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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Management Challenge: Lifeguards in the IoT Data Lake

In their Harvard Business Review November cover story, How Smart, Connected Products Are Transforming Competition, PTC CEO Jim Heppelmann and Professor Michael Porter make a critical strategic point about the Internet of Things that’s obscured by just focusing on IoT technology: “…What makes smart, connected products fundamentally different is not the internet, but the changing nature of the “things.”

In the past, “things” were largely inscrutable. We couldn’t peer inside massive assembly line machinery or inside cars once they left the factory, forcing companies to base much of both strategy and daily operations on inferences about these things and their behavior from limited data (data which was also often gathered only after the fact).

Now that lack of information is being removed. The Internet of Things creates two unprecedented opportunities regarding data about things:

  • data will be available instantly, as it is generated by the things
  • it can also be shared instantly by everyone who needs it.

This real-time knowledge of things presents both real opportunities and significant management challenges.

Each opportunity carries with it the challenge of crafting new policies on how to manage access to the vast new amounts of data and the forms in which it can be accessed.

For example: with the Internet of Things we will be able to bring about optimal manufacturing efficiency as well as unprecedented integration of supply chains and distribution networks. Why? Because we will now be able to “see” inside assembly line machinery, and the various parts of the assembly line will be able to automatically regulate each other without human intervention (M2M) to optimize each other’s efficiency, and/or workers will be able to fine-tune their operation based on this data.

Equally important, because of the second new opportunity, the exact same assembly line data can also be shared in real time with supply chain and distribution network partners. Each of them can use the data to trigger their own processes to optimize their efficiency and integration with the factory and its production schedule.

But that possibility also creates a challenge for management.

When data was hard to get, limited in scope, and largely gathered historically rather than in the moment, what data was available flowed in a linear, top-down fashion. Senior management had first access, then they passed on to individual departments only what they decided was relevant. Departments had no chance to simultaneously examine the raw data and have round-table discussions of its significance and improve decision-making. Everything was sequential. Relevant real-time data that they could use to do their jobs better almost never reached workers on the factory floor.

That all potentially changes with the IoT – but will it, or will the old tight control of data remain?

Managers must learn to ask a new question that’s so contrary to old top-down control of information: who else can use this data?

To answer that question they will have to consider the concept of a “data lake” created by the IoT.

“In broad terms, data lakes are marketed as enterprise wide data management platforms for analyzing disparate sources of data in its native format,” Nick Heudecker, research director at Gartner, says. “The idea is simple: instead of placing data in a purpose-built data store, you move it into a data lake in its original format. This eliminates the upfront costs of data ingestion, like transformation. Once data is placed into the lake, it’s available for analysis by everyone in the organization.”

Essentially, data that has been collected and stored in a data lake repository remains in the state it was gathered and is available to anyone, versus being structured, tagged with metadata, and having limited access.

That is a critical distinction and can make the data far more valuable, because the volume and variety will allow more cross-fertilization and serendipitous discovery.

At the same time, it’s also possible to “drown” in so much data, so C-level management must create new, deft policies – to serve as lifeguards, as it were. They must govern data lake access if we are to, on one hand, avoid drowning due to the sheer volume of data, and, on the other, to capitalize on its full value:

  • Senior management must resist the temptation to analyze the data first and then pass on only what they deem of value. They too will have a crack at the analysis, but the value of real-time data is getting it when it can still be acted on in the moment, rather than just in historical analyses (BTW, that’s not to say historical perspective won’t have value going forward: it will still provide valuable perspective).
  • There will need to be limits to data access, but they must be commonsense ones. For example, production line workers won’t need access to marketing data, just real-time data from the factory floor.
  • Perhaps most important, access shouldn’t be limited based on pre-conceptions of what might be relevant to a given function or department. For example, a prototype vending machine uses Near Field Communication to learn customers’ preferences over time, then offers them special deals based on those choices. However, by thinking inclusively about data from the machine, rather than just limiting access to the marketing department, the company shared the real-time information with its distribution network, so trucks were automatically rerouted to resupply machines that were running low due to factors such as summer heat.
  • Similarly, they will have to relax arbitrary boundaries between departments to encourage mutually-beneficial collaboration. When multiple departments not only share but also get to discuss the same data set, undoubtedly synergies will emerge among them (such as the vending machine ones) that no one department could have discovered on its own.
  • They will need to challenge their analytics software suppliers to create new software and dashboards specifically designed to make such a wide range of data easily digested and actionable.

