborative health care

Posted on 25th February 2015 in health, Internet of Things, open data, SmartAging

It’s hard to describe to someone who hasn’t encountered the phenomenon first hand, but there’s something really exciting (and perhaps transformative) when data is shared rather than hoarded. When data becomes the focus of discussions, different perspectives reveal different aspects of the data that even the brightest person couldn’t discover working in isolation.

That transformative aspect is very exciting when it involves health care.

I’ve written before about the life-saving discoveries when doctors and data scientists from Toronto’s Hospital for Sick Children and IBM collaboratively analyzed data from newborns in the NICU and discovered early signs of infections that allowed them to begin treatment a day before there was any outward manifestation of the infection. Now, the always-informative SAP Innovation blog (I don’t just say that because they’re kind enough to reprint many of my posts: I find it an eclectic and consistently informative source of information on all things dealing with innovation!) has an interesting piece about how Dartmouth Hitchcock is sharing real-time data with patients considering knee-replacement surgery.

In some cases, that data leads patients to decide — sigh of relief — their condition doesn’t warrant surgery at this point, while it confirms the need for others.  In both cases, there’s a subtle but important shift in the doctor-patient relationship that’s at the heart of my proposed “Smart Aging” paradigm shift: away from the omnipotent doctor telling the patient what’s needed and instead empowering the patient to be an active partner in his or her care.

The key is using the data to predict outcomes:

“‘Prior to anyone ever getting surgery, we want to try to predict how they’re going to do,’ Dartmouth-Hitchcock orthopedic surgeon Michael Sparks said in an SAP video. ‘But we’ve never had that missing tool, which is real-time data.’

“D-H recently began using real-time data analytics and predictive technologies to help people suffering from chronic knee pain to choose wisely and improve their outcomes. ‘It is actually a partnership to help people get ‘through this,’ Sparks said. ‘And it’s the analysis of data that adds to their ability to make a decision.’”

For the first time, the patient’s choice really becomes informed consent.

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IFTTT DO apps: neat extension of my fav #IoT crowdsourcing tool!

Have I told you lately how much I love IFTTT? Of course!  As I’ve said, I think they are a phenomenal example of my IoT “Essential Truth” question: who else can use this data?

IFTTT_DO_buttonNow, they’ve come up with 3 new apps, the “DO button,” “DO camera,” and “DO Note,” that make this great tool even more versatile!

With a DO “recipe,” you simply tap on the appropriate app, and the “recipe” runs. Presto! Change-o!

As a consultant who must bill for his time, I particularly like the one that lets you “Track Your Work hours” on Google Drive, but you’re sure to find your own favorites in categories such as play, work, home, families, and essentials. Some are just fun, and some will increase your productivity or help manage your household more easily (hmm: not sure where “post a note to your dog’s timeline” fits in (aside to my sons: feel free to “send notes to your data via email”.  If past experience is any indication, there should be many, many more helpful “Do” recipes as soon as users are familiar with how to create them.

As I’ve said before, it’s no reflection on the talented engineers at HUE, NEST, et. al., but there’s simply no way they could possibly visualize all the ways that their devices could be used and/or combined with others, and that’s why IFTTT, by adding the crowdsourcing component and democratizing data, is so important to speeding the IoT’s deployment.

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

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

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

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

Two dealing with sensors did strike my eye:

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

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

Both make a lot of sense.

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

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

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Gartner study confirms senior managers don’t understand IoT

Posted on 21st February 2015 in Internet of Things, M2M, management, manufacturing, marketing, strategy

The “Managing the Internet of Things Revolution” e-guide I wrote for SAP was aimed at C-level executives. Even though it’s proven popular enough that the company is translating it into several languages, it appears we need to redouble our efforts to Managing_the_Internet_of_Things_Revolutionbuild IoT awareness among executives.

I say that because Gartner has just come out with a survey confirming my suspicions: even though a lot of companies now think the IoT will have a major effect on them, they’re clueless about how to manage it and most have yet to launch major IoT initiatives.

