Holy Clayton Christensen! Is Local Motors prototype for future of manufacturing?

In the latter stages of writing The Future Is Smart, I came across Local Motors, an amazing company that is not only an IoT innovator but also might pr0vide a model to revolutionize American manufacturing in general.

I’d read an article years ago about the company when it was locally-based, but since it was focused entirely on off-road & fast cars at the time (both of which leave me cold) I didn’t follow up.

Now it’s diversifying into a cute small urban shuttle device, the Olli, which is being produced at Local Motion’s Knoxville microfactory, taps IBM’s Watson, and which they label “the world’s first self-driving cognitive vehicle.” Very cool.

co-creation

The first of Local Motor’s revolutionary aspects is its design process, which it labels “co-creation” (AKA crowdsourcing — in fact founder/visionary John B. (Jay) Rogers, Jr. says he was inspired by the Jeff Howe book of the same name). It uses a SaaS platform, where the company posts design challenges, and then community members (some experts, some just enthusiasts) offer their ideas. Eventually, the community votes on which designs to actually produce:

“An active process where brands and their customers work together with solvers, designers, and engineers to accelerate product and technology development. We call this group our Community and proudly work to empower genius ideas and brilliant solutions from Community members across the globe.”

The participatory aspect even extends to the shop floor: buyers can opt to personally take part in the final assembly process (and designs are also easily customized after the sale as well).

The company has also provided consulting services on co-creation for organizations ranging from the US Army to Airbus. 

This is not unlike my “share data, don’t hoard it” IoT Essential Truth, which is also at the heart of my Circular Company vision: when you involve and empower a wide range of people, you can unleash creativity that even the most talented person can’t.

direct digital manufacturing

The second Local Motors innovation is use of creative technologies, especially 3D printing, in manufacturing, what they call “direct digital manufacturing (DDM).”  The process mimics what Siemens does at its “Factory of the Future,”  where complete digitalization gives them quality, precision, and the opportunity for mass customization:

“DDM creates significant unfair advantages: the ability to produce parts directly from a CAD file; elimination of investments in tooling; reduction in time lag between design and production and, best of all, elimination of penalties for redesigns — unlocking mass customization that was previously unobtainable.”

According to Chief Strategy Officer Justin Fishkin, the economies possible with the DDH approach means the Rally Fighter model was profitable after only the 60th one was built.

microfactories

I’ve written before about Ford’s River Rouge plant, the ne plus ultra of the first Industrial Age: iron ore went in one end of the 1 x 1.6 mile factory and Model Ts came out the other.

By contrast, Local Motors is building several supermarket-sized “microfactories” around the globe at a cost 1/100th of that for conventional car plants, which “..will also act as points of sale, or what Fishkin calls ‘experiential dealerships.’”

 


The jury’s still out on Local Motors (Rogers, for example, has come in for some scathing tell-all comments by former employees), but even if it isn’t a roaring success, it will have a lasting legacy for challenging such long-held assumptions about the entire design/build process. and for exploiting the full benefits of digitization.  It’s the essence of Christensen’s disruptive innovation.

We’ll be watching

 

Great Podcast Discussion of #IoT Strategy With Old Friend Jason Daniels

Right after I submitted my final manuscript for The Future is Smart I had a chance to spend an hour with old friend Jason Daniels (we collaborated on a series of “21st Century Homeland Security Tips You Won’t Hear From Officials” videos back when I was a homeland security theorist) on his “Studio @ 50 Oliver” podcast.

We covered just about every topic I hit in the book, with a heavy emphasis on the attitude shifts (“IoT Essential Truths” needed to really capitalize on the IoT and the bleeding-edge concept I introduce at the end of the book, the “Circular Corporation,” with departments and individuals (even including your supply chain, distribution network and customers, if you choose) in a continuous, circular management style revolving around a shared real-time IoT hub.  Hope you’ll enjoy it!

Liveblogging from Internet of Things Global Summit

Critical Infrastructure and IoT

Robert Metzger, Shareholder, Rogers Joseph O’Donnell 

  • a variety of constraints to direct government involvement in IoT
  • regulators: doesn’t trust private sector to do enough, but regulation tends to be prescriptive.
  • NIST can play critical role: standards and best practices, esp. on privacy and security.
  • Comparatively, any company knows more about potential and liabilities of IoT than any government body. Can lead to bewildering array of IoT regulations that can hamper the problem.
  • Business model problem: security expensive, may require more power, add less functionality, all of which run against incentive to get the service out at lowest price. Need selective regulation and minimum standards. Government should require minimum standards as part of its procurement. Government rarely willing to pay for this.
  • Pending US regulation shows constant tension between regulation and innovation.

             2017 IoT Summit

Gary Butler, CEO, Camgian 

  • Utah cities network embedding sensors.
  • Scalability and flexibility needed. Must be able to interface with constantly improving sensors.
  • Expensive to retrofit sensors on infrastructure.
  • From physical security perspective: cameras, etc. to provide real-time situational awareness. Beyond human surveillance. Add AI to augment human surveillance.
  • “Dealing with ‘data deluge.'”  Example of proliferation of drones. NIST might help with developing standards for this.
  • Battery systems: reducing power consumption & creating energy-dense batteries. Government could help. Government could also be a leader in adoption.

 

Cyber-Criminality, Security and Risk in an IoT World

John Carlin, Chair, Cybersecurity & Technology Program, Aspen Institute

  • Social media involved in most cyberwar attacks & most perps under 21.  They become linked solely by social media.
  • offensive threats far outstrip defenses when it comes to data
  • now we’re connecting billions of things, very vulnerable. Add in driverless cars & threat even greater. Examples: non-encrypted data from pacemakers, and the WIRED Jeep demo.

