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Case Studies (146)

In the United States, precision agriculture is one of the largest industries by both operational scale and economic impact. The technology utilized is typically on the cutting edge, especially for automation and control. Things like sensors, programmable IoT radios and generally more complex software applications have allowed that industry to evolve, domestically, to a point where land and other resources are used optimally. Internationally, although there have been ‘smart’ or ‘precision’ practices in certain sectors of agriculture, many countries are just now starting to adopt the technology to its fullest extent, including the ability to innovate via start-ups and new practices.

India & the Digital Agriculture Revolution

According to an article in India Times (image credit), the country is aiming to secure a 20 percent stake in the IoT market share in the next five years through its ‘Digital India’ initiative. While many might look at India and think of the sprawling and diverse urban environments that could offer some potential complications for IoT, it is rural areas seeing the most interesting developments. There has been a noticeable growth in tele-medicine operations, which can allow patients in remote areas to interact with doctors for consultation, eliminating the need to get to a city, or vice versa. Perhaps an even greater area of growth lies in the agricultural realm. According to the article, agriculture employs 50 percent of the country’s population, so the potential for a digital revolution is high. Farmers are just starting to implement sensor technology, automation hardware, and even leading-edge tools like voluntary milking systems the allow cows to be milked on an automated machine according to biological needs.

Israel’s Precision Ag Start-Up Community

In Israel, where IoT technology is starting to mature, the name of the game is data collection and analytics. Mobile applications, sensor data collection hardware, and advanced analytics software are three areas that Israel is seeing significant market growth, according to Israel21c:

Israel stands out in precision-ag subsectors of water management, data science, drones and sensors, says Stephane Itzigsohn, investment associate at OurCrowd. … “Multiple startups are aiming toward the same goal — providing good agricultural data — but approaching it from slightly different angles,” Itzigsohn tells ISRAEL21c. “One might use satellite images or aerial photography; another might use autonomous tractors. Not all will get to that peak in the long journey of farming becoming more efficient.”

For example, CropX, an investor-backed advanced adaptive irrigation software solution, can be placed throughout a farming area and synced with a smart phone, allowing the operators to receive real-time data updates on things like soil and weather conditions. CropX is based in both Tel Aviv and San Francisco, indicating that the technology may be poised for wide international adoption in the future.

Analytics Drive Italy’s Drought Recovery

Italy is perhaps best known for a single agricultural export: wine. However, many would be surprised to find out that it is one of the top corn producers in the European Union, producing more than 7 million tons of corn in 2015, according to an RCR Wireless report. In 2016, the EU’s total corn output dropped noticeably due to year-long droughts affecting production. In Italy, start-up companies collaborated with industrial ag operations develop and deploy widespread soil sensor and water automation technology to help streamline farming practices and create a more efficient system for resource use. The technology allowed farmers to get a comprehensive look at their operations and identify high and low yield areas in order to better utilize the available space.

Precision Agriculture and the Industrial IoT

The continued maturation of IIoT technology is enabling countries around the globe to better utilize resources like water, energy, and land area to create better agricultural operations. As populations continue to expand, and food production becomes even more important, being able to connect these technologies across the globe could become a key factor in optimizing crop output in critical areas. Imagine the above farm in Italy being able to send its data to data scientists in Germany or the Eastern Europe who could in turn analyze it and provide actionable feedback. Or an industrial farm in Israel managing its yields sending that information in real-time around the country. These possibilities are not far off, and as the networks, hardware and software continue to be adapted, the future of precision ag internationally, will become the present.

For additional reading:

India Times: http://www.indiatimes.com/news/india/how-the-internet-of-things-is-digitizing-agriculture-speeding-up-rural-development-in-india-326546.html

Israel 21c: https://www.israel21c.org/5-israeli-precision-ag-technologies-making-farms-smarter/

RCRWireless: http://www.rcrwireless.com/20161005/big-data-analytics/precision-agriculture-omica-tag31-tag99

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20 Job Interview Questions for IoT Professionals

Bill McCabe knows everyone. He has to. He’s a thought leader in IoT, with a particular focus on recruiting. He’s authored dozens of articles on all things IoT and recruitment, and has placed a number of IoT professionals at organizations big and small. We wanted to know in particular, for the IoT job seeker, what are the top 20 questions they should be prepared to answer in their interview. Below is what Bill shared.

  1. What changes in the IoT do you feel is the most groundbreaking?

  2. How would you assess a security concern in our software?  

  3. What was the last training course you took?

  4. What is the most overlooked thing with the IoT during development and deployment ?

  5. How will you take our technology to the next level?

  6. What effect will the Internet of Things have on your daily life?

  7. Do you think IoT will be a job killer or a job creator?

  8. What concerns do you have about IoT and privacy and security ?

  9. What are the difference between the Industrial Internet of Things and the Internet of Things?   

  10. What do you think will be the impact of IoT on Smart Cities?

We have 10 more important questions for you to consider in your IoT interview. To see the rest of the questions, become a member of IoT Central (it’s free!) and click here.

Did you get a great, interesting or hard IoT related question during your interview? If so, let us know and we’ll add it to this list. Leave your question in the comments section or email us

 

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Here is the latest round-up of articles from IoT Central. Remember: get your friends and enemies to join IoT Central here.

Navigating the Critical Database Decision While Building Our IoT Application

Posted by Gena Minevich

The promise of IoT solutions comes from their tremendous ability to harness data on a scale that has never before been possible. This data, wrangled by countless transmitters and sensors, offers us a wealth of insights about everything from the homes we live in to the products we buy to the health of our own bodies – all while IoT applications provide the power to act upon this data in real-time. Delivering these remarkable capabilities calls for a similarly capable database, one that can match IoT applications’ stringent requirements around performance, scalability, and availability.

Ongoing trends in IoT device lifecycle management

Posted by Mohit Bhardwaj 

IoT device lifecycle management is the key element for industries to have complete insight and control of their devices infrastructure. Today, device lifecycle management enables many industries to transition to ‘smart’ ecosystems, like smart energy (a.k.a Internet of Energy or smart grid), smart buildings, smart retail, smart transportation, smart cities, smart factories, and smart agriculture. As more and more devices get connected, the challenges with data security, control, and management becomes critical. IoT remote device lifecycle management plays a key role in enabling a 360 degree data view of the device infrastructure.

Interview: Bringing Machine Learning to The Edge

Posted by David Oro

A couple of weeks ago, I spent a few hours at GE Digital’s headquarters in San Ramon, CA. It was a great overview by several executives of how GE is using their Predixplatform to create software to design, build, operate, and manage the entire asset lifecycle for the Industrial IoT.  A big part of this transformation for GE involves hiring tons of software developersacquisitions, and partnerships. One of those partnerships is with Silicon Valley based FogHorn Systems (GE Ventures, Dell Ventures, March Capital and a few others are investors). FogHorn is a developer of “edge intelligence” software for industrial and commercial IoT applications. FogHorn and GE are working very closely on many IIoT customer use cases, across verticals, bolstered by the integration of FogHorn with Predix. I turned to FogHorn Systems CEO David C. King to learn more about edge intelligence software for the Industrial IoT.

The Buzz of Platforms and the Bazaar of IoT Platforms

Posted by Somjit Amrit

Among the words, phrases and acronyms in the Tech worlds “Platform” seems to be a word which seems to grab the headlines. If one listens to any pitch from a start up venture it would be not uncommon to get the “platform pitch”in at least 1 out of 2 proposals. A lazy search on Google on the “Top 20 Tech weary  words” fetched me the result that “platform was 3rd in the list . There have been words verbalised like “Being Platformed” as well and a host of books on the significance of platform in the Technology world. I will not go into the virtues of platform. I would dwell on how the leaders in respective segments  are a few ( a maximum of 3 ) while in the IoT world we seem to have by some counts 170 of them ( McKinsey ) to 400 of them ( Beecham Research).This is definitely a bewildering array to go through and investigate . What is a Platform – why there are only a few platform leaders ?

Infographic: Securing Connected Cars

Posted by David Oro 

In my recent interview with Sam Shawki, the founder and chief executive officer of MagicCube, I wrote about getting a new Ram Truck and noted that it was a beast not just in size and towing power, but a beast of electronics and connectivity. According to Intertrust Technologies, the percentage of new cars shipped with Internet connectivity will rise from 13% in 2015 to 75% in 2020, and that in 2020, connected cars will account for 22% of all vehicles on the road. That number is sure to grow. More stats in the infographic below. 

AggreGate Server on Nanopi NEO

Posted by Victor Polyakov

We’ve tested AggreGate Server on Nanopi NEO, one of the smallest Linux-based single-board PCs. Despite its small size, this device simply rules! It has RAM 512 Mb on board, 1,2 GHz quad-core CPU, 10/100M Ethernet network interface, and many other interfaces to connect the world. AggreGate possibilities on the NEO board are similar to Linux-based Tibbo Project System. It can act as a simple close-knit protocol gateway with intermediate data processing.