In fact, “many survey respondents felt that the senior levels of their organizations don’t yet have a good understanding of the potential impact of the IoT.” (my emphasis)

 

That’s despite the fact that a key conclusion of my guide was that (even though the IoT is a long way from full maturity) companies can and should begin their IoT strategies and implementation now, because they can already achieve significant savings in operating costs, improve marketing, and create new revenue streams with the current early stage sensors and analytical tools. Getting started will also build their confidence and familiarity with IoT tools and strategy before they begin more dramatic transformational strategies.

Consider these findings from the survey of 463 business and IT leaders:

  • 40% of companies think the IoT will at least bring new short-term revenue and cost reduction opportunities in the next three years — or perhaps even transform them. More than 60% think that will be true over 5 years or more.
  • Fewer than 25% said their company had “established clear business leadership for the IoT,” — even among the companies predicting a significant  – this includes those who said they expect the IoT to have a significant or transformational impact, says Gartner (however, 35% of them came from this group).
  • Yet, few have delegated specific responsibility for IoT strategy and management: “… less than one-quarter of survey respondents has established clear business leadership for the IoT, either in the form of a single organizational unit owning the issue or multiple business units taking ownership of separate IoT efforts.”
  • “attitudes toward the IoT vary widely by industry. For example, board of directors’ understanding of the IoT was rated as particularly weak in government, education, banking and insurance, whereas the communications and services industries scored above-average ratings for senior executive understanding of the IoT.”

Gartner concluded most companies have yet to really create IoT strategies:

“‘The survey confirmed that the IoT is very immature, and many organizations have only just started experimenting with it,’ said Nick Jones, vice president and distinguished analyst at Gartner. ‘Only a small minority have deployed solutions in a production environment. However, the falling costs of networking and processing mean that there are few economic inhibitors to adding sensing and communications to products costing as little as a few tens of dollars. The real challenge of the IoT is less in making products ‘smart’ and more in understanding the business opportunities enabled by smart products and new ecosystems.’ However, a lack of clear business or technical leadership is holding back investment in the technology.” (my emphasis)

In line with my current preoccupation, privacy and security, the survey did show companies are concerned with both issues, as well as with finding talented new staff who understand the IoT and how to benefit from it. According to Steve Kleyhans, Gartner’s research vp:

 “While a single leader for the IoT is not essential, leadership and vision are important, even in the form of several leaders from different business units. We expect that over the next three years, more organizations will establish clear leadership, and more will recognize the value of some form of an IoT center of excellence because of the need to master a wide range of new technologies and skills.”

If you haven’t launched any IoT projects or begun to create a strategy, the writing’s on the wall: get going!


Carpe diem: I take this survey as an omen that there’s a desperate need for When Things Can Talk: profiting from the Internet of Things revolution,” my proposed full-length book on IoT corporate strategy. Let me know if you can suggest a possible publisher!

The #IoT Can Kill You! Got Your Attention? Car Security a Must

The Internet of Things can kill you.

Got your attention? OK, maybe this is the wake-up call the IoT world needs to make certain that privacy and security are baked in, not just afterthoughts.

Markey_IoT_car_reportI’ve blogged before about how privacy and security must be Job 1, but now it’s in the headlines because of a new report by our Mass. Senator, Ed Markey (Political aside: thanks, Ed, for more than 30 years of leadership — frequently as a voice crying in the wilderness — on the policy implications of telecomm!), “Tracking & Hacking: Security & Privacy Gaps Put American Drivers at Risk,” about the dangers of not taking the issues seriously when it comes to smart cars.

I first became concerned about this issue when reading “Look Out, He’s Got an Phone,!” (my personal nominee for all-time most wry IoT headline…), a litany of all sorts of horrific things, such as spoofing the low air-pressure light on your car so you’ll pull over and the Bad Guys can get it would stop dead at 70 mph,  that are proven risks of un-encrypted automotive data.  All too typical was the reaction of Schrader Electronics, which makes the tire sensors:

“Schrader Electronics, the biggest T.P.M.S. manufacturer, publicly scoffed at the Rutgers–South Carolina report. Tracking cars by tire, it said, is ‘not only impractical but nearly impossible.’ T.P.M.S. systems, it maintained, are reliable and safe.