Belisario Contreras, Cyber Security Program Manager, Organization of American States

  • must think globally.
  • criminals have all the time to prepare, we must respond within minutes.
  • comprehensive approach: broad policy framework in 6 Latin American countries.

Samia Melhem, Global Lead, Digital Development, World Bank

  • projects: she works on telecommunications and transportation investing in government infrastructure in these areas. Most of these governments have been handicapped by lack of funding. Need expert data integrators. Integrating cybersecurity.

Stephen Pattison, VP Public Affairs, ARM

  • (yikes, never thought about this!) cyberterrorist hacks self-driving car & drives it into a crowds.
  • many cyber-engineers who might go to dark side — why hasn’t this been studied?
  • could we get to point where IoT-devices are certified secure (but threats continually evolve. Upgradeability is critical.
  • do we need a whistleblower protection?
  • “big data starts with little data”

Session 4: Key Policy Considerations for Building the Cars of Tomorrow – What do Industry Stakeholders Want from Policymakers?

Ken DiPrima, AVP New Product Development, IoT Solutions, AT&T

  • 4-level security approach: emphasis on end-point, locked-down connectivity through SIM, application level …
  • deep in 5-G: how do you leverage it, esp. for cars?
  • connecting 25+ of auto OEMs. Lot of trials.

Rob Yates, Co-President, Lemay Yates Associates

  • massive increase in connectivity. What do you do with all the data? Will require massive infrastructure increase.

Michelle Avary, Executive Board, FASTR, VP Automotive, Aeris

  • about 1 Gig of data per car with present cars. Up to 30 with a lot of streaming.
  • don’t need connectivity for self-driving car: but why not have connectivity? Also important f0r the vehicle to know and communicate its physical state. Machine learning needs data to progress.
  • people won’t buy vehicles when they are really autonomous — economics won’t support it, will move to mobility as a service.

Paul Scullion, Senior Manager, Vehicle Safety and Connected Automation, Global Automakers

  • emphasis on connected cars, how it might affect ownership patterns.
  • regulatory process slow, but a lot of action on state level. “fear and uncertainty” on state level. Balance of safety and innovation.

Steven Bayless, Regulatory Affairs & Public Policy, Intelligent Transportation Society of America

  • issues: for example, can you get traffic signals to change based on data from cars?
  • car industry doesn’t have lot of experience with collaborative issues.

How Are Smart Cities Being Developed and Leveraged for the Citizen?

Sokwoo Rhee, Associate Director of Cyber-Physical Systems Program, National Institute of Standards and Technology (NIST)

  • NIST GCTC Approach: Smart and Secure Cities. Partnered with Homeland Security to bring in cybersecurity & privacy at the basis of smart city efforts “Smart and Secure Cities and Communities Challenge”

Bob Bennett, Chief Innovation Officer, City of Kansas, MO

  • fusing “silos of awesomeness.”
  • 85% of data you need for smart cities already available.
  • “don’t blow up silos, just put windows on them.”
  • downtown is 53 smartest blocks in US
  • can now do predictive maintenance on roads
  • Prospect Ave.: neighborhood with worst problems. Major priority.
  • great program involving multiple data sources, to predict and take care of potholes — not only predictive maintenance but also use a new pothole mix that can last 12 years 
  • 122 common factors all cities doing smart cities look at!
  • cities have money for all sorts of previously allocated issues — need to get the city manager, not mayor, to deal with it
  • privacy and security: their private-sector partner has great resoures, complemented by the city’s own staff.

Mike Zeto, AVP General Manager, IoT Solutions, AT&T

  • THE AT&T Smart Cities guy. 
  • creating services to facilitate smart cities.
  • energy and utilities are major focus in scaling smart cities, including capital funding. AT&T Digital Infrastructure (done with GE) “iPhone for cities.”
  • work in Miami-Dade that improved public safety, especially in public housing. Similar project in Atlanta.
  • privacy and security: their resources in both have been one of their strengths from the beginning.

Greg Toth, Founder, Internet of Things DC

  • security issues as big as ever
  • smart city collaboration booming
  • smart home stagnating because early adopter boom over, value not sure
  • Quantified-Self devices not really taking hold (yours truly was one of very few attendees who said they were still using their devices — you’d have to tear my Apple Watch off).
  • community involvement greater than ever
  • looming problem of maintaining network of sensors as they age
  • privacy & security: privacy and security aren’t top priorities for most startups.

DAY TWO:

IoT TECH TALKS

  • Dominik Schiener, Co-Founder , IOTA speaking on blockchain
    • working with IoT version of blockchain for IoT — big feature is it is scaleable
    • why do we need it?  Data sets shared among all parties. Each can verify the datasets of other participants. Datasets that have been tampered are excluded.
    • Creates immutable single source of truth.
    • It also facilitates payments, esp. micropayments (even machine to machine)
    • Allows smart contracts. Fully transparent. Smart and trustless escrow.
    • Facilitates “machine economy”
    • Toward “smart decentralization”
    • Use cases:
      • secure car data — VW. Can’t be faked.
      • Pan-European charging stations for EVs. “Give machines wallets”
      • Supply chain tracking — probably 1st area to really adopt blockchain
      • Data marketplace — buy and sell data securely (consumers can become pro-sumers, selling their personal data).
      • audit trail. https://audit-trail.tangle.works
  • DJ Saul, CMO & Managing Director, iStrategyLabs IoT, AI and Augmented Reality
    • focusing on marketing uses.

