NOTA BENE
A blog about leadership and smart connected living

Presentation on IoT cybersecurity and corporate innovation at Harvard Club of NYC

Presented today at the Harvard Club of NYC on IoT cybersecurity and corporate innovation for highly regulated industries.

Publication on tactics for avoiding common pitfalls for IoT program leaders in IoT Central

Published a piece today in IoT Central for digital transformation leaders within organizations, and how rigid organizational structures, inflexible cultures, and lack of market insight increase the probability of creating an IoT platform that is fragmented, brittle, and ultimately more susceptible to failure.

Publication on Tiers of User Experience for Smart Connected Appliances in Appliance Design Magazine

Honored to have a piece published this week in Appliance Design Magazine on how the Internet of Things is changing the way appliance designers are addressing visceral, behavorial, and reflective user experiences for the products they create.

Radio Interview on KZSU Stanford 90.1 FM

I had a great time being interviewed by Labiba Boyd last week on Modern Tek News (KZSU Stanford 90.1 FM) on how the Internet of Things is changing everything from smart buildings to high performance road cycling as well as the companies that make the products they depend on.

Cyber-Physical Security Presentation at University of Minnesota

Honored to give a presentation at the University of Minnesota Technological Leadership Institute on how organizations can build a sustainable cyber-physical security competency, and the critical role that technology leaders play.

Building An Organizational IoT Competency: What You Need To Know

Honored to be published in Forbes this week on how organizations can build an IoT competency.

The Road To Unconscious Competence

In the field of psychology, the “conscious competence” learning model describes how individuals move from incompetence to competence in a certain subject area as they move from unconscious incompetence (naiveté about the competency deficit) to conscious incompetence (acknowledgment that there is competency deficit) to conscious competence (demonstrated competency through a concerted effort) to unconscious competence (competency as second nature).

This same model of “conscious competence” is true for organizations faced with the task of digital transformation through smart connected products, a visual depiction of which appears here.

There is no shortcut to mastery. Identification of gaps followed by planning, execution, growth and institutionalization of process and behavior are necessary waypoints on the journey to IoT competency.

The Voice of Machine Learning Starts and Ends With Humans

I had a piece published this week in Embedded Computing Design on the collaborative relationship between machines and humans when it comes to machine learning:

The Internet of Things (IoT) represents new opportunities for manufacturers to capitalize on the value of data for their business. One of those opportunities is through leveraging an approach called machine learning, which is a branch of artificial intelligence that enables machines (or virtual representations of machines in the cloud) to learn new behaviors based on their external environments, internal health, and changing inputs. However, in order for machine learning to work, humans must be able to grok the context of how the machine data is collected, aggregated, and consumed.

How IoT is Changing Corporate Innovation

I was honored to be published this week in a piece on IoT Agenda on how the Internet of Things is changing the way that organizations think about innovation:

Innovation programs are historically the vehicle that protects against internal stagnation and external irrelevance. However, the larger an organization gets, the more difficult it becomes to innovate outside of historical core competencies and market-facing product lines, both of which are common with IoT.

Interviewed by Forbes on Machine Learning

Honored to be interviewed by Forbes this week in a piece on machine learning and analytics:

"The road to advanced analytics and machine learning starts with basic connectivity and data collection. This journey includes pinpointing the questions that need to be answered with data analysis, identifying the data needed to answer those questions, and putting processes in place to gather the correct type and amount of that data to properly support machine learning."

Also, Kurt Dykema was interviewed in the same piece, saying that the first step is to start with an internal project based on a passion to solve an interesting problem:

Find an interesting problem that the team wants to crack, and let them develop their skills in machine learning while they work on a problem they are passionate about.`

Interview with Embedded Computing Design

Honored to be interviewed by Brandon Lewis at Embedded Computing Design on "IT, OT, and vying for control of the IoT connectivity platform" as part of their IoT Design initiative.

Here's a quote from the interview:

I’ve seen companies hire data scientists to try and figure out what’s going on with their data, but they haven’t captured enough data for the data scientist to actually do anything, and the data scientists don’t understand the machines well enough to know how to instrument them to get the answers that they want. So it turns into this cycle of inefficiency where if companies don’t get the first part right – which is basic connectivity, adding sensors to machines, getting data flowing, and learning to collect data on failures – if they don’t do that first they won’t ever be successful adding data scientists to their teams and driving true operational efficiency.

The Security Tesseract of the Internet of Things

Devices all around us are becoming connected to the Internet. A quick search online turns up a multitude of wild predictions. One thing is for certain: by 2020, there are going to be a lot of devices connected to the Internet.

Read more

IoT Data Engineering

Dan Woods, writing for Forbes:

The bounding condition in deploying the Internet of Things (IoT) is not going to be the deployment of devices but rather the management and analysis of the data coming off those devices. If you are interested in making use of the IoT, that’s what you need to be working on: Data Engineering.

I disagree that the deployment of IoT is "not a problem". However, it's true that the problem of dealing with large unstructured data streams is where the true dragons and opportunities are.

FIDO Alliance

About the FIDO Alliance:

The FIDO Alliance plans to change the nature of authentication by developing specifications that define an open, scalable, interoperable set of mechanisms that supplant reliance on passwords to securely authenticate users of online services.

Trading simplicity (no passwords) can at times come at the cost of high security. However, I like the line of thinking that makes simplifying assumptions such as if a person is near to a device (physical proximity), they are very likely authorized to provision and use that device.

The Industrial IoT Isn't The Same As The Consumer IoT

Varun Nagaraj:

The differences between the IIoT and IoT are not just a matter of slight degree or semantics. If your Fitbit or Nest device fails, it might be inconvenient. But if a train braking system fails, it could be a matter of life and death.