Make no mistake about it: the simple creation of vast data lakes won’t automatically cure companies’ varied problems. But C-level managers who realize that if they are willing to give up control over data flow, real-time sharing of real-time data can create possibilities that were impossible to visualize in the past, will make data lakes safe, navigable – and profitable.

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I’ll be on SAP Radio Again Today: the IoT and Big Data

I’ll be on SAP’s “Coffee Breaks With Game Changers” radio again today, live @ 2 EST, appearing again with SAP’s David Jonker, again talking about the IoT and Big Data.  This time I plan to speak about:

  • Integrating real-time and historic data in decision-making:  in the past, it was so hard to glean real-time operating data that we had to operate on the basis of inferring about how to manage the future based on analysis of past data.  Now we have a more difficult challenge: learn to balance past and real-time data.
  • Sharing data in real-time: In the past, data trickled down from top management and might (or might not) eventually get to operators on the shop floor.  Now, everyone can get immediate access to it. Will senior managers continue to be the gatekeepers, or will everyone have real-time access to the data that might allow them to do their jobs more effectively (for example, fine-tuning production processes).

  • Revolutionizing decision-making: Decision-making will also change, because of everyone being able to have simultaneous access to data. Does it really make sense any more for sequential decision-making by various siloed departments when they might all benefit by making the decisions simultaneously and collaboratively, based on the data?

Tune in!

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My #IoT predictions for 2015

I was on a live edition of “Coffee Break With Game-Changers” a few hours ago with panelists Sherryanne Meyer of Air Products and Chemicals and Sven Denecken of SAP, talking about tech projections for 2015.

Here’s what I said about my prognostications:

“I predict that 2015 will be the year that the Internet of Things penetrates consumer consciousness — because of the Apple Watch. The watch will unite both health and smart home apps and devices, and that will mean you’ll be able to access all that usability just by looking at your watch, without having to fumble for your phone and open a specific app.

If Apple chooses to share the watch’s API on the IFTTT – If This Then That — site, the Apple phone’s adoption – and usability — will go into warp speed. We won’t have to wait for Apple or developers to come up with novel ways of using the phone and the related devices — makers and just plain folks using IFTTT will contribute their own “recipes” linking them. This “democratization of data” is one of the most powerful – and under-appreciated – aspects of the IoT. In fact, Sherryanne, I think one of the most interesting IoT strategy questions for business is going to be that we now have the ability to share real time data with everyone in the company who needs it – and even with supply chain and distribution networks – and we’ll start to see some discussion of how we’ll have to change management practices to capitalize on this this instant ability to share.

(Sven will be interested in this one) In 2015, the IoT is also going to speed the development of fog computing, where the vast quantities of data generated by the IoT will mean a switch to processing data “at the edge,” and only passing on relevant data to the cloud, rather than overwhelming it with data – most of which is irrelevant.

In 2015 the IoT is also going to become more of a factor in the manufacturing world. The success of GE’s Durathon battery plant and German “Industry 4.0” manufacturers such as Siemans will mean that more companies will develop incremental IoT strategies, where they’ll begin to implement things such as sensors on the assembly line to allow real-time adjustments, then build on that familiarity with the IoT to eventually bring about revolutionary changes in every aspect of their operations.

2015 will also be the year when we really get serious about IoT security and privacy, driven by the increasing public concern about the erosion of privacy. I predict that if anything can hold back the IoT at this point, it will be failure to take privacy and security seriously. The public trust is extremely fragile: if even some fledgling startup is responsible for a privacy breach, the public will tend to tar the entire industry with the same brush, and that could be disastrous for all IoT firms. Look for the FTC to start scrutinizing IoT claims and levying more fines for insufficient security.”