Raising the bar for federal IoT Security – ‘The Internet of Things Cybersecurity Improvement Act’

  • Jim Langevin, Congressman, US House of Representatives
    • very real threat with IoT
    • technology outpacing the law
    • far too many manufacturers don’t make security a priority. Are customers aware?
    • consumers have right to know about protections (or lack thereof)
    • “failure is not an option”
    • need rigorous testing
  • Beau Woods, Deputy Director, Cyber Statecraft Initiative, Atlantic Council
    • intersection of cybersecurity & human condition
    • dependence on connected devices growing faster than our ability to regulate it
    • UL developing certification for medical devices
    • traceability for car parts
  • John Marinho, Vice President Cybersecurity and Technology, CTIA
    • industry constantly evolving global standards — US can’t be isolated.
    • cybersecurity with IoT must be 24/7. CTIA created an IoT working group, meets every two weeks online.
    • believe in public/private partnerships, rather than just regulatory.

Session 9: Meeting the Short and Long-Term Connectivity Requirements of IoT – Approaches and Technologies

  •  Andreas Geiss, Head of Unit ‘Spectrum Policy’, DG CONNECT, European Commission
    • freeing up a lot of spectrum, service neutral
    • unlicensed spectrum, esp. for short-range devices. New frequency bands. New medical device bands. 
    • trying to work with regulators globally to allow for globally-usable devices.
  • Geoff Mulligan, Chairman, LoRa Alliance; Former Presidential Innovation Fellow, The White House
    • wireless tradeoffs: choose two — low power/long distance/high speed.
    • not licensed vs. unlicensed spectrum. Mix of many options, based on open standards, all based on TCP/IP
    • LPWANs:
      • low power wide area networks
      • battery operated
      • long range
      • low cost
      • couple well with satellite networks
    • LoRaWAN
      • LPWAN based on LoRa Radio
      • unlicensed band
      • open standards base
      • openly available
      • open business model
      • low capex and opex could covered entire country for $120M in South Korea
      • IoT is evolutionary, not revolutionary — don’t want to separate it from other aspects of Internet
  • Jeffrey Yan, Director, Technology Policy, Microsoft
    • at Microsoft they see it as critical for a wide range of global issues, including agriculture.
  • Charity Weeden, Senior Director of Policy, Satellite Industry Association
    • IoT critical during disasters
    • total architecture needs to be seamless, everywhere.
  • Andrew Hudson, Head of Technology Policy, GSMA
    • must have secure, scalable networks

Session 10: IoT Data-Ownership and Licencing – Who Owns the Data?

  • Stacey Gray, Policy Lead IoT, Future Privacy Forum 
    • consumer privacy right place to begin.
    • need “rights based” approach to IoT data
    • at this point, have to show y0u have been actually harmed by release of data before you can sue.
  • Patrick Parodi, Founder, The Wireless Registry
    • focus on identity
    • who owns SSID identities? How do you create an identity for things?
  • Mark Eichorn, Assistant Director, Division of Privacy and Identity Protection, Federal Trade Commission 
    • cases involving lead generators for payday loan. Reselling personal financial info.
  • Susan Allen, Attorney-Advisor, Office of Policy and International Affairs, United States Patent & Trademark Office 
    • focusing on copyright.
    • stakeholders have different rights based on roles
  • Vince Jesaitis, Director, US Public Affairs, ARM
    • who owns data depends on what it is. Health data very tough standards. Financial data much more loose.
    • data shouldn’t be treated differently if it comes from a phone or a browser.
    • industrial side: autonomous vehicle data pretty well regulated.  Pending legislation dealing with smart cities emphasis open data.

OtoSense: the next level in sound-based IoT

It sounds (pardon the pun) as if the IoT may really be taking off as an important diagnostic repair tool.

I wrote a while ago about the Auguscope, which represents a great way to begin an incremental approach to the IoT because it’s a hand-held device to monitor equipment’s sounds and diagnose possible problems based on abnormalities.

Now NPR reports on a local (Cambridge) firm, OtoSense, that is expanding on this concept on the software end. Its tagline is “First software platform turning real-time machine sounds and vibrations into actionable meaning at the edge.”

Love the platform’s origins: it grows out of founder Sebastien Christian’s research on deafness (as I wrote in my earlier post, I view suddenly being able to interpret things’ sounds as a variation on how the IoT eliminates the “Collective Blindness”  that I’ve used to describe our past inability to monitor things before the IoT’s advent):

“[Christian} … is a quantum physicist and neuroscientist who spent much of his career studying deaf children. He modeled how human hearing works. And then he realized, hey, I could use this model to help other deaf things, like, say, almost all machines.”

(aside: I see this as another important application of my favorite IoT question: learning to automatically ask “who else can use this data?” How does that apply to YOUR work? But I digress).

According to Technology Review, the company is concentrating primarily on analyzing car sounds from IoT detectors on the vehicle at this point (working with a number of car manufacturers) although they believe the concept can be applied to a wide range of sound-emitting machinery:

“… OtoSense is working with major automakers on software that could give cars their own sense of hearing to diagnose themselves before any problem gets too expensive. The technology could also help human-driven and automated vehicles stay safe, for example by listening for emergency sirens or sounds indicating road surface quality.

OtoSense has developed machine-learning software that can be trained to identify specific noises, including subtle changes in an engine or a vehicle’s brakes. French automaker PSA Group, owner of brands including Citroen and Peugeot, is testing a version of the software trained using thousands of sounds from its different vehicle models.

Under a project dubbed AudioHound, OtoSense has developed a prototype tablet app that a technician or even car owner could use to record audio for automated diagnosis, says Guillaume Catusseau, who works on vehicle noise in PSA’s R&D department.”