Not all IIoT applications are a matter of life and death, but it's true that industrial requirements for reliability, safety, and security are usually more stringent than with consumer applications.

International M2M Council

The IMC is gaining momentum:

The IMC will roll out its new IoT Content Library, which includes over 50 case studies emphasizing ROI for M2M deployments, during the Mobile World Congress in Barcelona.

No doubt the biggest reason for the growth of the IMC is due to the collection and dissemination of business case studies and ROI models.

GE Predix

GE is planning to "release public APIs" for their Predix platform. Nikhil Chauhan, director of product marketing for GE Software:

Predix is a set of IoT applications designed to merge the physical worlds of machines with analytical data to create software-defined machines that will ultimately eliminate unplanned downtime [...]

Making an API public is not big news in itself. However, if an API becomes widely used, it could trump other lesser-used APIs that are coming out of the standards bodies (ETSI, OneM2M, etc.).

Industrial Internet Gold: Hassle-Free UX

Pragati Verma:

As more and more millenials join the workforce, they will expect industrial equipment to offer the ease of navigation and intuitive interface similar to the smartphones and tablets they have grown up with. In the era of ubiquitous sensors and miniaturized mobile computing, a hassle-free UX design and contextual awareness will be the glue binding together the Industrial Internet.

For the Industrial Internet, UX is the new black.

Wolfram Connected Devices Project

Wolfram just announced their Connected Devices Project:

[...] today we’re launching the Wolfram Connected Devices Project—whose goal is to work with device manufacturers and the technical community to provide a definitive, curated, source of systematic knowledge about connected devices.

Built, of course, on the Wolfram Language.

PTC Acquires ThingWorx

PTC just acquired ThingWorx for $112M:

Incidentally, PTC also owns the venerable Pro/Engineer (now Creo), which is a great piece of 2D CAD software.

The acquisition is expected to add more than $10 million of revenue over the next 12 months, with $5 million to $7 million of revenue in FY'14.

Given an annual turnover of <$10M, that's a pretty nice valuation for ThingWorx (>10x). (PTC's FY'13 revenue was $1.3 billion.)

Deutsche Telekom 2014 M2M Predictions

Jürgen Hase on behalf of Deutsche Telekom:

Industrial applications are the all-time paragon of M2M.

The rest of the predictions are pretty safe (smart factories, automotive aftermarket, big data analytics, consumer applications, smart cities, and global alliances).

(Via IoT World.)

Business Model Innovation at Bosch/HSG

Anita Bunk, writing for Bosch Software Innovations:

However, what I’ve learned for the IoT is that it is not just technology that counts. Finding successful business models is equally important – and no less demanding.

There is some solid work coming from the Bosch IoT Lab at the University of St. Gallen, led by Elgar Fleisch, Markus Weinberger, and Felix Wortmann on this topic.

Bluetooth Low Energy and IPv6

Stacey Higginbotham:

The final tweak is a bit vague, but involves giving Bluetooth devices a way to talk directly to the internet by giving them some kind of dedicated channel, which could be used for IPv6 communications. But because Bluetooth is a low-power protocol, implementing IPv6 could require more battery power than is wise. So how the SIG or chipmakers add IPv6 compatibility to Bluetooth-power devices seems to need a bit more explanation and development from the chipmakers.

There has been quite a bit of work in this area at the IETF since April of 2011.

The Art of Software Thermal Management for Embedded Systems -- Final Proofs

This week, I finished reviewing final proofs for my upcoming book with Springer Verlag: The Art of Software Thermal Management for Embedded Systems. Abstract:

Thermal performance is the new bottleneck in embedded systems design. As processing requirements increase, and physical device sizes continue to decrease, it is becoming more and more difficult to efficiently get heat out of embedded systems efficiently.

This book focuses on the root cause of heat in an embedded system: power. And since software has an enormous impact on power consumption in an embedded system, if we are to manage heat effectively, we need to therefore understand, categorize, and develop new ways to aggressively reduce power.

The Art of Software Thermal Management (STM) explores both the science and also the art of reducing power consumption in a computing system as a means to manage heat, improve component reliability, and increase system safety. This book is a pragmatic guide to the field of STM for embedded systems, a catalog of software thermal management techniques, and a call to action for future areas of research and development.

Scheduled publication date is January, 2014. Formats: print (hardcover, softcover), digital/e-book. Distribution: Springer direct, Amazon, Google, and through university library systems via Springer Link.

UPDATE: Springer and Amazon and a few other distributors now have pages up in prep for the scheduled release date on January 31st, 2014: Springer, Amazon (UK), cCampus, Knetbooks, Rakuten, The Reading Room, Bigger Books, Bokus, Todos Tus Libros (All Your Books), Abe, Desch-Drexler, All Bookstores, and Foyles.

6LoWPAN-Compressed DTLS for CoAP

Ran across this excellent paper today by Raza, Trabalza, and Voigt on the topic of compressing and fragmenting DTLS headers over 802.15.4 networks using 6LoWPAN for CoAP. From the abstract:

Real deployments of the IoT require security. CoAP is being standardized as an application layer protocol for the Internet of Things (IoT). CoAP proposes to use DTLS to provide end-to-end security to protect the IoT. DTLS is a heavyweight protocol and its headers are too long to fit in a single IEEE802.15.4 MTU. 6LoWPAN provides header compression mechanisms to reduce the size of upper layer headers. 6LoWPAN header compression mechanisms can be used to compress the security headers as well. In this paper we propose 6LoWPAN header compression for DTLS. We link our compressed DTLS with the 6LoWPAN standard using standardized mechanisms.

CoAP requires DTLS, so that's not new. However, compressing and fragmenting DTLS such that it can be transported using 6LoWPAN is really neat. IoT needs more security-based solutions like this for resource-constrained sensing applications.