What’s your take on the year ahead? Would love your comments!

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Is GE the future of manufacturing? IoT + nanotech + 3D-printing

The specific impetus for this post was an article in The Boston Globe about heart stents that fit perfectly because they’re 3-D printed individuallly for each patient.

GE jet engine 3-D-printed fuel nozzle

That prompted me to think of how manufacturing may change when three of my favorite technologies — nanotech, 3-D printing and the Internet of Things — are fully mature and synergies begin (as I’m sure they will) to emerge between the three.

I’m convinced we’ll see an unprecedented combination of:

  • waste elimination: 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.
  • as with the stents, 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.

Guess what?  The same company is in on the cutting edge of all three: General Electric (no, I’m not on their payroll, despite all my fawning attention to them!):

  • Their Industrial Internet IoT initiative is resulting in dramatic changes to their products, with built-in sensors that relay data constantly to GE and the customer about the product’s current status, allowing predictive maintenance practices that cuts repair costs, optimizing the device’s performance for more economical operations, and even allowing GE to switch from selling products to leasing them, with the lease price determined dynamically using factors such as how many hours the products are actually used.  Not only that, but they practice what they preach, with 10,000 sensors on the assembly line at their Durathon battery plant in Schenectady, plus sensors in the batteries themselves, allowing managers to roam the plant with an iPad to get instant readings on the assembly line’s real-time operation, to fine-tune the processes, and to be able to spot defective batteries while they are still in production, so that 100% of the batteries shipped will work.
    They’re also able to push products out the door more rapidly and updating them quicker based on the huge volumes of data they gather from sensors built into the products: “… G.E. is adopting practices like releasing stripped-down products quickly, monitoring usage and rapidly changing designs depending on how things are used by customers. These approaches follow the ‘lean start-up’ style at many software-intensive Internet companies. “’We’re getting these offerings done in three, six, nine months,’ he [William Ruh] said. ‘It used to take three years.’”
  • They’ve made a major commitment to 3-D printing, with 100,000 3-D printed parts scheduled to be built into their precision LEAP jet engines — a big deal, since there’s not a great deal of fault tolerance in something that may plunge to the earth if it malfunctions! As Bloomberg reported, “The finished product is stronger and lighter than those made on the assembly line and can withstand the extreme temperatures (up to 2,400F) inside an engine.”  They’re making major investments to boost the 3-D printers’ capacity and speed.  Oh, and did I mention their precedent-setting contest to crowd-source the invention of a 3-D printed engine mount?
  • They’re also partnering with New York State on perhaps the most visionary technology of all, nanotech, which manipulates materials on the molecular level. GE will focus on cheap silicon carbide wafers, which beat silicon chips in terms of efficiency and power, leading to smaller and lighter devices.

GE is the only member of the original Dow-Jones Index (in 1884) that still exists. As I’ve said before, I’m astounded that they not only get it about IoT technology, but also the new management practices such as sharing data that will be required to fully capitalize on it.

Thomas A. Edison is alive and well!

I’ll be on “Game Changer” Radio Today @ 3 EST Talking About IoT

Huzzah!  I’ll be a guest on Bonnie Graham’s “Coffee Break With Game Changers” show live, today @ 3 PM to discuss the Internet of Things. SAP Radio

Other guests will include David Jonker, sr. director of Big Data Initiatives at SAP, and Ira Berk, vice-president of Solutions Go-to-market at SAP, who has global responsibility for the IoT infrastructure and middleware portfolio.