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Interview: Bringing Machine Learning to The Edge

A couple of weeks ago, I spent a few hours at GE Digital’s headquarters in San Ramon, CA. It was a great overview by several executives of how GE is using their Predix platform to create software to design, build, operate, and manage the entire asset lifecycle for the Industrial IoT.  A big part of this transformation for GE involves hiring tons of software developers, acquisitions, and partnerships.

One of those partnerships is with Silicon Valley based FogHorn Systems (GE Ventures, Dell Ventures, March Capital and a few others are investors). FogHorn is a developer of “edge intelligence” software for industrial and commercial IoT applications. FogHorn and GE are working very closely on many IIoT customer use cases, across verticals, bolstered by the integration of FogHorn with Predix.

I turned to FogHorn Systems CEO David C. King to learn more about edge intelligence software for the Industrial IoT. David has been at the helm of FogHorn since 2015, a year after its founding. Prior to FogHorn, David co-founded AirTight Networks, Inc., a technology leader in secure cloud-managed Wi-Fi. Before AirTight, he served as Chairman, President and Chief Executive Officer of Proxim Inc., a pioneer in WLANs and the first publicly traded Wi-Fi company, from 1993-2002.

Lots of talk about the edge in IoT. It’s my smartphone and my doorbell, as well as the sensor on a traffic light or a wind turbine. What exactly is the edge of the network and how do you define it?

We define edge as the closest compute point that can process real time streaming data. So in your case, all three -- phone, doorbell, sensors -- are edges because you can bring compute to the data on any of these platforms. The question is what compute is possible? The single variable filtering that you can do on a sensor is very simple when compared to the complex Machine Learning models that can execute on your phone.   

Analytics is done in the data center or cloud. You claim to do this at the edge now.  Please describe your offering.  

FogHorn has developed a tiny footprint complex event processor (CEP) that provides advanced streaming analytics, and machine learning capabilities at the edge.  This powerful combination of being able to pre-process, cleanse the data and execute ML models, all in real-time, brings the power of big data analytics to the edge. The FogHorn software platform is highly flexible and can be easily scaled to optimize for footprint and/or feature needs.

Tell us about a customer you’re working with and how they are applying your technology.

FogHorn Lightning is an extensible platform currently used by customers from Manufacturing, Oil & Gas, Power & Water, Renewable Energy, Mining, Transportation, Smart Buildings/Cities and other industrial verticals. The deployment patterns range across gateways, PLCs, to ruggedized servers in production, at Fortune 100 sites. A common implementation of FogHorn Lightning is product quality inspection, predictive maintenance, real time health monitoring. Customers are seeing immediate business value; e.g. identifying defects in the early stages of manufacturing reduces, scrap and increases yield. Additionally, there is a trend to FogHorn to generate new streams of revenue by providing real-time smart maintenance for their end customers.

When compared to software-defined IIoT smart gateways, there are still millions more hardware-defined M2M gateways out there. At what point do we cross the chasm to smarter gateways, and where are we now in this cycle?

We are still very early in adoption of IIoT technologies. Understandably, typical industrial sectors are conservative, and have much longer adoption curves. However, we are beginning to observe that it the ROI from edge intelligence is accelerating customer demand for FogHorn. We will cross the chasm once industries identify key use cases that generate new revenue streams, which is still about 3-5 years away.

You can’t talk about IoT without talking about security, and it’s even more important in the industrial sector. How do you address security concerns for your customers and what does the industry need to do to make IoT more secure?

Yes, you are right. When you think of IoT, especially IIoT, security is a top concern. Hacks such as “Devil’s Ivy” will become everyday events with increasingly connected devices. At FogHorn, our edge intelligence software runs very close to the data source, and is local to the asset. This implies that we are secure (like the assets) behind firewalls, and in a DMZ layer. And because most of our processing is done locally, we are less vulnerable to malicious hacks that occur when connected.

Because IIoT is still such a nascent set of technologies, we caution users to deploy solutions after thoroughly weighing the business value, and convenience versus security risk factors. My guiding question before any deployment: “Can I do this locally, without connecting to an external network?”. The answer is usually yes, and if otherwise, you should probably talk to us.

How can companies make their industrial processes better?

We understand that today’s industrial processes are highly complex and advanced, with many moving parts. While it may seem humanly impossible to optimize it any more without help from technology, we believe that a key asset is still untapped: your operator! Companies will start seeing incredible improvements once they translate the tribal knowledge on the plant floor into actionable insights. This can be further supplemented by techniques from machine learning, and artificial intelligence, to tease out the known unknowns, and also, the unknown unknowns.

Anything else you’d like to add?

FogHorn is redefining edge intelligence for IIoT. A year ago, we started our journey as a company that did analytics on tiny footprint devices. Today, we have accelerated the transition to Machine Learning at the edge, and are very are excited about the market validation. With our Operational Technology focus, we are looking forward to defining new business models, and delivering transformational value for our industrial customers.

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Imagine your worst winter day. Bone-chilling cold, howling, bitter winds, blinding snow and sleet, and your truck is encased in ice. What do you do? You tough it out, scrape the ice off the windshield and get to work.

The radio network deployed at one of the world’s most important weather research facilities has to endure and perform in extremely brutal climates nearly every day of the year, 24/7/365. Lives depend on its successful transmission of weather data. And for over a decade, wireless data radios have gotten the job done at the Mount Washington Observatory.

LOCATION: The private, non-profit Mount Washington Observatory (MWO) in New Hampshire, USA, one of the most important state-of-the-art climate research facilities in the world.

With a weather recording history dating back to 1932, the MWO’s mission is to research the Earth’s climate. Weather observations are reported to the National Weather Service and National Oceanic and Atmospheric Administration for use in nationwide and global forecasting models.

Additionally, the New Hampshire State Park (NHSP), US Forest Service Snow Rangers, and New Hampshire Fish and Game all rely on the MWO’s current weather data to determine the safety and viability of launching search operations.

In short, the MWO saves lives and provides critical climate data, and rugged wireless data radios delivers it – no matter what the weather conditions may be.

Located on the highest peak in the Northeast United States (elevation 6,288 ft.), the MWO operates mission-critical weather stations in notoriously brutal and erratic weather conditions that are amongst the worst in the world. The long-standing slogan of the MWO is “The Home of the World’s Worst Weather” and summit conditions certainly prove this.

During the summer, researchers encounter 50-100 mph winds with penetrating fog.  Winter conditions include sub-arctic temperatures, 140+ mph winds, freezing fog, and heavy glaze icing.  The weather can change rapidly, going from clear and warm to fogged-in and freezing within minutes.  Additionally, ice accretion rates of up to 12”/hour are often observed. Winter winds can change from light and variable to hurricane-force, and beyond, without notice, with blinding snow eliminating all visibility.  In fact, at one time Mt. Washington held the world record for recorded wind speed of 231 mph.

These unique conditions make the Observatory an ideal location for research and product testing. If a product is stamped “Mt Washington Tested”, know that it has experienced the harshest conditions imaginable on this continent.

It is because of these year-round brutal conditions that the MWO turns to proven data radio technology for mission-critical and extremely rugged wireless communications.

THE NETWORK

On its mountaintop weather station, MWO deploys a radio network of 900 MHz frequency hopping spread spectrum (FHSS) radios (both serial and Ethernet) connecting a network of 28 sensors and devices on five different remote weather stations. These stations and sensors measure temperature, humidity, wind speed/direction and ground temperature. Continuous links are vital to provide real-time weather feeds.

The master radio is located 4 miles away on the summit of 4,063 ft. Wildcat Mountain, with 5 client stations situated at 1,000 ft. intervals along the Mt. Washington Auto Road, a privately owned 7.6 mile gravel and tar road that winds its way to the summit at 6,288 ft. These combined stations comprise MWO’s Auto Road Vertical Profile (ARVP). The Auto Road is closed to the public in winter, but the staff of the MWO and the NHSP routinely travel its treacherous path to and from the summit in full-sized snowcats, breaking through snowdrifts of 10 and 20 feet, carving a notch into its side in the vicinity of the actual road.

Because this type of winter travel is so treacherous, current weather data along the road is crucial for the safety of the crew, and both the MWO and the NHSP rely on FreeWave radios to maintain the constant communications links between weather stations and data servers.

The FHSS radio network has been in operation since 2004.

All 6 weather stations are solar-powered in locations that only get sunlight approximately 40% of the year, so the MWO needs radios that consume minimal power while providing constant 24/7/365 connectivity on the Mount Washington Regional Mesonet. In meteorology, a mesonet is a network of automated weather and environmental monitoring stations designed to observe meteorological phenomena.

RESULTS

According to the MWOs IT Manager, Peter Gagne, “For almost 13 years these radios have been on duty continuously, and I personally can attest to their durability and reliability in conditions that, frankly, radios shouldn’t survive. These radios routinely are exposed to bitter cold and winds that far exceed the radios specifications, and have always passed the test. It is because of this outstanding record of performance, as well as the superior customer support we receive, that we have decided to stay with FHSS radios, despite the multitude of competitors, in the upgrade of our ARVP sites this year of 2017.”