According to NPR, the company is working to apply the same approach to a wide range of other types of machines, from assembly lines to DIY drills. As always with IoT data, handling massive amounts of data will be a challenge, so they will emphasize edge processing.

OtoSense has a “design factory” on the site, where potential customers answer a variety of questions about the sounds they must monitor (such as whether the software will be used indoors or out, whether it is to detect anomalies, etc. that will allow the company to choose the appropriate version of the program.

TechCrunch did a great article on the concept, which underscores really making sound detection precise will take a lot of time and refinement, in part because of the fact that — guess what — sounds from a variety of sources are often mingled, so the relevant ones must be determined and isolated:

“We have loads of audio data, but lack critical labels. In the case of deep learning models, ‘black box’ problems make it hard to determine why an acoustical anomaly was flagged in the first place. We are still working the kinks out of real-time machine learning at the edge. And sounds often come packaged with more noise than signal, limiting the features that can be extracted from audio data.”

In part, as with other forms of pattern recognition such as voice, this is because it will require accumulating huge data files:

“Behind many of the greatest breakthroughs in machine learning lies a painstakingly assembled dataset.ImageNet for object recognition and things like the Linguistic Data Consortium and GOOG-411 in the case of speech recognition. But finding an adequate dataset to juxtapose the sound of a car-door shutting and a bedroom-door shutting is quite challenging.

“’Deep learning can do a lot if you build the model correctly, you just need a lot of machine data,’ says Scott Stephenson, CEO of Deepgram, a startup helping companies search through their audio data. ‘Speech recognition 15 years ago wasn’t that great without datasets.’

“Crowdsourced labeling of dogs and cats on Amazon Mechanical Turk is one thing. Collecting 100,000 sounds of ball bearings and labeling the loose ones is something entirely different.

“And while these problems plague even single-purpose acoustical classifiers, the holy grail of the space is a generalizable tool for identifying all sounds, not simply building a model to differentiate the sounds of those doors.

…”A lack of source separation can further complicate matters. This is one that even humans struggle with. If you’ve ever tried to pick out a single table conversation at a loud restaurant, you have an appreciation for how difficult it can be to make sense of overlapping sounds.

Bottom line: there’s still a lot of theoretical and product-specific testing that must be done before IoT-based sound detection will be an infallible diagnostic tool for predictive maintenance, but clearly there’s precedent for the concept, and the potential payoff are great!

 


LOL: as the NPR story pointed out, this science may owe its origins to two MIT grads of an earlier era, “Click” and “Clack” of Car Talk, who frequently got listeners to contribute their own hilarious descriptions of the sounds they heard from their malfunctioning cars.   BRTTTTphssssBRTTTT…..

A Vision for Dynamic and Lower-Cost Aging in Cities Through “SmartAging”

I’ve been giving a lot of thought recently about how my vision of I0T-based “SmartAging” through a combination of:

  • Quantified Self health apps and devices to improve seniors’ health and turn their health care into more of a partnership with their doctors
  • and smart home devices that would make it easier to manage their homes and “age in place” rather than being institutionalized

could meld with the exciting developments in smart city devices and strategy.  I believe the results could make seniors happier and healthier, reduce the burdens on city budgets of growing aging populations, and spur unprecedented creativity and innovation on these issues. Here’s my vision of how the two might come together. I’d welcome your thoughts on the concept!

 

A Vision for Dynamic and Lower-Cost Aging in Cities Through “SmartAging”

It’s clear business as usual in dealing with aging in America won’t work anymore.  10,000 baby boomers a day retire and draw Social Security. Between now and 2050, seniors will be the fastest growing segment of the population.  How can we stretch government programs and private resources so seniors won’t be sickly and live in abject poverty, yet millennials won’t be bankrupted either?

As someone in that category, this is of more than passing interest to me! 

I propose a new approach to aging in cities, marrying advanced but affordable personal technology, new ways of thinking about aging, and hybrid formal and ad hoc public-private partnerships, which can deal with at least part of the aging issue. Carving out some seniors from needing services through self-reliance and enhancing their well-being would allow focusing scarce resources on the most vulnerable remaining seniors. 

The approach is made possible not only by the plummeting cost and increasing power of personal technology but also the exciting new forms of collaboration it has made possible.

The proposal’s basis is the Internet of Things (IoT).  There is already a growing range of IoT wearable devices to track health indicators such as heart rates and promoting fitness activities, and IoT “smart home” devices controlling lighting, heat, and other systems. The framework visualized here would easily integrate these devices, but they can be expensive, so it is designed so seniors could benefit from the project without having to buy the dedicated devices.

This proposal does not attempt to be an all-encompassing solution to every issue of aging, but instead will create a robust, open platform that government agencies, companies, civic groups, and individuals can build upon to reduce burdens on individual seniors, improve their health and quality of life, and cut the cost of and need for some government services. Even better, the same platform and technologies can be used to enhance the lives of others throughout the life spectrum as well, increasing its value and versatility.

The proposal is for two complementary projects to create a basis for later, more ambitious one.

Each would be valuable in its own right and perhaps reach differing portions of the senior population. Combined, they would provide seniors and their families with a wealth of real-time information to improve health, mobility, and quality of life, while cutting their living costs and reducing social isolation.  The result would be a mutually-beneficial public-private partnerships and, one hopes, improve not only seniors’ lives, but also their feeling of connectedness to the broader community. Rather than treat seniors as passive recipients of services, it would empower them to be as self-reliant as possible given their varying circumstances. They would both be based on the Lifeline program in Massachusetts (and similar ones elsewhere) that give low-income residents basic Internet service at low cost.