Among other topics that I hope to get to during the discussion:

  • The “Collective Blindness” meme that I raised recently — and how the IoT removes it.
  • The difficult shift companies will need to make from past practices, where information was a zero-sum game, where hoarding information led to profit, to one where sharing information is the key. Who else can use this information?
  • How the IoT can bring about an unprecedented era of “Precision Manufacturing,” which will not only optimize assembly line efficiency and eliminate waste, but also integrate the supply chain and distribution network.
  • The sheer quantity of data with the IoT threatens to overwhelm us. As much as possible, we need to migrate to “fog computing,” where as much data as possible is processed at the edge, with only the most relevant data passing to the cloud (given the SAP guys’ titles, I assume this will be of big interest to them.
  • The rise of IFTTT.com, which means device manufacturers don’t have to come up with every great way to use their devices: use open standards, just publish the APIs to IFTTT, and let the crowd create creative “recipes” to use the devices.
  • Safety and security aren’t the other guy’s problem: EVERY device manufacturer must build in robust security and privacy protections from the beginning. Lack of public trust can undermine everyone in the field.
  • We can cut the cost of seniors’ care and improve their well being, through “smart aging,” which brings together Quantified Self fitness devices that improve their care and make health care a doctor-patient partnership, and “smart home” devices that automate home functions and make them easier to manage.

Hope you can listen in.  The show will be archived if you can’t make it for the live broadcast .

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Live Blogging from IoT Global Summit

I’ll be live-blogging for the next two days from the 2nd Internet of Things Global Summit.

  • Edith Ramirez, FTC chair:
    • potential for astounding benefits to society, transforming every activity
    • risks: very technology that allows this can also gather info for companies and your next employer
    • possible consumer loss of confidence in connected devices if they don’t think privacy w
    • 3 challenges:
      • adverse uses
      • security of the data
      • collection of the data
    • key steps companies should take:
      • security front and center
      • deidentify data
      • transparent policies
    • data will provide “startlingly complete pictures of us” — sensors can already identify our moods, even progression of neurological diseases
    • how will the data be used? will TV habits be shared with potential employers? Will it paint picture of you that others will see, but you won’t
    • will it exacerbate current socio-economic disparities?
    • potential for data breaches such as Target grows as more data is collected
    • FTC found some companies don’t take even most basic protections. Small size and cheap cost of some sensors may inhibit data protections
    • steps:
      • build security in from beginning
      • security risk assessment
      • test security measures before launch
      • implement defense and depth approach
      • encryption, especially for health data.
    • FTC action against TrendNet
    • follow principle of “data minimization,” only what’s needed, and dispose of it afterwards.
  • she’s skeptical of belief that there should be no limits on collection of data (because of possible benefits)
    • de-identified data: need dual approach — commit to not re-identify data
    • clear and simple notice to consumers about possible use of data.
    • Apple touting that it doesn’t sell data from Health App — critical to building consumer trust
    • transparency: major FTC priority. FTC review of mobile apps showed broad and vague standards on data collection & use.
  • Ilkka Lakaniemi, chair, FIWARE Future Internet PPP, EU perspective on IoT:
    • lot easier to start IoT businesses in Silicon Valley because of redundant regulations in EU
    • Open Standard Platform + Sustainable Innovation Ecosystem. “Synergy Platform”
  • Mark Bartolomeo,   vp of integrated solutions, Verizon:
    • Bakken Shale area visit: “landscape of IoT” solutions — pipeline monitoring, water monitoring, etc.
    • concerned about rapid urbanization: 30% of city congestion caused by drivers looking for parking. $120B wasted in time and fuel yearly.
    • cars: “seamless nodes” of system.
    • market drivers & barriers:
      • increased operational efficiency, new revenue streams, better service, comply with regulators, build competitive edge
      • fragmented ecosystem, complex development, significant back end obstacles
    • they want integrated systems.
    • need to remove barriers: aging infrastructure, congestion, public safety, economics
    • remove complexity
    • economies of scale: common services
    • trend to car sharing, smart grid
    • yea: highlighting intellistreets — one of my 1st fav IoT devices!!
    • Verizon working primarily on parking & traffic congestion on the East Coast, and water management in CA.