Highlights include:

  • Cost-effective, real-time data transmission enabled by a rugged serial communication solution.
  • Mount Washington Observatory is able to issue severe warnings that assist operations and rescue efforts.
  • Real-time weather data and highly reliable performance in extreme weather conditions.

FreeWave Technologies has been a supplier to the MWO for more than a decade and has provided a reliable and rugged wireless data communiocation network in spite of the brutal weather conditions. To learn more, visit: http://www.freewave.com/case-studies/.  

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The IoT Central Interviews

Got a cool perspective on IoT? Writing code that streamlines IoT analytics? Analyzing killer data to drive business value? Leading a team of technologists and data scientists that is at the forefront of the industrial IoT? Then we want to talk to you. 

We are expanding our interviews series so I invite you to suggest names of inventors, analysts, thought-leaders, executives, and practitioners who are driving the Industrial IoT. It could be you. Tips and interest to: [email protected]

This edition of IoT Central Digest highlights some of our most popular interviews. Remember: get your friends and enemies to join IoT Central here.

Interview: Why is it so hard to monetize the Internet of Things?

From wind turbines to your washing machine, the IoT is all the rage, and everyone wants their piece of the pie. Monetization and creating business value, not to mention profits, is the holy grail for the IoT. But who is really making money on the IoT and where are the most lucrative opportunities?  For that we turned to Mike Fallon, Senior Advisor of the IoT Transformation Advisory Practice at PTC. Mike is responsible for delivering frameworks to companies that address the how of IoT monetization – specifically for CIOs and other C-suite executives.

Interview: How Connected Cars Can Learn from Fintech

With connectivity increasing and self-driving cars on the fore, how do we keep improving on the convenience while keeping it secure. For that we turned to Sam Shawki, the founder and chief executive officer of MagicCube, a digital mobile security start-up located in Silicon Valley. Prior to his current role, Sam was head of Visa’s Global Remote Payments business unit, where he drove the company’s global initiatives in mobile and remote payments.  Before Visa, Sam served as Chief Innovation Officer of VimpelCom, the sixth largest mobile network operator in the world, with over 214 million customers in 18 countries. We asked him about connected cars, mobile security, and what’s in store for the future.

An Interview with Ken Finnegan, Chief Technology Officer, IDA Technology Ireland

Who's Your Buddy? An interview with Dave McLauchlan, CEO & Co-Founder, Buddy Platform

Last week at IoT World, I stopped by the Buddy Platform booth (namely because of their killer Lego set-up). Buddy provides data hosting and management solutions for manufacturers and vendors of connected ("IoT") devices. Prior to IoT World, I sent Buddy CEO and Co-Founder Dave McLauchlan a few questions. Here's what he had to say.

Are You Real? Bringing Authentication to IoT

Serial entrepreneur Chris Ciabarra is at it again. The co-founder and CTO of Revel Systems, an iPad point-of-sale (POS) disruptor which has a valuation of more than $500 million and landed a global contract to replace all of Shell Oil’s PoS terminals with Revel’s, has helped launch Authenticated Reality, an authenticated secure community that fosters real interactions, comments and online conversations from real people on the internet.

Chris is an anti-hacker and data security expert with a strong background in PCI compliance and P2PE. He has presented across the globe as well as in front of the 5th Annual United States Homeland Security Conference on various security topics including how the Internet needs to change.

While his current company is aimed at getting consumers and business to identify themselves as “real,” we couldn’t help but ask him about what his current endeavor might mean for IoT. 

Autodesk's Bryan Kester - Skills for the IoT pro, disagreement with Gartner, and what's next for IoT

In our latest installment of interviews with IoT practitioners, we interview Bryan Kester, Director of IoT, Autodesk, Inc. Bryan leads the Internet of Things (IoT) Product Group at Autodesk. We asked him questions about Gartner's prediction of IoT maturation, his take on the IoT platform wars, the skills sets needed in this rapidly emerging and changing field, and what's next for IoT. Bryan predicts, "There will be some continued hype and then a subtle, but significant shakeout among both pure play and "me too" vendors. Those that help simplify the systems integration nature of IoT will have a future."

Interview: 3M's Road to IoT

 

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Future-Proofing Your IoT Infrastructure

For all the value and disruptive potential that Internet of Things (IoT) solutions provide, corporate buyers face a dilemma. Today’s IoT technologies are still immature point solutions that address emerging use cases with evolving technology standards. Buyers are concerned that what they buy today may become functionally or technologically obsolete tomorrow. Faced with this dilemma, many defer buying even if the IoT solutions they buy today offer tremendous value to their organizations.

This post describes a planning strategy called “future-proofing” that helps managers, buyers, and planners deal with obsolescence.

What causes IoT solution obsolescence?

An IoT solution, whether you buy it now or in the future, can become functionally obsolete for several reasons, as described in Figure One.  Unlike more established technologies, today’s immature and fast evolving nature of IoT solutions, amplifies the risk of early obsolescence.

For example, today there are multiple Low Power Wide Area Network (LPWAN) connectivity options – SigFox, LoRa, RPMA (by Ingenu), Symphony Link (by Link Labs), NB-IoT and LTE-M. While each option has advantages and disadvantages, a subset of these will eventually “win” out as technology standards, business models and use cases emerge.

Similarly, there are 350+ IoT platforms in the marketplace today (source: “Current state of the 360+ platforms”, IoT Analytics, June 9, 2016). While many of these platforms target specific applications and industry segments, consolidation is inevitable as there are more vendors than the market can eventually support. The major IoT platform vendors (Amazon, Microsoft, Google, IBM, GE, et al), currently on a market share land grab, will drive consolidation when they begin to acquire select vertical platforms to gain rapid access to those markets.

What is Future-Proofing?

According to Collins English Dictionary (10th edition), “future-proof” is defined as:

“protected from consequences in the future, esp. pertaining to a technology that protect it from early obsolescence”

Because of the high cost of enterprise technologies, many buyers perceive obsolescence as bad. To them, future-proofing means keeping the technology as long as possible in order to minimize costs and maximize return on investment (ROI). Their companies have standardized their business processes, policies and even their technical support on the technologies that they have bought. When a solution goes End of Life (EOL) and transitions to a newer version, it means that managers will have to recertify and retrain everyone on the “new” solution all over again. In general, transitions happen over a period of months (and sometimes years) in large global companies. During this time, multiple generations of the solution will co-exist, with each requiring different processes and policies.

In today’s fast moving IoT market, planned and unplanned obsolescence will be the norm for the foreseeable future. The traditional concept of “future-proofing” doesn’t apply, and can lead to significant, adverse business disruption.

In the era of cloud based solutions and IoT, future-proofing is not about outguessing the future, and choosing the “right” solution so as to never have to “buy” again. Nor is it overbuying technology now to avoid buying in the future. Finally, future-proofing is not about avoiding change. Future-proofing is a solution lifecycle management strategy. It is a continuous process to maximize solution flexibility and options, while making deliberate choices and managing risk.

What does a future-proof IoT infrastructure look like?

In planning the future-proofed IoT infrastructure, managers must first understand its key characteristics, and then define specific requirements for each of those characteristics. At a high level, these characteristics include:

  • Usable– the infrastructure and solutions achieve all functional needs with no loss in performance, security, service level agreements (SLA) over the desired time period.

  • Scalable – supports future needs, applications, devices

  • Supportable – resolves technical, performance, reliability, SLA issues

  • Changeable – addresses “lock-in” and facilitates migration to updated solutions on your schedule based on your needs

  • Economical – the total cost of ownership of the solution stays within forecasted ranges

A framework for future-proofing your IoT infrastructure

Change is constant and cannot be avoided. The driving principle behind future-proofing is managing change, not avoiding or preventing it. This principle recognizes that every solution has a useful functional life, and that what is functionally useful today may be obsolete and discarded tomorrow.

A properly designed future-proof plan provides the organization with options and flexibility, rather than lock-in and risk. It prevents suboptimal decision-making by managing the infrastructure on a system level, rather than at the individual component level.

Future-proofing your IoT infrastructure is a three step process (Figure Two). It is not a “once and done” exercise but must be done annually to remain relevant.

Plan and Design

The first step of the future-proofing process is to identify and place the various IoT infrastructure, systems and solutions into one of nine actionable categories. These categories are shown in Figure Three. The horizontal rows represent the “change” category, while the vertical columns represent the timeframe decision timeframe.

The actual classification of the IoT infrastructure solutions into one of the categories is determined in conjunction with IT, operations and the business units. Key considerations for determining the “future-proof category” include:

  • Usability/functionality – functional utility, compliance with standards, performance against needs, SLAs, and performance

  • Scalability – ability to meet current and future needs, anticipated change in standards

  • Support – resources, expertise, reliability

  • Ease of transition –contractual agreements, technology interdependence/dependence, specialized skills

  • Economics – maintenance costs, licensing/content/subscription fees, utilities, new replacement costs, transition costs

Source and Build

Once the proper categorization is completed, the second step is to procure the necessary solutions, whether they are hardware or software. This requires that a sourcing strategy be put into place over the desired time period. The terms sourcing and buying are sometimes used interchangeably, but they are not the same. Sourcing is about ensuring strategic access to supply while buying is more transactional. In executing the future-proofing plan, procurement managers must understand the supplier product lifecycle, and develop specific tactics.

