The current political events in Barcelona provide us with a barely-needed reminder that we live in changing times.  I was in the city as part of the Trustonic team exhibiting at IoT Solutions World Congress last week and took some time to speak with fellow vendors. I soon saw some fantastic product demonstrations that drew my attention - I wanted to learn more. Frequently though, the response to: “This looks great - how is it secured? How do we know the data is trustworthy?” was a puzzled look and a “It uses our cloud and we secure that” or “It runs on a secure OS”.  Sometimes the response was worse: “It’s a closed network. You couldn’t attack it”.

It didn’t fill me with confidence. Everyone has a secure solution, it seems. But how do we know that it’s secure? Who has validated it? The questions and the perplexed looks continued. I slept uneasily.

I don’t want to criticise the IoT solutions that I saw – they were interesting and point to an exciting future for us all. Unfortunately, securing these solutions isn’t exciting and probably won’t draw a crowd to your stand. It’s rare to see ground-breaking security solutions making the news – consumers just expect it these days. Of course, you can expect a media frenzy if you’re breached. There have been some horrifying examples already and we are still in the early days of this industry. IoT solutions need to be secure by design – or, to put it another way, the components of the solution must already be secure when they are deployed. With the headache (and tedium) of security taken care of, the industry would be free to innovate and dream up even more exciting products.

I was showing an IoT security demo built on a Samsung ARTIK board, which already has Trustonic TEE technology embedded. It showed an IoT device connecting to Amazon Web Services (AWS), cryptographically proving itself to be secure and having a trusted identity, thus enabling it to become automatically registered on the system. Perhaps not as exciting as an IoT boat or sports bike sharing data in real time, but it demonstrated that, by embedding a truly secure OS (one that’s Common Criteria certified and FIPS-140-2 approved) combined with a Root of Trust installed in the factory (think of this like a digital birthmark), an IoT device can be trusted pretty much automatically. Once you have an inherently trusted device, you can be confident that data from its sensors is also trustworthy.

Shakespeare wrote “Love all, trust a few”. So, love all the cool and exciting IoT products – but only trust the few which are truly secure.

How edge computing is poised to jump-start the next industrial revolution.

From travel to fitness to entertainment, we now have killer apps for many things we never knew we needed. Over the past decade, we’ve witnessed tremendous improvements in terms of democratizing data and productivity across the consumer world.

Building on that, we’re entering a new era of software-defined machines that will transform productivity, products and services in the industrial world. This is the critical link which will drive new scenarios at even faster rates of innovation. By 2020, the Industrial Internet of Things (IIoT) is expected to be a $225 billion market.

To jump-start the productivity engine of IIoT, real-time response is needed at the machine-level at scale and that requires an edge-plus-cloud architecture designed specifically for the Industrial Internet. From Google maps to weather apps, we’ve been experiencing the benefits of cloud and edge computing working together in our daily lives for quite some time.

But, what is edge? Edge is the physical location that allows computing closer to the source of data. Edge computing enables data analytics to occur and resulting insights to be gleaned closer to the machines. While edge computing isn’t new, it’s beginning to take hold in the industrial sector – and the opportunity is far greater than anything we’ve seen in the consumer sector, and here’s why:

Real-time data in a real-time world: The edge is not merely a way to collect data for transmission to the cloud. We are now able to process, analyze and act upon the collected data at the edge within milliseconds. It is the gateway for optimizing industrial data. And when millions of dollars and human lives are on the line, edge computing is essential for optimizing industrial data at every aspect of an operation.

Take windfarms for example. If wind direction changes, the edge software onsite would collect and analyze this data in real-time and then communicate to the wind turbine to adjust appropriately using an edge device, such as a field agent and connected control system, and successfully capture more kinetic energy. Because the data is not sent to the cloud, the processing time is significantly faster. This increases wind turbines’ production, and ultimately distributes more clean energy to our cities, increasing the value of the renewable energy space.

Big data, big trade-offs: The harsh and remote conditions of many industrial sites make it challenging to connect and cost-effectively transmit large quantities of data in real-time. We are now able to add intelligence to machines at the edge of the network, in the plant or field. Through edge computing on the device, we’re bringing analytics capabilities closer to the machine and providing a less expensive option for optimizing asset performance.

Consider the thousands of terabytes of data from a gas turbine. Sending this data to the cloud to run advanced analytics maybe technologically possible, but certainly too cost prohibitive to do a daily basis. Through edge computing, we can capture streaming data from a turbine and use this data in real-time to prevent unplanned downtime and optimize production to extend the life of the machine.