“This is the kind of statement that security analysts regard as an invitation. A year after Schrader’s sneering response, researchers from the University of Washington and the University of California–San Diego were able to ‘spoof’ (fake) the signals from a tire-pressure E.C.U. by hacking an adjacent but entirely different system—the OnStar-type network that monitors the T.P.M.S. for roadside assistance. In a scenario from a techno-thriller, the researchers called the cell phone built into the car network with a message supposedly sent from the tires. ‘It told the car that the tires had 10 p.s.i. when they in fact had 30 p.s.i.,’ team co-leader Tadayoshi Kohno told me—a message equivalent to ‘Stop the car immediately.’ He added, ‘In theory, you could reprogram the car while it is parked, then initiate the program with a transmitter by the freeway. The car drives by, you call the transmitter with your smartphone, it sends the initiation code—bang! The car locks up at 70 miles per hour. You’ve crashed their car without touching it.’”

Hubris: it’ll get you every time….

So now Senator Markey lays out the full scope of this issue, and it should scare the daylights out of you — and, hopefully, Detroit! The report is compiled on responses by 16 car companies (BMW, Chrysler, Ford, General Motors, Honda, Hyundai, Jaguar Land Rover, Mazda, Mercedes-Benz, Mitsubishi, Nissan, Porsche, Subaru, Toyota, Volkswagen (with Audi), and Volvo — hmm: one that didn’t respond was Tesla, which I suspect [just a hunch] really has paid attention to this issue because of its techno leadership) to letters Markey sent in late 2013. Here are the damning highlights from his report:

“1. Nearly 100% of cars on the market include wireless technologies that could pose vulnerabilities to hacking or privacy intrusions.

2. Most automobile manufacturers were unaware of or unable to report on past hacking incidents.

3. Security measures to prevent remote access to vehicle electronics are inconsistent and haphazard across all automobile manufacturers, and many manufacturers did not seem to understand the questions posed by Senator Markey.

4. Only two automobile manufacturers were able to describe any capabilities to diagnose or meaningfully respond to an infiltration in real-time, and most say they rely on technologies that cannot be used for this purpose at all. (my emphasis)

5. Automobile manufacturers collect large amounts of data on driving history and vehicle performance.

6. A majority of automakers offer technologies that collect and wirelessly transmit driving history data to data centers, including third-party data centers, and most do not describe effective means to secure the data.

7. Manufacturers use personal vehicle data in various ways, often vaguely to “improve the customer experience” and usually involving third parties, and retention policies – how long they store information about drivers – vary considerably among manufacturers.

8. Customers are often not explicitly made aware of data collection and, when they are, they often cannot opt out without disabling valuable features, such as navigation.”

In short, the auto industry collects a lot of information about us, and doesn’t have a clue how to manage or protect it.

I’ve repeatedly warned before that one of the issues technologists don’t really understand and/or scoff at, is public fears about privacy and security. Based on my prior work in crisis management, that can be costly — or fatal.

This report should serve as a bit of electroshock therapy to get them (and here I’m referring not just to auto makers but all IoT technologists: it’s called guilt by association, and most people tend to confabulate fears, not discriminate between them. Unless everyone in IoT takes privacy and security seriously, everyone may suffer the result [see below]) to realize that it’s not OK, as one of the speakers at the Wearables + Things conference said, that “we’ll get to privacy and security later.” It’s got to be a priority from the get-go (more about this in a forthcoming post, where I’ll discuss the recent FTC report on the issue).

I’ve got enough to worry about behind the wheel, since the North American Deer Alliance is out to get me. Don’t make me worry about false tire pressure readings.


PS: there’s another important issue here that may be obscured: the very connectedness that is such an important aspect of the IoT. Remember that the researchers spoofed the T.P.M.S. system not through a frontal assault, but by attacking the roadside assistance system? It’s like the way Target’s computers were hacked via a small company doing HVAC maintenance. Moral of the story? No IoT system is safe unless all the ones linking to it are safe.  For want of a nail … the kingdom was lost!

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