As an example, a large global company decides to standardize around a specific IoT edge device (and specific generation) and technology for the next five years. In order to maintain access to this supply during this time period, it employs a number of tactics, including:

  • Stocking of spare units to be deployed in the future

  • Placing large “Last time” orders before that version of the solution is discontinued

  • Sourcing refurbished versions of the technology

  • Incorporating leasing as sourcing strategy

  • Negotiating contractual arrangements with the vendor to continue the solution line

Support and Monitor

The third step in the future-proofing strategy is to keep the IoT infrastructure and solutions operational over the desired time period. This is relatively easy when the solutions and technologies are being serviced and supported by the vendors. However, as vendors transition to newer technology and solution versions, buyers may find limited support and expertise. This problem is amplified the further you are from the original end-of-life date.

To keep the infrastructure and solutions fully operational during this time, companies must employ various reactive and proactive tactics. Some of these include:

  • Incorporating and installing vendor firmware updates to maximize functionality, apply bug fixes and extend useful life. Vendors may issue firmware updates on both End of Life and current generation solutions.

  • Purchase warranty and extended warranty and maintenance service contracts to assure access to support

  • Develop in-house maintenance and repair capability

  • Negotiate special one-off engineering support services with the vendor or their designated contractors

About:

Benson Chan is an innovation catalyst at Strategy of Things, helping companies transform the Internet of Things into the Innovation of Things through its innovation laboratory, research analyst, consulting and acceleration (execution) services. He has over 25 years of scaling innovative businesses and bringing innovations to market for Fortune 500 and start-up companies. Benson shares his deep experiences in strategy, business development, marketing, product management, engineering and operations management to help IoTCentral readers address strategic and practical IoT issues.

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Being direct part of the worldwide development community for "Internet of things" and connected device and working day by day on architectural topics and talking to many experts in this area, I've mentioned that indeed the technologies behind IoT are well known but the definition of IoT itself is very diverse. My key experience was while I was participating the Security of Things conference in Berlin this year. The discussions what IoT is and what is IoT not started already during the icebreaking session the evening before the first official day and continues in the same manner during the next two days. I've heard statements like "Every PC is an Internet of things device" over "Any internet connectivity must be disabled (to guarantee security)" up to "We log the values of a digital thermometer by hand and enter them in a specific AWS-based Back-End to run analytics on it ... therefore we converted our thermometer to an Internet of things device". This experience gave me the impulse fin
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In May, after nearly 10 years and a 147,000 miles, I sold my 2008 Mazda CX-9. It was a great car for me and my family. Our new car is a truck, the Ram 2500. It’s a beast, not just in size and towing power, but a beast of electronics and connectivity. Sure the 2008 Mazda had Bluetooth and a GPS, but cars today are so much more connected with onboard services like WiFi, custom car applications, and even consumer applications like Yelp! Mind you, this is a Ram Truck I’m talking about, not a Tesla or a Prius.

With connectivity increasing and self-driving cars on the fore, how do we keep improving on the convenience while keeping it secure. For that we turned to Sam Shawki, the founder and chief executive officer of MagicCube, a digital mobile security start-up located in Silicon Valley. Prior to his current role, Sam was head of Visa’s Global Remote Payments business unit, where he drove the company’s global initiatives in mobile and remote payments.  Before Visa, Sam served as Chief Innovation Officer of VimpelCom, the sixth largest mobile network operator in the world, with over 214 million customers in 18 countries.

We asked him about connected cars, mobile security, and what’s in store for the future.

When people talk about connected cars and especially self-driving cars, many worry about the safety around driving, without immediately thinking about the security behind all of the connections that are required for the connected car’s infrastructure to thrive. How does mobile security play a part?

Whether the smartphone is at the heart of what makes cars connected, or an embedded system created by automotive manufacturers like your car’s dashboard or even a digital car key takes over the identity hub, many of the car systems and subsystems are getting smart which means such systems are now attackable.  

What are some of the challenges car companies are facing today that may require different thinking?

The right technologies to protect these systems cannot come from legacy ideas like inserting a secure chip in each system or relying on pure encryption like white box of multi-party computation alone. It needs to be designed specifically for scale and with security specific to mobile and IoT deployments. This is the different thinking that the connected cars ecosystem has no choice but to embrace, and quickly.  

What can car companies and governments learn from other industries when it comes to connected cars?

Security breaches in any industry should be viewed as a clarion call to the automotive industry. There are lessons to be learned there. For example, look the recent eATM breach from the financial sector. This is believed to be related to technology that used legacy ideas that adhered to minimal security requirements. The difference between security breaches on ATMs and on self-driving cars of course is that a security breach on a car going 70 mph is truly a matter of life and death.

Who’s doing connected cars well?

It’s too early to tell. Many are on the right track, yet security remains a huge concern.  I’m excited to see who figures this out first and our team is working hard to make sure MagicCube is empowering such success.

Your background is in payment technology. Does that throw people off when you talk to car companies about MagicCube?

Although I know a lot about it, my background is not on the financial side, but rather in innovating new technologies and business models across many industries. I was part of the initial teams at Netscape where we enabled the masses to experience being connected for the first time, Shoretel where VOIP for the enterprise was invented and at Siebel Systems where CRM and e-business were made mainstream. My experience at Obopay or Visa comes from my work in enabling the security and digitization, not the other way around. The beauty of such experience is that the financial industries historically pioneered other industries like aerospace and connected cars, and established standards that other industries adopt. This is helping us at MagicCube navigate industries where standards and protocols are just starting to take shape.

Explain how MagicCube came about and why it’s called MagicCube?

While running global remote payments for Visa, which was under the digital and innovation side of the business, Visa and MasterCard created tokenization and figured out how to secure those tokens by asking device makers like Apple to house the tokens in their hardware. In Apple’s case this became Apple Pay. The next logical step was to figure out how to secure the Visa and MasterCard tokens without having to depend on hardware. This when we discovered that no solution existed and I was told it is impossible to have the same level of security in pure software. Given my background, I was motivated to solve this problem properly. In talking to Nancy Zayed, a distinguished engineer in her field, she figured out how to solve the problem using her years of operating systems knowledge at Apple, Cisco and other companies. Just to be able to visualize something virtual, the “cube” is what we called the secure software container that replaces the need for a hardware chip. Since we seem to have achieved a technology that we were told was impossible, what came to our minds was Sir Arthur C. Clarke’s quote, “Any sufficiently advanced technology is indistinguishable from magic.”  Hence MagicCube.

Anything else you’d like to add?

I’m excited by the evolution and the social impact potential of self-driving cars. When it comes to autonomous cars, we still have a fair way to go, mainly because car systems will need to process data without attackers gaining any form of control on the car or any of its systems. That is where the success, and even the viability of self-driving cars will be measured.

 

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So You Think You Know Your IoT Devices

What's the difference between IoT vs. IIoT besides the extra I? What is 3M doing in IoT? What you need to know about data in Antarctica. It's all in this edition of the IoT Central Digest, and more. 

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Not all Devices are IoT or IIoT

Business opportunities created by Internet of Things (IoT) and the Industrial IoT (IIoT) are among the most debated topics, as these are designed to function in a broad range of consumer and industrial applications. Manufacturers of IoT components believe in this new trend, but many of them still not understand the essence of the IoT concept. In reality, not every controlled device is an IoT nor IIoT.


Interview: 3M's Road to IoT



Deep Learning Vs Machine Learning And Its Affect On Jobs

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With the revolution in IT regarding the connectivity and internet, a new concept of internet of things is being evolved. This is increasing the number of jobs in this sector for example; 3D printing has shown a growth of whooping 1800%. Some of the jobs that you can get if you have the right skillset are-

  • Agriculture technologist-vehicle location, need of fertilizers, fuel in the vehicles and even check the moisture of the soil all are detected by using a network of sensors. Agricultural technologist can be very helpful to the farmers for maximizing their production.
  • Grid modernization engineers- the electric grids that are being used are becoming outdated and the need for ‘smart’ grid has started to rise. These grids would make the power consumption more effective for which, they will be needed to monitor the power consumption of each house, street lamps and even the traffic signals. Imagine the communications that will take place between the sensors and for this the employer needs someone who is an expert in the field.
  • Wearable techs- smart watches, smart t shirt all are perfect example of how this interconnectivity is increasing between the sensors of the same gadget. With smart watches you can take and make calls with your watch and the smart shirt records all your activity and stores it for further review. The market is growing and you can find out lots of jobs.
  • Medical robot designer- with the advancement in medical science, the surgeries are now being done using robots that of course is more accurate. All the sensors, small gears and all the complex machinery are actually interconnected because of which it is showing such growth. In near future, it is being estimated by the experts that robots will replace the doctors in the surgery rooms which will help this sector grow and invite the deserving for a bright future.
  • Data security expert-More and more the devices communicate with each other easier it gets for the hacker to get a loophole and create an information breach. Data security experts need to understand the breaches and are expected to keep the data secure from any hacking attack.
  • Cloud computing expert-if the devices need to communicate; it needs to be a common place from where they retrieve data and send it. Any computer’s hard drive not being sufficient the information is now getting stored online often called on the cloud. Data is at the apex position of concern to companies this is needed to be done in a proper way for which an expert is required.