What’s Next

Today, only 3% of data from industrial assets is useable. Connecting machines from the cloud to the edge will dramatically increase useable data by providing greater access to high powered, cost effective computing and analytics tools at the machine and plant level.

Consider the fact that for years traditional control systems were designed to keep a machine running the same way day in and day out for the lifecycle of the machine. At GE Energy Connections, we recently debuted the Industrial Internet Control System (IICS), which successfully allows machines to see, think and do and will enable machine learning at scale. To take IICS to the next level, we’re creating an ecosystem of edge offerings to accelerate widespread adoption across the industrial sector. We’re advancing this ecosystem and empowering app developers who want to play a role in driving the new industrial era. 

Currently, to add value to a software system, a developer writes the code, ports it into the legacy software stack, shuts down the devices and finally, updates it. That’s all going to change. We are working on creating an opportunity for any developer to create value-added edge applications. Customers will be able port the necessary apps to their machine without having to shut it down, just like we do on our phones today. Companies will be able to download apps for their needs and update frequently to ensure their business is running smoothly. While no one likes to run out of battery on their smart phone, an outage for a powerplant is far more costly, so the ability to port apps without shutting down devices and being able to detect issues before it occurs will be a game changer.

From wind turbines to autonomous cars, edge computing is poised to completely revolutionize our world. It’s forcing change in the way information is sent, stored and analyzed.  And there’s no sign of slowing down.

Your IoT platform is the heart of your entire IoT solution. Building a reliable and scalable IoT platform is not a piece of cake, which is why these days the market is booming with hundreds of thousands of IoT PaaS (Platform as a Service) vendors. Choosing the right IoT platform for your solution has become more complex than it was ever before. That’s why, in this blog post we have covered some of the best selection criteria to pick the right IoT cloud platform for your needs. Before we delve into this, you first need to know what an IoT platform is. 

What is an IoT Platform?

In simple terms, a platform is a comprehensive set of tools and services which allow developers to build and run an application. However, an IoT platform could have diverse meanings depending on whom you are talking to in the internet of things, IoT ecosystem. For instance, an IoT platform for cloud service providers is their infrastructure, where a developer creates an application. For hardware vendors, an IoT platform is the embedded board where you could write your IoT applications. For the sake of clarity, we are considering an IoT platform as the middleware layer responsible for consuming data from the devices and sensors and providing meaningful and actionable results based on that insight. Generally, an IoT platform offers a device software development kit a.k.a SDK or well defined APIs through which developers and programmers could easily connect to any hardware platform and avail of their cloud-based services.

If you have attended any IoT expo recently, most probably you would have noticed that almost every IoT platform provider claims to be better, faster, safer and smarter than others. Now, how do you make a wise decision in such a competitive landscape and pick the right platform that will reduce your solution risk? Don’t fret, we’ve mentioned below some key selection criteria to choose the right IoT platform. Let us take a quick look. 

Considerations In Choosing The Right IoT Platform

Alas! Today, a cloud IoT platform is opted for based on the effectiveness of the vendor sales pitch. This is mainly because the companies that are trying to get a handle on digital transformation do not possess the requisite knowledge or training in IoT specific areas, and IoT vendors usually woo their customers based on their impressive customer references.  There are some important technical evaluation criteria which are often overlooked.  These need to be kept in mind for choosing the right IoT platform. Let's take a look at them:

#1 Bandwidth

#2 Scalability

#3 Protocol

#4 Security

#5 System Performance

#6 Redundancy and Disaster Recovery

#7 Interoperability

#8 Edge Intelligence 

#9 Budget, developmental skills, and capacity of your in-house team

#10 Your business model and its specific requirements that must be met  

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Believe it or not, but the possibilities that the Internet of Things, IoT brings to the table are countless. The internet of things, IoT continues to be the next big thing in technology, and now the new phase of the internet of things is pushing everyone hard to ask questions about the data collected by sensors and devices of IoT.  

Undoubtedly, the internet of things, IoT will generate a tsunami of data, with the swift expansion of sensors and devices connected to the IoT. The sheer volume of data being produced by the internet of things will rise exponentially in the upcoming years. This generated data can provide extremely valuable insight to figure out what’s working well and what’s not. Moreover, the internet of things, IoT, will point out the issues that often arise and provide meaningful and actionable insight into new business opportunities and potential risks as correlations and associations are made. 