Locally, Boston already has a record of achievement in internet-based services to connect seniors with others, starting with the simple and tremendously effective SnowCrew program that Joe Porcelli launched in the Jamaica Plain neighborhood. This later expanded nationwide into the NextDoor site and app, which could easily be used by participants in the program.

The first project would capitalize on the widespread popularity of the new digital “home assistants,” such as the Amazon Echo and Google Home.  One version of the Echo can be bought for as little as $49, with bulk buying also possible.  A critical advantage of these devices, rather than home monitoring devices specifically for seniors, is that they are mainstream, benefit from the “network effects” phenomenon that means each becomes more valuable as more are in use, and don’t stigmatize the users or shout I’M ELDERLY. A person who is in their 50s could buy one now, use it for routine household needs, and then add additional age-related functions (see below) as they age, amortizing the cost.

The most important thing to remember about these devices regarding aging is the fact that they are voice-activated, so they would be especially attractive to seniors who are tech-averse or simply unable to navigate complex devices. The user simply speaks a command to activate the device.

The Echo (one presumes a variation on the same theme will soon be the case with the “Home,” Apple’s forthcoming “Home Pod” and other devices that might enter the space in the future) gets its power from “skills,” or apps, that are developed by third-party developers. They give it the power, via voice, to deliver a wide range of content on every topic under the sun.  Several already released “skills” give an idea of how this might work:

  • Ask My Buddy helps users in an emergency. In an emergency, it can send phone calls or text messages to up to five contacts. A user would say, “Alexa, ask my buddy Bob to send help” and Bob would get an alert to check in on his friend.
  • Linked thermostats can raise or lower the temperature a precise amount, and lights can also be turned on or off or adjusted for specific needs.
  • Marvee can keep seniors in touch w/ their families and lessen social isolation.
  • The Fitbit skill allows the user who also has a Fitbit to trace their physical activity, encouraging fitness.

Again looking to Boston for precedent, related apps include the Children’s Hospital and Kids’ MD ones from Children’s Hospital. Imagine how helpful it could be if the gerontology departments of hospitals provided similar “skills” for seniors!

Most important to making this service work would be to capitalize on the growing number of city-based open-data programs that release a variety of important real-time data bases which independent developers mash up to create “skills”  such as real-time transit apps.  The author was a consultant to the District of Columbia in 2008 when it began this data-based “smart city” approach with the Apps for Democracy contest, which has spawned similar projects worldwide since then.  When real-time city data is released, the result is almost magic: individuals and groups see different value in the same data, and develop new services that use it in a variety of ways at no expense to taxpayers.

The key to this half of the pilot programs would be creating a working relationship with local Meetups such as those already created in various cities for Alexa programmers, which would facilitate the relationship) to stage one or more high-visibility hackathons. Programmers from major public and social service institutions serving seniors, colleges and universities, and others with an interest in the subject could come together to create “skills” based on the local public data feeds, to serve seniors’ needs, such as:

  • health
  • nutrition
  • mobility
  • city services
  • overcoming social isolation (one might ask how a technological program could help with this need. The City of Barcelona, generally acknowledged as the world’s “smartest” city, is circulating an RFP right now with that goal and already has a “smart” program for seniors who need immediate help to call for it) .

“Skills” are proliferating at a dizzying rate, and ones developed for one city can be easily adapted for localized use elsewhere.

Such a project would have no direct costs, but the city and/or a non-profit might negotiate lower bulk-buying rates for the devices, especially the l0wer price ($59 list) Amazon Dot, similar to the contract between the Japan Post Group, IBM, and Apple to buy 5 million iPads and equip them with senior-friendly apps from IBM which the Post Group would then furnish to Japanese seniors. Conceivably, the Dots bought this way might come preloaded with the localized and senior-friendly “skills.” 

The second component of a prototype SmartAging city program would make the wide range of local real-time location-based data available by various cities usable by cities joininh the 100+ cities worldwide who have joined the “Things Network” that create free citywide data networks specifically for Internet of Things use.

The concept uses technology called LoRaWAN: low-cost (the 10 units used in Amsterdam, each with a signal range of about 6 miles, only cost $12,000 total — much cheaper ones will be released soon), and were deployed and operative in less than a month!  The cost and difficulty of linking an entire city has plummeted as more cities join, and the global project is inherently collaborative.

With Things Network, entire cities would be converted into Internet of Things laboratories, empowering anyone (city agencies, companies, educational institutions, non-profits, individuals) to experiment with offering new services that would use the no-cost data sharing network.  In cities that already host Things Networks,  availability of the networks has spawned a wide range of novel local services.  For example, in Dunblane, Scotland, the team is developing a ThingsNetwork- based alarming system for people with dementia.  Even better, as the rapid spread of citywide open data programs and resulting open source apps to capitalize on them has illustrated, a neat app or service created in one city could easily be copied and enhanced elsewhere — virtuous imitation!

The critical component of the prototype programs would be to hold one or more hackathons once the network was in place.  The same range of participants would be invited, and since the Things Network could also serve a wide range of other public/private uses for all age groups and demographics, more developers and subject matter experts might participate in the hackathon, increasing the chances of more robust and multi-purpose applications resulting.

These citywide networks could eventually become the heart of ambitious two-way services for seniors based on real-time data, similar to those in Bolsano, Italy

The Internet of Things and smart cities will become widespread soon simply because of lowering costs and greater versatility, whether this prototype project for seniors happens or not. The suggestions above would make sure that the IoT serves the public interest by harnessing IoT data to improve seniors’ health, reduce their social isolation, and make them more self-sufficient. It will reduce the burden on traditional government services to seniors while unlocking creative new services we can’t even visualize today to enhance the aging process.