 

There are few leading companies which are looking for talent in this sector:

  • IBM
  • PTC – The Product Development Company
  • Savi Group
  • Intel
  • Amazon
  • Red Hat, IncCisco Systems, Inc

IOT is a newly introduced market in IT sector that is rapidly increasing. People who possess the right skillset might provide the job that will give them a bright future.

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Most IoT projects today are unsuccessful

A recent Cisco survey of 1845 business and IT decision-makers in mid market and enterprise companies, conducted in April 2017, found that nearly three quarters of Internet of Things (IoT) projects were not successful.

The top five reasons include:

  • Long completion times,
  • Poor quality of the data collected,
  • Lack of internal expertise,
  • IoT integration,
  • Budget overruns.

These results are not surprising given the immaturity of the IoT solutions, evolving technology standards, and limited expertise among the IoT community.

In light of these survey results, how do you ensure that your first IoT project implementation will be successful? In this post, I’ll share ten best practices for managers planning their first IoT project.

Best Practices for IoT Projects

Best Practice #1 – Solve a problem that someone cares about. Whether it’s a pilot project, or a mini IoT project added to a larger non-IoT project, make the project relevant by addressing a real need. This ensures visibility and support from the organization, whether it is something as simple as time to answer your questions, commitment from management, or contribute resources. Equally important, it gives you a foundation from which to build follow-on projects.

Best Practice #2 – Plan conservatively. As an early IoT adopter, your organization’s capabilities will be limited and the learning curve will be steep. Managers must plan for this in several ways. Don’t try to “change the world”, but instead focus on doing one or two things well. Define the requirements well and resist scope creep. Build in a larger than usual contingency for schedule, resources and cost.

Best Practice #3 – Fix outdated processes and policies. IoT solutions can disrupt existing organizational processes and policies. If you fix the technology but not the processes and policies, you will just get “bad news faster”. Implementing the technology side of IoT is only half the solution. Realize its full potential by updating affected, or in some cases, creating new processes and policies.

Best Practice #4 – Partner for success. IoT solutions affect multiple teams within the organization. Partner with these affected teams early in the planning process to get their requirements, gain their support (knowledge, resources, and budget), and leverage their influence to remove barriers during the execution stages. Partner with your organization’s digital transformation or innovation office, if one exists.

Equally important, partner with IoT solution vendors throughout the process. At this stage of the market, their solutions are still evolving. Work with your IoT vendor at a deeper level than you would with other vendors. Stay in close contact and leverage their product management and technical support teams throughout the project.  Co-design the solution and project with them – tell them what features you like to see, report bugs, and test updated versions of the product.

Best Practice #5 – Augment your capabilities with outside resources. Address gaps in your internal capabilities by leveraging outside resources. Build your IoT knowledge through information shared on industry blogs, publications and analyst reports. Augment your project planning and execution capabilities by contracting with subject matter experts, IoT consultants, and innovation labs.

Best Practice #6 – Address resistance to change. The more disruptive the IoT solution is, the more likely you will face adoption resistance both internally and externally. Whether the changes are small or large, ensure IoT project success with a change adoption plan early on in the project. Identify who is affected and how they are affected, then understand their objections. Craft a plan to address these objections, be transparent and communicate regularly, and implement well before the solution goes live. Be responsive and act with a sense of urgency to any concerns raised during the project.

Best Practice #7 – Define extended project success and goals. During the project planning stage, identify the key success outcomes of the project. Beyond the goals directly enabled by the IoT solution, consider goals around internal capabilities development, gaps identification (processes, policies, technologies, resources, etc.), organization readiness, channel and customer acceptance. Treat your early IoT projects as learning experiences, and use these projects to learn, experiment, uncover challenges, develop the organization and go faster on future projects.

Best Practice #8 – Drive shared ownership and accountability. IoT solutions affect multiple teams across the organization. Because of this, you must establish a structure of shared ownership and accountability to drive project success. Identify and secure the commitment of the critical executive sponsors and  business unit owners. Align the value and relevance of the IoT solution to their team’s goals and needs to drive their ownership.

Best Practice #9 – Establish a learning culture. To ensure that your subsequent IoT projects are successful, you must establish a rapid learning culture right from the start. During the project, establish a process for experimenting, prototyping and problem solving. At the end of the project, document the knowledge and expertise gained, and then develop a system to retain and transfer that knowledge. Identify who the “experts” are, the lessons learned, and project debriefs. Develop a system to share that knowledge across the organization, with solutions vendors, consultants, and other resources.

Best Practice #10 – Be flexible and adapt. Despite careful planning and risk management, your first IoT projects will still be significant learning experiences. You know what you know, but you don’t know what you don’t know. Your planning and risk management is based on what you know. Unforeseen things happen because of the things you, your consultants, or the vendors don’t know. In this type of environment, the project teams should be nimble and agile to respond to the unplanned. Incorporate larger contingencies in project plans. Prepare your sponsors and owners to expect change. Select your project team members for their ability to quickly adapt and learn, as well as for their knowledge and execution ability.

About:

Benson Chan is an innovation catalyst at Strategy of Things, helping companies transform the Internet of Things into the Innovation of Things through its innovation laboratory, research analyst, consulting and acceleration (execution) services. He has over 25 years of scaling innovative businesses and bringing innovations to market for Fortune 500 and start-up companies. Benson shares his deep experiences in strategy, business development, marketing, product management, engineering and operations management to help IoTCentral readers address strategic and practical IoT issues.

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Automation has managed to create quite a buzz in the recent times by dramatically impacting almost every aspect of our lives. With robots replacing laborers in manufacturing vehicles or systems of artificial intelligence (AI) driving cars on our behalf, this extensive concept is concerning almost all the individuals because it is simply killing the job sectors.

Which Industries are Affected the most by Automation?

According to the latest report, automation has the potential to replace factory workers, miners, travel agents and bank tellers. The truck and taxi drivers must also start worrying because the automated technology threatened 2.2 to 3.1 million people all across the globe, who are involved in the transportation sector. Innovative software is developed having the capability of assessing substantial volumes of documents, thus, eliminating most of the professionals in IT. With the advancement of such software programs, individuals with other sorts of occupation such as accountants would also be replaced easily.

While we did understand that automation is depriving people of their jobs, there is another brighter side to the story. Individuals with tech skills are greatly in demand for without them an automation system cannot be installed or operated. However, they are hired in absolutely negligible numbers.

Is the World going to Suffer from Mass Employment?

Well, studies did manifest that automation would adversely impact the varied working sectors but the chances of mass employment are quite unlikely. Although it needs to be duly informed that people, who are technologically incompetent would surely stay behind. Thus, in order to reverse the detrimental effects of automation, it is necessary for the people to have at least some sort of knowledge in the tech field. Even medical personnel and lawyers need to learn the usage of contemporary tools so that they can stay abreast of all these ongoing changes.

Now that we know, which sectors are going to be affected and what are the ways by which we may use automation to our favors, it is time to talk about those professions that have simply no reasons to worry.

Which Industries are not to be Affected by Automation?

Automation would not be able to kill the jobs that require interpersonal skills and empathy. Now can you imagine programmed robots to be psychiatrists helping you to deal with life’s complex issues? Quite hard isn’t it? Well, that is because it is not possible. Consultants communicate and extend affection for treating and curing people. Same goes for teachers imparting knowledge. Well, of course, technological education managed to gain recognition and students are using modern-day gadgets for studying but all of these cannot really be compared to the experience of an educator, whose love nurtures the pupils, making them ready for the outer world. Other examples are the jobs of nurses, personal trainers, makeup artists, hairdressers, etc., which cannot really be affected by automation. 

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The Top Five Things

We're back in fives and all about things. We also included thoughts on making money and the ever present security topic with a nice infographic on the DDoS of things.  

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Enjoy. 

5 Blockchain Technologies To Watch For In 2017

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Interview: 3M's Road to IoT

When you think of 3M you immediately think of Post-It Notes or Scotch tape. If you're old school or local, maybe you know that 3M was founded as Minnesota Mining and Manufacturing Company. But have you ever thought about this company, which has $30 billion in annual sales, employs 88,000 people worldwide and produces more than 55,000 products, as an IoT company? All that material science must have an opportunity in IoT. 