Smart Cities:

  • Nigel Cameron: nation-state receding, cities and corporations on ascendency
  • Sokwoo Rhee, NIST: Cyber-Physical Systems — emphasis on systems dynamics, data fed back into system, makes it autonomous.  Did Smart America Challenge with White House. Fragmentation on device level. Demonstrate tangible effects through collaborations. Examples: health care systems, transactive energy management, smart emergency response, water distribution, air quality. 24 projects.  Round Two is application of the projects to actual cities. Now 26 teams.
  • Joseph Bradley, VP, IoT Practice, Cisco Consulting: value isn’t in the devices, but the connections. Intersection of people, data, process, and things. Increase City of Nice’s parking revenue 40-60% without raising taxes through smart parking. They project $19 trillion in value over 10 years from combo of public and private innovations. Smart street lighting: reduces crime, property values increase, free wi-fi from the connected street lights. Barcelona is Exhibit A for benefits. Need: comprehensive strategy (privacy is a contextual issue: depends on the benefits you receive), scalability, apps, data analytics, transparency, powerful network foundation, IoT catalyst for breaking down silos, IoT must address people and process.
  • Ron Sege, chair and ceo of Echelon Corp: got started with smart buildings, 25 yrs. old. Why now with IoT: ubiquitous communications, low cost, hyper-competition, cloud. They do outdoor & indoor lighting and building systems. Challenges: move to one infrastructure/multiple use cases, will IT learn about OT & visa-versa?, reliability: critical infrastructure can’t fail & must respond instantly.
  • Christopher Wolf, Future of Privacy Forum: flexible, use-based privacy standards. Industry-wide approach to privacy: auto industry last week told NISTA about uniform privacy standards for connected cars (neat: will have to blog that…).
  • Peter Marx, chief innovation officer, City of LA:  big program to reduce street lights with LEDs: changed whole look of city at night & saves lot of money. 6 rail lines being built there. Adding smart meters for water & power. EV chargers on street lights. Held hackathon for young people to come up with ideas to improve city. Procurement cycles are sooo arcane that he suggests entrepreneurs don’t do business with city — he just tries to enable them.

Outside the City:

  • Darrin Mylet, Adaptrum: Using “TV white space spectrum” in non-urban areas. Spectrum access critical:need mix of spectrum types. Where do we need spectrum? Most need in non-line-of-sight areas such as trees, etc. Examples: not only rural, but also some urban areas (San Jose); Singapore; Africa; redwood forests;
  • Arturo Kuigami, World Bank: examples in developing nations: (he’s from Peru); most of global migration is to smaller cities; look at cities as ecosystems; “maker movement” is important — different business models: they partnered with Intel and MIT on “FabLabs” in Barcelona this year. MoMo — water access point monitoring in Tanzania.  Miroculus: created by a global ad hoc team — cheap way to make cancer diagnosis: have identified 3-4 types of cancers it can diagnose. Spirometer to measure COPD, made by a 15-year old! “IoT can be a global level playing field.”
  • Chris Rezendes, INEX Advisors: Profitable sustainability: by instrumenting the physical world, we can create huge opportunities for a wide range of people outside our companies. Focusing on doing a better job of instrumenting and monitoring our groundwater supplies: very little being done in SW US right now (INEX investing in a startup that is starting this monitoring). If we have better data on groundwater, we can do a better job of managing it. “Embrace complexity upfront” to be successful.
  • Shudong Chen, Chinese Academy of Sciences: talking about the Chinese food security crisis because of milk production without a food production license.  Government launched “Wuxi Food Science & Technology Park.”

Smart Homes:

  • Tobin Richardson, Zigbee Alliance: critical role of open, global standards. Zigbee LCD lights now down to $15.
  • Cees Links, GreenPeak Technologies: Leader in Zigbee-based smart home devices. Smart home waay more complex than wi-fi.  1m chips a week, vs. 1 million for whole year of 2011. “Not scratching the surface.” Small data — many small packets.
  • Todd Green, CEO PubNub: data stream network.
  • no killer app for the smart home..  Controlling by your phone not really that great a method.
  • FTC agrees with me: a few adverse stories (TrendNet baby cam example) can be really bad for an industry in its infancy.
  • always hole in security. For example, you can tell if no one’s home because volume of wi-fi data drops.W
  • FTC: consumer ed critical part of their work. Working now on best practices for home data protection.
  • mitigation after a security breach? Always be open, communicate (but most hunker down!).