Libelium: flexibility a key strategy for IoT startups

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

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

Libelium CEO Alicia Asin

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

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

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

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

Why?  As Asin told me:

 

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

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

“No one knows what will be the winner.

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

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

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

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

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


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

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

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

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

Siemens’s Mobility Services: Trains Become IoT Labs on Wheels

George Stephenson's Killingworth locomotive Source: Project Gutenberg

George Stephenson’s Killingworth locomotive
Source: Project Gutenberg

As those of you who know rail history understand, with Stephenson as your last name, you’re bound to have a strong interest in railroads! Add in the fact that I was associate producer of an award-winning documentary on the subject back in the early 70’s, and it’s no wonder I was hooked when I got a chance to meet with some of Siemens’s top rail executives on my trip to Barcelona last week (Disclaimer: Siemens paid my expenses, but didn’t dictate what I covered, nor did they have editorial review of this piece).

What really excites me about railroads and the IoT is that they neatly encapsulate the dramatic transformation from the traditional industrial economy to the IoT: on one hand, the railroad was perhaps THE most critical invention making possible 19th century industry, and yet it still exists, in recognizable but radically-evolved form, in 2016. As you’ll see below, trains have essentially become laboratories on wheels!

I dwelt on the example of the Union Pacific in my e-book introduction to the IoT, SmartStuff, because to CIO Lynden Tennison was an early adopter, with his efforts focused largely on reducing the number of costly and dangerous derailments, through measures such as putting infrared sensors every twenty miles along the rail bed to spot “hotboxes,” overheating bearings. That allowed an early version of what we now know as predictive maintenance, pulling cars off at the next convenient yard so the bearings could be replaced before a serious problem. Even though the technology even five years ago was primitive compared to today, the UP cut bearing-related derailments by 75%.

Fast-forward to 2016, and Siemens’s application of the IoT to trains through its Mobility Services is yielding amazing benefits: increasing reliability, cutting costs, and even leading to possible new business models. They’ve taken over maintenance for more than 50 rail and transit programs.

While I love IoT startups with a radical new vision and no history to encumber them, Siemens is a beacon to those companies firmly rooted in manufacturing which may wonder whether to incorporate the IoT in their services and strategy. I suspect that its software products are inherently more valuable than competitors from pure-play software firms at commercial launch because the company eats its own dogfood and applies the new technology first to the products it manufactures and maintains — closing the loop.

Several of its executives emphasized that one of the advantages Siemens feels they enjoy is that their software engineers in Munich work in a corner of an old locomotive factory that Siemens still operates, so they can interact with those actually building and maintaining the engines on a daily basis. When it comes to security issues, their experience as a manufacturer means they understand the role of each component of the signaling system. Dr. Sebastian Schoning, ceo of Siemens client Gehring Technologies, which manufactures precision honing tools, told me that it was easier to sell these digital services to its own client base because so much of their current products include Siemens devices, giving them confidence in the new offerings. GE enjoys the same advantages of combining manufacturing and digital services with its Evolution Series locomotives.

The key to Siemens’s Mobility Services is Sinalytics, its platform architecture for data analysis not just for rail, but also for industries ranging from medical equipment to wind farms. More than 300,000 devices currently feed real-time data to the platform,   Consistent with my IoT-centric “Circular Company” vision, Sinalytics capitalizes on the data for multiple uses, including connectivity, data integration, analytics, and the all-important cyber security — they call the result not Big Data, but Smart Data. As with data services from jet turbine manufacturers such as Rolls Royce and GE, the platform also allows merging the data with data from sources such as weather forecasts which, in combination, can let clients optimize operating efficiency on a real-time M2M basis.  

With the new approach, trains become IoT laboratories on wheels, combining all of the key elements of an IoT system:

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

When operations are digitized, it allows seamlessly integrating emerging digital technologies into the services. Siemens Digital Services also included augmented reality (so repair personnel can see manuals on heads-up displays), social collaboration platforms, and — perhaps most important — 3-D printing-based additive manufacturing, so that replacement parts can be delivered with unprecedented speed. 3-D printing also allows dramatic reduction in parts inventories and allows replacement of obsolete parts that may no longer be available through conventional parts depots or even — get this — to improve on the original part’s function and/or durability, based on practical experience gained from observing the parts in use.  Siemens has used 3-D printing for the past last 3 years, and it lets them assure that they will have replacements for the locomotive’s entire lifespan, which can exceed 30 years.

The results of the new approach are dramatic.

  • None of the Velaro trains that Siemens maintains for several operators have broken down since Sinalytics was implemented. Among those in Spain only 1 has left more than 15 min. behind time in 2,300 trips: .0004%!
  • Reliability for London’s West Coast Mainline is 99.7%

  • Perhaps most impressive, because of the extreme cold conditions it must endure, the reliability rate for the Velaro service in Russia is 99.9%!

Their ultimate goal is a little higher: what Siemens calls (pardon the pun) 100% Railability (TM).

And, consistent with what other companies find when they fully implement not only IoT technology, but also what I like to call “IoT Thinking,” when it does reach those previously inconceivable quality benchmarks, the company predicts that, as the software and sensors evolve, the next stage will be new business models in which billing will be determined by guaranteeing customers availability and performance.

PS: I’ll be posting more about my interviews with Siemens officials and the Gartner event in coming days.

Circular Company: Will Internet of Things Spark Management Revolution?

Could the IoT’s most profound impact be on management and corporate organization, not just cool devices?

I’ve written before about my still-being-refined vision of the IoT — because it (for the first time!) allows everyone who needs instant access to real-time data to do their jobs and make better decisions to share that data instantly —  as the impetus for a management revolution.