For that we turned to Dr. Jennifer F. Schumacher, the technical supervisor and co-founder of the Computational Intelligence group in the Corporate Research Laboratory at 3M Company. She manages a team and portfolio of 35 new technology Introduction programs which are mechanizing, electrifying, and digitizing 3M materials. Her current initiative is to drive technology platform development in computer vision, machine learning, and deep learning

When people talk about 3M, the first thing that usually comes to mind is Post-it® Notes, and they might not think about 3M at the ready for future advances. How is a materials science company playing in the IoT space?

They say you’re never more than ten feet from a 3M product – that is a lot of potential “things” we could integrate into the IoT space. In fact, we have already digitized the simple Post-it® Notes through the Post-it® Plus App, it integrates physical and digital notes and lets you connect with others to share, for example, outputs from brainstorming sessions.  

What have been some of the roadblocks you and your team have faced in convincing people that a materials science company is also a tech and data science company? How are you working to overcome this?

The data science/machine learning group at 3M is relatively new, and as such, many of the technologies we are developing are not ready for public disclosure yet. Therefore, it is difficult to communicate externally that 3M is actually working on these things, and difficult to recruit talent in this high-demand skillset space. We are addressing this by attending key conferences and interacting more with universities, for example we are sponsoring a seminar series at the University of Wisconsin – Madison.

You have a PhD in neuroscience and an expertise in human vision. How does this apply to your work at 3M when it comes to data science and the IoT?

I initially leveraged my expertise in human vision to develop the 3M™ Display Quality Score – a metric that predicts how well a human will prefer a digital display based on its resolution, contrast, color saturation, etc. I then translated this skillset from understanding how people see, to teaching computers how to see, or ‘computer vision’. The opportunity to learn new things and adapt skillsets makes the job fun.

I believe that in a world full of data, it will be the ones that ask the right questions that have the advantage. Formal training in science has helped me hone my skills in asking the right questions so the most efficient and effective experiments can be carried out first. Much of my formal training has been multi-disciplinary, and I think this breadth of knowledge and cross pollination of ideas and concepts is the key to innovation. 3M’s approach to science is aligned to this approach of cross pollinating ideas and heavy collaboration.

Explain how machine learning can be applied to 3M products?

Machine learning thrives on data. 3M products are, or could be, producing data. We can then leverage the insights from the algorithms to enhance the product itself (for example, the Victory Series™ buccal tubes, which were optimized for fit) or to create an entirely new solution (we have several in the pipeline, so stay tuned!)

What can 3M do to adapt to the current digital economy and help your customers adapt?

There is a global trend of greater economic opportunity in service-based business models rather than product-based. I think 3M will need to start adapting some of these service-based models to adapt to the current digital economy, and we can do so by providing complete solutions (products + services) to our customers.

What do you think the most pressing challenges are when it comes to IoT? How is 3M working to solve these?

The most pressing challenge I see is finding the most impactful applications – there are plenty of ‘cool’ factor solutions or products, but what are the sustainable solutions, the ones that significantly improve the quality of life or enable new capabilities? 3M’s vision statement concludes with ‘3M Innovation Improving Every Life’, so I think we align our research goals with significant global technology trends and sustainability issues that would have this broad impact.

 What excites you most about the future of IoT?

The more trivial decisions that a smart system can take care of, the more time I can spend dreaming and implementing what the next technology to improve lives will be.

 

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Not all Devices are IoT or IIoT

Introduction

Business opportunities created by Internet of Things (IoT) and the Industrial IoT (IIoT) are among the most
debated topics, as these are designed to function in a broad range of consumer and industrial applications.
Manufacturers of IoT components believe in this new trend, but many of them still not understand the essence
of the IoT concept. In reality, not every controlled device is an IoT nor IIoT.

The IoT/IIoT concept is a communication-based eco-system in which control devices, CCTV cameras and
industrial sensors communicate via the Internet with cloud-based computer systems and data sources, and
the result of this process is displayed on a computer screen, smartphone or used for optimal activation of a
process. Through an IoT/IIoT ecosystem you may boost productivity and achieve unique benefits. Examples
of IoT/IIoT include applications such as; remote operation of home appliances, medical devices, check on
availability of a product in a store, warnings of unusual conditions and malfunctions and more.

Leading market research firms already estimate that by 2020 there will be over 20 billion devices worldwide,
defined as part of IoT/IIoT systems. Although the forecasted number is growing every year, it is not clear
whether these figures correctly refer to what can be and what cannot be considered IoT or IIoT. It is strongly
recommended that decision factors such as outlined below shall be taken into consideration.

Devices not considered as IoT/IIoT

In reality not all devices can be accepted to the “IoT/IIoT Club”. Through the following three examples I will
try to clarify the main considerations referring to this topic.
a) You purchased a home air conditioner activated by a smartphone or a web based application. If the
packing label shows “Wi-Fi-Ready”, you can do that, but it will not necessarily make it an IoT, since remote
activation by itself is not a sufficient condition to call it an IoT.
b) You consider to add a vibration sensor to a large water pump or gas turbine to diagnose a malfunction.
This is not an IIoT, as the vibration sensor device is reporting to a special PLC and an ICS computer
which control the operation of that machinery and may stop it if a fault is detected.
c) You purchased a CCTV camera, which is connected to a home computer or a VCR for security
surveillance. This is also not an IoT, because 24/7 loop recording system does not require additional data
available from cloud based resources and not require cloud based computing.

Devices considered as IoT/IIoT

Here are three commercial, consumer oriented and industrial examples, that according to listed explanations
are considered appropriate for being considered as IoT/IIoT ecosystem.
a) Computerized control of a washing machine. The IoT ecosystem using the built-in controller which
support the decision related to optimal starting of the washing process. Consequently, the IoT controller
device communicates with cloud based data sources related to the following considerations:
• Is there a report from the electric company on unusually high loading of the power grid at the
neighborhood? If yes, the washing process is delayed.
• Is it forbidden to cause unusual noise in a residential area such as may be caused by the washing
machine? If yes, the washing process is delayed
• Is there sufficient amount of hot water from the sun-roof boiler as required for the washing? If not, the
activation is delayed until electric heating of the water is completed.

The operation of a solar power plant can be controlled by an IIoT process. After the power plant receives
a request to start supplying power, the IIoT ecosystem system checks the following conditions:
• Is the forecasted intensity of sun-rays during the next few hours adequate to generate the required
energy to the grid? If not, the power plant activation is canceled.
• Are there alternative electric power resources that are more suitable to generate electricity for the
requested period? If yes, the power plant activation is rejected.
• If there are no other alternatives, the solar power plant will be activated with limiting conditions, and
the power grid operator will be advised accordingly.
c) An order is received to purchase a certain type meat for home use. Following this requirement, the
customer can start and IoT-based search using his smartphone:
• In which food chain is this item available, and what is the ticket price
• Which stores are active during the hours when the purchase is required
• The outcome of that process shall be a list of options sent to the customer
From the three examples listed above you may learn that the IoT/IIoT concept is applicable when it is
impossible to perform a simple interaction between the requesting entity and the device which provides the
service. IoT/IIoT systems allow such interactive process through cloud-based data resources.

Is there a reason for concerns?

Definitely yes, because huge amounts of cheap IoT components without professional configuration and
without cyber security measures will flood the internet network and allow cyber-attacks from all directions and
for any purpose. Can ordinary home owners properly configure these devices, replace the default password
and detect DDoS-type security breach? Of course not, and that's the problem.
Today, as a result of strong expectations towards IoT market, none wants to remember the early 2000’s and
the dot.com bubble. Then, well-known and professional companies invested billions of dollars in products
that did not provide benefits for which users were willing to pay. The benefits came only years later, and then
more resources were required to create new business models in order to recover their losses.

Summary

We all hope for huge IoT/IIoT deployments in the future, as this is good for users, vendors and also for
innovation. But…., anyone considering to develop a new IoT/IIoT ecosystem, shall focus on finding a real
need and properly design a cloud-data based solution that delivers significant benefits.
Cyber protection for any IT and ICS architecture consists of three essential elements that are achievable: a)
the use of security technologies, b) strict adherence to policies, and c) careful user behavior. This is also true
for IoT/IIoT ecosystems. Innovative technologies, components and architectures that will include cyber
protection as part of the IoT/IIoT ecosystem at no extra cost, will definitely drive the success.

Photo credit Martin Košáň via Flickr.

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Antarctica inhabits a unique place in the human exploration mythos. The vast expanse of uninhabitable land twice the size of Australia has birthed legendary stories of human perseverance and cautionary tales about the indomitable force of nature. However, since those early years, Antarctica has become a rich research center for all different kinds of data collection – from climate change, to biology, to seismic and more. And although today there are many organizations with field stations running this data collection, the nature of its, well, nature still presents daily challenges that technology has had a hand in helping address.

Can You Send Data Through Snow?

British Antarctic Survey (BAS) – of recent Boaty McBoatface fame – has been entrenched in this brutal region for over 60 years, the BAS endeavors to gather data on the polar environment and search for indicators of global change. Its studies of sediments, ice cores, meteorites, the polar atmosphere and ever-changing ice shelves are vitally important and help predict the global climate of the future. Indeed, the BAS is one of the most essential research institutions in the world.