DAY TWO

Beyond Cost Savings: Forging a Path to Revenue Generation

  • Eric Openshaw: (had tech problems during his preso: very important one — check the Deloitte The Internet of Things white paper for details) cost savings through IoT not enough for sustainable advantage: need to produce new revenue to do that. Defined ecosystem shaping up, which creates clarity, breaks down silos.
    • areas: smart grid, health care, home automation, cars, industrial automation
    • study the GE jet model for health care: what if doctors were paid to keep us healthy.
    • need comprehensive understanding of the change issues
    • be very specific: singular asset class, etc. — so you get early victories
    • companies will have overarching, finite roadmap
    • security & privacy dichotomy: differentiate between personal health care data and data from your washing machine. Most of us will share all sorts of information if there’s something in return
    • get focused on customer and product life cycle — that’s where the money will be. Focus on operating metric level. This is most far-reaching tech change he’s seen.

Managing Spectrum Needs

  • Julius Knapp, Chief, FCC Office of Engineering & Technology: new opportunity to combine licensed and unlicensed space. Described a number of FCC actions to reconsider role of various types of spectrum. “Hard to predict I0T’s long-term spectrum needs” because industry is new: they’ll watch developments in the field.
  • Prof. H. Nwana, exec. director of Dynamic Spectrum Alliance: most spectrum usually not used in most places at most time.  His group working to use changes to spectrum to end digital divide: (used incredible map showing how much of world, including US, China, India, W. Europe, could be fitted into Africa).
  • Carla Rath, VP for Wireless Policy, Verizon: “in my world, the network is assumed.”  Need for more spectrum — because of growth in mobile demand. Praises US govt. for trying to make more spectrum available. Don’t want to pigeonhole IoT in certain part of spectrum: allow flexibility.  Tension between flexibility and desire for global standards when it comes to IoT.
  • Philip Marnick, group director of spectrum policy, Ofcom UK:  no single solution.  Market determines best use. Some applications become critical (public safety, etc.) — must make sure people using those are aware of chance of interference.
  • Hazem Moakkit, vp of spectrum development for 03b (UK satellite provider for underserved areas of developing world): “digital divide widened by IoT if all are not on board.” Fair allocation of spectrum vital.
  • interesting question: referred to executive of a major farm equipment manufacturer whose products are now sensor-laden (must be John Deere…) and is frustrated because the equipment won’t work in countries such as Germany due to different bands.

Architecting the IoT: Sensing, Networking & Analytics: 

  • Tom Davenport: IoT highly unpredictable. “Great things about standards is there’s so many to choose from” — LOL.  Will IoT revolution be more top down or bottom up?
  • Gary Butler, CEO, Camgian: announcing an edge system for IoT. Driven by sensor info. Need new networking architecture to combine sensing and analytics to optimize business processes, manage risk. Systems now built from legacy equipment, not scalable. They’re announcing new platform: Egburt. Applicable to smart cities, retailing, ifrastructure (I’ll blog more about this soon!!). “Intelligence out of chaos.” Anomaly detection. Real-time analysis at the device level. Focus on edge computing. Must strengthen the ROI.
  • Xiaolin Lu, Texas Instruments fellow & director of IoT Lab: Working in wearables, smart manufacturing, smart cities, smart manufacturing, health care, automotive. TI claims it has all IoT building blocks: nodes, gateway/bridge or router/cloud.  Power needs are really critical, with real emphasis on energy harvesting from your body heat, vibration, etc. Challenges: sensing and data analytics, robust connectivity, power, security, complexity, consolidation of infrastructure and data. Big advocates for standards. They work on smart grid.
  • Steve Halliday, president, RAIN RFID: very involved in standards. 4 BILLION RFID tags shipped last year. Don’t always want IP devices. Power not an issue w/ RFID because they get their power from the reader. Think RFID will be underpinning of IoT for long time. Lot of confusion in many areas about IoT, especially in manufacturing.
  • Sky Mathews, IBM CTO: IBM was one of earliest in the field, with Smarter Planet. Lot of early ones were RFID. A variety of patterns emerging for where and how data is processed. What APIs do you want to expose to the world? “That’s where the real leaps of magnitude will occur” — so design that in from beginning.