My thoughts were provoked by Heppelmann & Porter’s observation that:

“For companies grappling with the transition (to the IoT), organizational issues are now center stage — and there is no playbook. We are just beginning the process of rewriting the organization chart that has been in place for decades.”

If I’m right, the IoT could let us switch from the linear and hierarchical forms that made sense in an era of serious limits to intelligence about things and how they were working at thaFor companies grappling with the transition, organizational issues are now center stage—and there is no playbook. We are just beginning the process of rewriting the organization chart that has been in place for decades.t moment, to circular forms that instead eliminate information “silos” and instead give are circular, with IoT data as the hub. 

This article expands on that vision. I’ve tried mightily to get management journals to publish it. Several of the most prestigious have given it a serious look but ultimately passed on it. That may be because it’s crazy, but I believe it is feasible today, and can lead to higher profits, lower operating costs, empowering our entire workforces, and, oh yeah, saving the planet.

Audacious, but, IMHO, valid.  Please feel free to share this, to comment on it, and, if you think it has merit, build on it.

Thanks,

W. David Stephenson


The IoT Allows a Radical, Profitable Transformation to Circular Company Structure

 

by

W. David Stephenson

Precision assembly lines and thermostats you can adjust while away from home are obvious benefits of the Internet of Things (IoT), but it might also trigger a far more sweeping change: swapping outmoded hierarchical and linear organizational forms for new circular ones.

New org charts will be dramatically different because of an important aspect of the IoT overlooked in the understandable fascination with cool devices. The IoT’s most transformational aspect is that, for the first time,

everyone who needs real-time data to do their jobs better or
make better decisions can instantly 
share it.

That changes everything.

Linear and hierarchical organizational structures were coping mechanisms for the severe limits gathering and sharing data in the past. It made sense then for management, on a top-down basis, to determine which departments got which data, and when.

The Internet of Things changes all of that because of huge volumes of real-time data), plus modern communications tools so all who need the data can share it instantly. 

This will allow a radical change in corporate structure and functions from hierarchy: make it cyclical, with real-time IoT data as the hub around which the organization revolves and makes decisions.

Perhaps the closest existing model is W.L. Gore & Associates. The company has always been organized on a “lattice” model, with “no traditional organizational charts, no chains of command, nor predetermined channels of communication.”  Instead, they use cross-disciplinary teams including all functions, communicating directly with each other. Teams self-0rganize and most leaders emerge spontaneously.

As Deloitte’s Cathy Benko and Molly Anderson wrote, “Continuing to invest in the future using yesteryear’s industrial blueprint is futile. The lattice redefines workplace suppositions, providing a framework for organizing and advancing a company’s existing incremental efforts into a comprehensive, strategic response to the changing world of work.”  Add in the circular form’s real-time data hub, and the benefits are even greater, because everyone on these self-organizing teams works from the same data, at the same time.

You can begin to build such a cyclical company with several incremental IoT-based steps.

One of the most promising is making the product design process cyclical. Designers used to work in a vacuum: no one really knew how the products functioned in the field, so it was hard to target upgrades and improvements. Now, GE has found it can radically alter not only the upgrade process, but also the initial design as well:

“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. ‘We’re getting these offerings done in three, six, nine months,’ (Vice-President of Global Software William Ruh said). ‘It used to take three years.’”

New IoT and data-analytics tools are coming on the market that could facilitate such a shift. GE’s new tool, “Digital Twins,” creates a wire-frame replica of a product in the field (or, for that matter, a human body!) back at the company. Coupled with real-time data on its status, it lets everyone who might need to analyze a product’s real-time status (product designers, maintenance staff, and marketers, for example) to do so simultaneously.

The second step toward a cyclical organization is breaking down information silos.

Since almost every department has some role in creation and sales of every product, doesn’t it make sense to bring them together around a common set of data, to explore how that data could trigger coordinated actions by several departments? 

Collaborative big-data analysis tools such as GE’s Predix, SAP’s HANA, and Tableau facilitate the kind of joint scrutiny and “what-if” discussions of real-time data that can make circular teamwork based on IoT-data sharing really achieve its full potential.

The benefits are even greater when you choose to really think in circular terms, sharing instant access to that real-time data not only companywide, but also with external partners, such as your supply chain and distribution network – and even customers – not just giving them some access later on a linear basis.  For example, SAP has created an IoT-enabled vending machine. If a customer opts in, s/he is greeted by name, and may be offered “your regular combination” based on past purchases, and/or a real-time discount. That alone would be neat from a marketing standpoint, but SAP also opened the resulting data to others, resulting in important logistics improvements. Real-time machine-to-machine (M2M) data about sales at the new vending machines automatically reroute resupply trucks to those machines currently experiencing the highest sales. 

With the IoT, sharing data can make your own product or service more valuable. With the Apple HomeKit, you can say “Siri, it’s time for bed,” and the Hue lights dim, Schlage lock closes, and Ecobee thermostat turns down. By sharing real-time IoT data, each of these companies’ devices become more valuable in combinations than they are by themselves.

Hierarchical and linear management is outmoded in the era of real-time data from smart devices. It is time to begin to replace it with a dynamic, circular model with IoT data as its hub.

Smart Infrastructure Logical Top Priority for IoT

The only issue Clinton and Trump can agree on is the need for massive improvements to the nation’s crumbling infrastructure, especially its roads and bridges. But, please, let’s make it more than concrete and steel.

Let’s make it smart, and let’s make it the top priority for the IoT because of the trickle-down effects it will have on everything else in our economy.