In addition to two research ships, five aircraft and five research stations, the BAS relies on state of the art data gathering equipment to complete its mission. From GPS equipment to motion and atmospheric sensors, the BAS deploys only the most precise and reliable equipment available to generate data. Reliable equipment is vital because of the exceedingly high cost of shipping and repair in such a remote place.

To collect this data, BAS required a network that could reliably transmit it in what could be considered one of the harshest environments on the planet. This means deploying GPS equipment, motion and atmospheric sensors, radios and more that could stand up to the daily tests.

In order to collect and transport the data in this harsh environment, BAS needed a ruggedized solution that could handle both the freezing temperatures (-58 degrees F in the winer), strong winds and snow accumulation. Additionally, the solution needed to be low power due to the region’s lack of power infrastructure.

 The Application

Halley VI Research Station is a highly advanced platform for global earth, atmospheric and space weather observation. Built on a floating ice shelf in the Weddell Sea, Halley VI is the world’s first re-locatable research facility. It provides scientists with state-of-the-art laboratories and living accommodation, enabling them to study pressing global problems from climate change and sea-level rise to space weather and the ozone hole (Source: BAS website).

The BAS monitors the movement of Brunt Ice Shelf around Halley VI using highly accurate remote field site GPS installations. It employs FreeWave radios at these locations to transmit data from the field sites back to a collection point on the base.

Once there, the data undergoes postprocessing and is sent back to Cambridge, England for analysis. Below are Google Maps representation of the location of the Halley VI Research Station and a satellite image (from 2011) shows the first 9 of the remote GPS systems in relation to Halley VI.

The Problem

Data transport and collection at Halley VI requires highly ruggedized, yet precise and reliable wireless communication systems to be successful. Antarctica is the highest, driest, windiest and coldest region on earth and environmental condition are extremely harsh year round. Temperatures can drop below -50°C (-58 °F) during the winter months.

Winds are predominantly from the east. Strong winds usually pick up the dusty surface snow, reducing visibility to a few meters. Approximately 1.2 meters of snow accumulates each year on the Brunt Ice Shelf and buildings on the surface become covered and eventually crushed by snow.

This part of the ice shelf is also moving westward by approximately 700 meters per year. There is 24-hour darkness for 105 days per year when Halley VI is completely isolated from the outside world by the surrounding sea ice (Source: BAS Website).

Additionally, the components of the wireless ecosystem need to be low power due to the region’s obvious lack of power infrastructure. These field site systems have been designed from ‘off the shelf’ available parts that have been integrated and ‘winterized’ by BAS for Antarctic deployment.

The Solution

The BAS turned to wireless data radios from FreeWave that ensure uptime and that can transport data over ice – typically a hindrance to RF communications. Currently, the network consists of 19 FreeWave 900 MHz radios, each connected to a remote GPS station containing sensors that track the movement of the Brunt Ice Shelf near the Halley VI Research Station.

The highly advanced GPS sensors accurately determine the Shelf’s position and dynamics, before reporting this back to a base station at Halley VI. Throughput consists of a 200 kilobit file over 12 minutes, and the longest range between a field site and the research station is approximately 30 kilometers.

Deployment of the GPS field site is done by teams of 3-4 staff using a combination of sledges and skidoo, or Twin Otter aircraft, depending on the distance and the abundance of ice features such as crevassing. As such, wireless equipment needed to be lightweight and easy to install and configure because of obvious human and material resource constraints.

In addition, the solution has to revolve around low power consumption. FreeWave radios have more than two decades of military application and many of the technical advancements made in collaboration with its military partners have led to innovations around low power consumption and improved field performance. The below image shows an example of a BAS remote GPS site, powered by a combination of batteries, a solar panel and a wind turbine (penguin not included).

FreeWave Technologies has been a supplier to the BAS for nearly a decade and has provided a reliable wireless IoT network in spite of nearly year-round brutal weather conditions. To learn more, visit: http://www.freewave.com/technology/.

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From wind turbines to your washing machine, the IoT is all the rage, and everyone wants their piece of the pie. Monetization and creating business value, not to mention profits, is the holy grail for the IoT. But who is really making money on the IoT and where are the most lucrative opportunities?  For that we turned to Mike Fallon, Senior Advisor of the IoT Transformation Advisory Practice at PTC. Mike is responsible for delivering frameworks to companies that address the how of IoT monetization – specifically for CIOs and other C-suite executives.

How can organizations profit from the IoT? 

Today, we are seeing two primary areas of opportunity for monetizing the IoT: operational efficiencies and new revenue generation. Operational efficiencies are of interest because of how the IoT allows you to organize and use data. In manufacturing, for example, the IoT can help to prevent unplanned downtime, capture real-time insights regarding production and operation, and integrate data across an extended supply chain.

Of even greater interest, right now, is new revenue generation, particularly for hardware companies that see opportunities to introduce digital services into their product offerings. Since the economy has rebounded from the recession, C-level executives and shareholders are very focused on growth. With so many digital transformations happening right now, traditional manufacturers and hardware companies are looking to these digital services as a way to generate new revenue and bring value to those transformations that are underway.

Why is it so hard to monetize the Internet of Things? 

We see a handful of common challenges as we talk to companies about monetizing their IoT strategies. One of the main challenges is developing a strategy and achieving alignment across key stakeholders in the organization. This often carries over to another challenge that we see – companies taking an inside-out approach that prioritizes the provider’s goals over what the end customer needs. Many companies aren’t asking themselves important questions about their strategies, such as, “How do we ensure that the customer or user cares enough about our service to want to pay for it?” The most successful companies are the ones that prioritize the user’s needs and the user experience.

Further, this idea of forming the right strategy can extend to the company’s go-to-market execution. This can be particularly challenging for companies that traditionally sell hardware and are trying to introduce digital services to their customers as part of new offerings. Whenever new offerings or services are introduced, the challenge of how to best market them typically follows.


There is no neat one-size-fits-all monetization model for the IoT, not least because the needs of different companies vary hugely. What are some of the successful models that you have seen, both in consumer and industrial sectors of IoT?

If we look at new revenue monetization, the key question that a company needs to answer as it shapes its business model is, “What is my customer or user willing to pay and how would they like to buy?” Many companies get trapped in what we could describe as more traditional thinking, often asking themselves, “How do I want to bill the customer?” along with other internal-oriented perspectives. These factors won’t be ignored, but the best business models are the ones that customers adopt rapidly because it’s clear to the customer how the software or service helps them do their job easier, enables them to do more than they could previously, and helps them achieve their own goals and objectives.

If companies stick to an inside-out approach that prioritizes their own needs over those of the customer, they’re potentially setting themselves up for failure because they likely aren’t doing all that they can to achieve the customer adoption needed to be successful.

As our publication name suggests, we focus on the Internet of Things, specifically the Industrial IoT. How do you plan to roll your product out for IoT devices? Can you provide examples?  

Right now, the IoT space is being defined by the platform. More and more companies are adopting IoT platforms, like the ThingWorx Industrial IoT platform from PTC, for their IoT initiatives. The best platforms provide companies with the capabilities that they need to be successful with their IoT strategies, such as application enablement, machine learning, industrial connectivity, and, increasingly, augmented reality.

Platforms allow companies to rapidly iterate as they build new IoT applications and solutions. This is crucial right now, as the IoT space is still maturing and companies are determining what works and what is needed in the market. Platforms also help companies future-proof their IoT strategies, as the best platforms will continue to add new capabilities and features to match the evolution and maturity of the market.

PTC makes ThingWorx available to partner companies and solution builders, which, in turn, use the platform to develop new solutions and applications that they sell to end customers. These solution builders can be system integrators, hardware companies, or other software companies. PTC has developed a robust ThingWorx partner ecosystem that offers companies multiple ways to take advantage of the platform and its many benefits.

Additionally, PTC uses ThingWorx for its own internal development of new connected solutions that are sold through its well-known solutions business, focused primarily on computer-aided design (CAD) and product lifecycle management (PLM). An example is the Navigate application from PTC – a PLM-focused solution that has emerged as one of the best-selling solutions in PTC history.

Talk to us about pricing models. What are they, which are the most popular and which ones do you see has having the longest and greatest run?   

The IoT Transformation Advisory Practice at PTC spends a lot of time looking at pricing and business models. One of the things that we most often emphasize to our customers is, once the strategy around deciding what to connect and what data you can collect is set, do not try to copy and paste business models. There is rarely a one-size-fits-all approach when it comes to IoT business models, primarily because each customer could have a different set of needs and/or objectives. At a higher level, this is where companies tend to struggle with generating new revenue through IoT. The pricing models that work start with understanding the needs and aspirations of the user of the service. The company needs to understand what the user is willing to pay for and the specifications that are included.

In today’s world, opting in and out of digital services is commonplace – it could be something as simple as cancelling a Spotify account or it could reach the level of an Industrial IoT service. The pricing models with the greatest and most sustained adoption will fit the evolving needs and expectations of the customer. Because the companies providing the new services will likely have insights into their customers’ operations, they’ll have the opportunity to have access to changing behaviors and shifts in their customers’ business.