‘People’ Side of the IoT: meeting consumer expectations:

  • Mark Eichorn, asst. director, Consumer Protection Bureau, FTC: companies that have made traditional appliances & now web-enable them aren’t always ready to deal with data theft. Security and privacy: a lot don’t have privacy policies at all. At their workshop, talk about people being able to hack your insulin readings.
  • Daniel Castro, sr. analyst, Center for Data Innovation: thinks that privacy issue has been misconstrued: what people really care about is keeping data from government intrusion. Can car be designed so a cop could pull it over automatically (wow: that’s a thought!). Chance for more liability with misuse of #IoT data.
  • Linda Sherry, director of national priorities, Consumer Action: “convenience, expectations and trust.” “What is the IoT doing beside working?” Connecting everything may disenfranchise those who aren’t connected. Need to register those who collect data – hmm. Hadn’t heard that one before. Even human rights risks, stalking, etc. — these issues must be thought about. Can algorithms really be trusted on issues such as insurance coverage? How do you define particularly sensitive personal data? “Hobbling the unconnected” when most are connected? “Saving consumers from themselves.” “Document the harms.” Make sure groups with less $ can really participate in multi-stakeholder negotiations.
  • Stephen Pattison, vp of public affairs, ARM Holdings: disagrees with Linda about slowing things down: we want to speed up IoT as instrument of transformation. We need business model for it. Talks about how smart phone didn’t explode until providers started subsidizing purchase. He suspects that one model might be that a company would provide you whole range of smart appliances in return for your data. “Getting data right matters.” “Freak events” drive concerns about data security & privacy: they generate concern and, sometimes, “heavy-handed” regulation.
    Industry must work together on framework for data that creates confidence by public. Concerns about data are holding back investment in the field. They’re working with AMD on a framework: consumers own their own data — must start with that (if they do, people will cooperate); not all data equally sensitive — need chain of custody to keep data anomyzed; security must be right at the edge; simplify terms and conditions.
    Sometimes thinks that, in talking about IoT, it’s like talking about cars in 1900, but we managed to create a set of standards that allowed it to grow: “rules of the road,” etc.
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Thermostats: yet another example why open standards win with #IoT

Despite my passion for all things Apple and the incredible functionality that comes from Tim Cook’s passion for integrating all parts of the ecosystem seamlessly (and, as I’ve noted in prior disclaimers, my part-time work at the Apple Store ..), I don’t think there’s any doubt when it comes to the Internet of Things that open standards win out.

That’s because they meet the test of my favorite Essential Truth, “who else can use this data?”

It goes back to my Data Dynamite book and my work with Vivek Kundra when he was opening up data in the District of Columbia before becoming the US CIO: when you share data, you empower end users and can go beyond your own developers’ talents and interests, to harvest others’ interests and developments.

opower_sHere’s a great example. Opower’s OpenStat API enables the electric  industry’s only open thermostat management platform. It allows any smart thermostat provider to participate in existing Opower-managed utility thermostat programs. It combines energy usage, billing, parcel and weather data to engage customers, drive measurable energy efficiency, and deliver reliable demand response.  It already has 95 partner utilities, 50 million (really? that sounds high to me…) homes in 35 states sharing data.

By contrast, Nest (which of course was created by Apple alums) had to create a specific API to allow sharing its data. 

This API is Nest’s answer to the Learning Thermostat’s lack of Z-Wave or ZigBee wireless communication. Nest came under fire from the CEDIA crowd when the Learning Thermostat launched since it wouldn’t work within even $100k home automation systems. The thermostat wasn’t friendly with others. It wouldn’t talk to other home automation products using the legacy home automation protocols. This API could change everything.

The jury’s still out — and it will really be interesting to see how many other companies decide to integrate with Apple’s new Health and Home apps. On one hand, a proliferation of standards just retards more creative API mashups, a la IFTTT (my heros!!). On the other, seamless integration and ease-of-use, the Apple hallmarks, could go a long way to ingraining the IoT into consumers’ daily lives.

What do you think?

 

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