Global economist Jeffrey Sachs stated the case eloquently in a recent Boston Globe op-ed, “Sustainable infrastructure after the Automobile Age,” in which he argued that the infrastructure (including not only highways and bridges but also water systems, waste treatment, and the electric grid) shaped by the automotive age has run its course, and must be replaced by one “in line with new needs, especially climate safety, and new opportunities, especially ubiquitous online information and smart machines.”

I’m currently reading Carlo Ratti and Matthew Claudel’s The City of Tomorrow: Sensors, Networks, and the Future of Urban Life, which makes the same argument: “The answer to urban expansion and diffusion — and the host of social consequences that they bring — may be to optimize, rather than increase, transportation infrastructure.”

The IoT is perfectly suited to the needs of a new information-based infrastructure, especially one which must balance promoting the economy and mobility with drastic reductions in greenhouse gasses (transportation produces approximately a third of the U.S.’s  emissions). It can both improve maintenance (especially for bridges) through built-in sensors that constantly monitor conditions and can give advance warning in time to do less-costly and less-disruptive predictive maintenance, and reduce congestion by providing real-time information on current congestion so that real-time alterations to signals, etc., can be made rather than depending on outmoded fixed-interval stoplights, etc.

Sachs points out that infrastructure spending as a percentage of GDP has fallen since the Reagan years, and that it will require much more spending to bring it up to date.

A good place to look for a model is China.  The country already sports the largest concentration of M2M connections in the world: “74 million connections at the end of 2014, representing almost a third of the global base,” much of that in the form of smart bridges, smart rails, and smart grid, and critical because of the country’s rapid economic growth (Ratti cites a Beijing traffic jam that immobilized cars for an astounding 12 days!). Similarly, the government aims to have 95% of homes equipt with smart meters by next year.The country has used its investment in smart infrastructure to build its overall IoT industry’s ability to compete globally.

Sachs argues for a long-term smart infrastructure initiative:

“I propose that we envision the kind of built environment we want for the next 60 years. With a shared vision of America’s infrastructure goals, actually designing and building the new transport, energy, communications, and water systems will surely require at least a generation, just as the Interstate Highway System did a half-century ago.”

He says we need a plan based on three priorities to cope with our current national and global challenges:

“We should seek an infrastructure that abides by the triple bottom line of sustainable development. That is, the networks of roads, power, water, and communications should support economic prosperity, social fairness, and environmental sustainability. The triple bottom line will in turn push us to adopt three guiding principles.

First, the infrastructure should be “smart,” deploying state-of-the-art information and communications technologies and new nanotechnologies to achieve a high efficiency of resource use.

Second, the infrastructure should be shared and accessible to all, whether as shared vehicles, open-access broadband in public areas, or shared green spaces in cities.

Third, transport infrastructure should promote public health and environmental safety. The new transport systems should not only shift to electrical vehicles and other zero-emission vehicles, but should also promote much more walking, bicycling, and public transport use. Power generation should shift decisively to zero-carbon primary energy sources such as wind, solar, hydro, and nuclear power. The built environment should be resilient to rising ocean levels, higher temperatures, more intense heat waves, and more extreme storms.”

The IoT, particularly because of its ability to let us share real-time data that in turn can regulate the infrastructure, is ideally suited to this challenge. It’s time for Congress to not only spend on infrastructure but to do so wisely.

The result will be not only the infrastructure we need, but also a more robust IoT industry in general.

 

I’ll be on live Thursday morning talking the IoT and Smart Cities

Cities are the future of global civilization and the economy, and smart cities are the only way they’ll survive and prosper!

Join me and two SAP experts on the subject, Dina Dayal (global vice president for Digital Enterprise Platform Group) and Saj Kumar (vice president of Digital Transformation and Internet of Things) as we guest on Bonnie D. Graham’s always-enjoyable Coffee Break With Game Changers, 11 AM EDT, 8 AM PDT (it will be archived at the site if you can’t listen live.

Bonnie likes us to start with a provocative (and relevant) quote, and mine will be from Jane Jacobs’ great Death and Life of American Cities:

Cities have the capability of providing something for everybody, only because,
and only when, they are created by everybody.”

… with the emphasis on everybody: I’ll explain that there really is an important role in smart cities for city government, the private sector, and — often ignored — grassroots innovators.

A critical key is the global Things Network, created by Wienke Gieseman and his Gang of Ten in Amsterdam,  who created a free LoRaWAN city-wide data network for $12,000 and in less than a month, and then went on to create a global network and a crowdsourced campaign to bring the cost of LoRaWAN hubs down to $200.

I like to think I was there at the beginning, working with Vivek Kundra, then the DC’s CTO (before his accomplishments there led Obama to name him the first US CIO). Vivek and Mayor Fenty took the bold move of releasing more than 40 major city data bases on a real-time basis, then held a contest to get smart developers to create new-fangled “apps” (remember, this was 2008!) to capitalize on them. Because the apps were open-source, they’ve been constantly copied and improved in the years since then.

And that’s only the beginning:

  • creative startups such as Alicia Asin’s Libelium, working with an enlightened city government, have made Barcelona a massive testlab for the Iot, and arguably THE smart city of the day
  • Columbus OH won the Obama Administration’s Smart City competition for its all-inclusive transportation scheme (and I do mean all-inclusive: who ever thought a better transportation network could be used to cut infant mortality???)
  • Smart Cities organizations have been formed in cities worldwide to share ideas — we’re all in this together!

And, of course, I’m going to bring the discussion down to earth by really getting down and dirty — yessiree, we’re gonna talk trash cans.

Be there or be square!

 

http://www.stephensonstrategies.com/">Stephenson blogs on Internet of Things Internet of Things strategy, breakthroughs and management