As we’ve seen our customers’ journeys evolve, we’ve started to see innovation possibilities in the context of outcome-based design as well. Outcome-based design will continue to be important because it helps to align the design and engineering teams and more closely connects them to user insights that drive more targeted innovation and a faster time-to-market, all in the context of the customer experience.

Who in the organization plays the most important role creating an IoT monetization strategy?

It seems that there’s a common misconception that there’s one person who is most crucial to the development of an IoT monetization strategy. To be successful with a monetization strategy, it can’t fall solely on the shoulders of the CIO, CMO, CTO, etc. There needs to be a cross-functional team that provides input from each member’s respective discipline. IT, marketing, and finance can all play important roles in the development of the strategy, and it’s important that there’s a balance between these perspectives. When I work with customers, establishing a cross-functional view is a critical first step that I help them with.

If the CIO or another executive is in the lead role, he or she should reach across the hall and ensure that team members that spend all day thinking about customers and have direct engagement with customers are part of the team. This could be someone as high up as the CMO or it would be a more focused product marketing manager or director. Marketing will need to be a part of the solution to help guide the go-to-market strategy and execution.

So if a company wants to begin monetizing IoT, what’s the go-to-market approach they should take?

I work with companies that, for centuries, have been successful building their businesses with business models largely driven by the sale of physical products. While aftermarket services have also been a source of value (spare parts, component upgrades, warranty services, etc.), the strategy by the naming associated with “after” has been just that.

My background is working with companies that produce physical products. Now that I am in software, I have gained an appreciation for the importance of communicating in advance the availability of new services. This comes back to the critical role that marketing plays. Traditional and forward-thinking marketing efforts, along with the use of insights that you have from the customer and user are vital to connecting with your market.

As we think about how these new services will be sold, it’s important to consider that most sales executives could be used to getting paid in a certain way for selling a physical product. If the new service that is introduced requires a new selling strategy – perhaps one that requires more support from marketing, inside sales, or aftermarket services – both the learning curve and overall motivation for the sales executive needs to be considered.

If your strategy is to drive rapid adoption of the new service from your customers, at least at the initial launch of the offering, having a team that is dedicated to service with a focused understanding of the offering and a focused incentive or rewards system will typically drive adoption more rapidly and will have access to learnings that you may want to incorporate into the service as you iterate. Remember that your customer’s and user’s needs are in constant evolution and continuing to meet and anticipate those needs is critical to the overall strategy.

Anything else you’d like to add?

To summarize, there are six main components to think about when developing an IoT monetization strategy:

  • Strategy – Understand the objective in terms of a broad adoption strategy versus a more selective, premium offering for selective customers.
  • User-Centric – Approach the strategy from a user-focused perspective and build your design for revenue off of this.
  • What to Charge – Leverage learnings from user-engagement and feedback to understand pricing models.
  • How to Charge – Put a focus on making the service easy to adopt or test out.
  • Go-to-Market – Remember that this is a team game, driven by the cross-functional group that has developed the overall strategy. Tell a user-centric story and consider who sells and how to keep incentive and reward systems from being barriers.
  • Technology – Ideally, the technology that’s offered will have robust capabilities, allow for secure, rapid iteration and scaling, and allow for integration to other business and enterprise systems.
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Internet of Things (IoT) solutions offer tremendous and disruptive value for customers, but sometimes have the unintended effect of adversely impacting the channel that it is sold and serviced through. This results in slow adoption of IoT solutions, even if those solutions have significant and tangible customer value.


Common product-market fit mistakes

While many IoT vendors understand the concept of product-market fit, a common mistake that many product managers make is to overlook or understate the impact of the solution on stakeholders that “touch” the solution (Figure One) beyond the end user customer. When the needs of all the primary and secondary stakeholders are aligned with the solution, market adoption is facilitated. When the needs of these stakeholders conflict, market adoption is slowed or even stopped. 

One example of an external stakeholder is the channel reseller. Many manufacturers incorporate a channel strategy to market, sell and service their products in order to scale the business. The channel can be an one tier channel (manufacturer sells direct to reseller, who then resells it to the end customer) or a two tier channel (manufacturer sells to distributor, who then resells it to reseller, who finally resells it to the end customer). 

Consider an IoT based predictive maintenance solution for commercial heating, ventilation, and air conditioning (HVAC) systems. With this solution, the channel resellers will now know when the parts in the HVAC system are wearing out and a proactive service call is needed. While this assures the customers that their HVAC system will have minimum downtime, it may not be so good for the reseller. Prior to the incorporation of IoT into an HVAC system, channel resellers may have set up a service agreement with the end user where they would perform routine maintenance four times a year. With the IoT solution in place, it may reveal that they only need to come out once or twice a year to do maintenance. The reduced number of visits mean that their revenues from service calls is also reduced. Given this reality, the channel resellers have no incentive to adopt the predictive maintenance solution. 

A second common mistake is to look at product-market fit from a static perspective. In fact, the product manager must look at the product-market fit over the solution’s entire lifecycle from purchase to retirement (Figure Two). At each of the stages over the lifecycle, there may be different people or organizations “touching” the solution and performing a slightly different task in support of common activities. Problems arise when the needs of each party are inconsistent or misaligned.

Conflicts, or friction arise between the buyer, the vendor and the other affected stakeholders when there is misalignment of their needs. These needs may include performance, cost, revenue, operating efficiency, roles and responsibilities. Some of these misalignments may be managed, while others may be more severe and require a solution redesign.


Best practices to remove the friction points


Practice#1 - Expand your product-market fit analysis over the entire solution lifecycle.

As you design your IoT solutions, map out the different stakeholders that touch your product, from the time it leaves your hands delivery to the time it is retired from use. Identify who they are, why the customer buys from them, the tasks they do, the value they add, and how they make their money.

 How does your solution impact the services the channel provides, their value, and their financials?  What is changed and disintermediated?

It is not always possible to avoid disintermediation. But with this understanding, work with the channel to co-create a solution that removes the friction points, creates new value and opportunities.


Practice #2 - Create new value beyond product innovation.

Product managers must think beyond product and technology innovation. IoT solutions can also provide business model, service, and customer experience innovation. When designing the IoT solution with the channel needs in mind, look for opportunities to create these forms of innovation that will provide significant value for all stakeholders.

Customer experience innovation transforms the “customer journey”. It re-imagines how a customer uses a product or service. It uses data collected to create new processes, business partnerships, organizations and technology to support the new journey. Examples include Apple iPod/iTunes changes how we buy and listen to music, Uber changes how we go from one place to another, Netflix changes how we watch television, and Amazon Echo ((“Alexa”) changes how we control devices.

Services innovation transforms how, what and when a service is rendered, and who it is being offered to. It enhances a current value, or creates an entirely new value that was not possible before. A product can also be transformed into a service (e.g. car rentals). Some examples include Software-as-a-Service changes how we buy software, Uber changes how we go from one place to another, and Amazon Web Services changes businesses use IT infrastructure.

Business model innovation. A business model describes how an organization creates and delivers value to its customers. It is defined by nine parts – customer types, value to customer, sales channels, customer relationship types, revenue sources, operating resources, operational activities, key partnerships, and cost structure. Business model innovation transforms these nine parts to create to enhance or create new value to existing customers or to an entirely new customer base. Some example include Amazon Web Services “IT pay for you use” model, ZipCar’s “car sharing” model and Apple iPhone’s app ecosystem model.


Practice #3 - Develop marketing programs that incentivize the channel to pursue “green field” opportunities.

It is not always possible to redesign the solution to eliminate the misalignment between the stakeholders. In this type of scenario, develop marketing and channel programs that allow the channel to target new opportunities where the solution provides a significant competitive advantage. This will allow them to create new revenue streams that will offset any loss of revenues from the current business.

Recalling the predictive maintenance example in which the reseller is reluctant to offer the IoT based solution because their services revenues would decrease. However, the reseller can offer the solution to new customers (those it never had, including those customers who use a competitor’s solutions). The new solution may give them an unique compelling competitive advantage and offset potential revenue decreases when their customers convert to the new IoT solution in the future.


Practice # 4 - Help your channel identify suitable niches within their existing customer base.

While the channel may be reluctant to offer your IoT solution to all of their existing customers, there may be pockets within their base where your solution is in alignment with the reseller’s needs. They may have existing customers where the cost to service them is high, or the revenue impact is minimal, or are considering alternative offerings from other vendors.  Help the channel understand what these opportunities are, identify the target customer profiles, and develop conversion campaigns that allow them to sell to these customer niches.

About:

Benson Chan is an innovation catalyst at Strategy of Things, helping companies transform the Internet of Things into the Innovation of Things through its innovation laboratory, research analyst, consulting and acceleration (execution) services. He has over 25 years of scaling innovative businesses and bringing innovations to market for Fortune 500 and start-up companies. Benson shares his deep experiences in strategy, business development, marketing, product management, engineering and operations management to help IoTCentral readers address strategic and practical IoT issues.

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