Examples of IoT Data:  

• Data that improves productivity of industries through predictive maintenance of equipment and machinery 
• Data that assists smart cities in predicting crime rates and accidents   
• Data that creates truly smart living homes with connected devices    
• Data that provides doctors real-time insight into information from biochips to pacemakers 
• Data that gives critical communication between self-driven automobiles          

That’s great news, but it’s not possible for humans to monitor, analyze and understand all of this data using traditional methods. Even if they reduce the sample size, it will simply consume too much of their time.  Undoubtedly, finding actionable insights in terabytes of machine data is not a cakewalk, just ask a data scientist. The biggest challenge is to find ways to analyze the deluge of performance data and information that the internet of things, IoT devices creates. The only possible way to keep up with the terabytes of data generated by IoT devices and sensors and gain the hidden insights that it holds is using Artificial Intelligence, commonly known as AI.  

Artificial Intelligence (AI) and IoT    

Artificial intelligence, also known as machine intelligence (MI) is the intelligence that is exhibited by machines or software. John McCarthy, the person who coined this terminology back in 1955, describes it as "the science and engineering of making intelligent machines". In a nutshell, AI is a branch of computer science that emphasizes the creation of an intelligent machine that thinks intelligently, the way intelligent humans think and works and reacts like humans.   

In an IoT environment, Artificial Intelligence (AI) can aid business enterprises take the billions of data points they have and prune them down to what’s really helpful and actionable. The general principle is akin to that in retail applications i.e. review and analyze the data you have collected from different sources to find out similarities or patterns, so that better business decisions can be made.  

To be able to figure out the potential risks or problems, the collected data has to be analyzed in terms of what’s normal and what’s not. Abnormalities, correlations, and similarities need to be identified based on the real-time streams of data generated. The collected data combined with Artificial Intelligence makes life easier with predictive analytics, intelligent automation, and proactive intervention. 

Artificial Intelligence in IoT Applications  

• New sensors will enable computers and smart devices to “hear,” gather sonic information about the user’s ambience   
• Visual big data will allow computers and smart devices to gain a deeper insight of images on the screen, with the new AI app that understands the context of images

These are some of the promising applications of Artificial Intelligence in the internet of things, IoT ecosystem. The potential for highly personalized services are countless and will dramatically change the way people live. For example, Amazon.com can suggest what other books and movies you may like, helping Saavn and Gaana to determine what other songs you may love listening, and your family doctor would receive notification if you’re not feeling comfortable.  

Here Are Some Challenges Facing AI in IoT

• Artificial Stupidity
• Complexity
• Safety
• Ethical and legal Issues
• Compatibility
• Privacy/Security 

What’s Next? 

Gartner has predicted that by the end of next year, 6 billion connected devices will be requesting support, which means that processes, technologies, and strategies will have to be in place to respond to them. It is important to think of connected devices less as ‘things’, but more as customers or consumers of services in themselves. The need for Artificial intelligence, AI will become more prominent at the stage when the number of connected devices and sensors increase manifold.

Hope you find this post helpful. If you did, share it with your friends and colleagues. For AI and IoT Courses Online, you can do some research on Google to find the best institute that suits your needs and budget.

For any query related to this post, you can comment down below. Thanks for your time. 

When looking for a title for this article, I remembered the famous phrase from TV serie Heroes, "Save the cheerleader,  Save the world". Sorry if one more time I abuse of shocking headlines to attract more readers. 

Is the Internet of Thing (IoT) in danger? In light of the latest events I have attended in Berlin and London and news like this "Intel To Amputate Three Modules For Internet Of Things, Including Joule", I really believe  IoT is falling into the Gartner´s Trough of Disillusionment phase  and we need IoT heroes to push it faster towards the Plateau of Productivity phase.

The other part of the article's title, "Save the World," may sound pretentious, but the world need to be save. This year hot spring and summer is confirming even the most disbelieving that Global Warming is very real (Read more at " Global Warming, Christmas and the Internet of Things" and in spite I do not consider that only IoT can save our blue planet, per recent events like "Portugal forest fire", IoT can help and much.

“If we cannot control runaway pollution of our air and water, the world will end”

Source: Ron Lake, Technology Evangelist at Galdos Systems Inc.

Let's go by parts.

Has the Interest in IoT Slowed Down?  Some Symptoms

The IoT no longer fills single events. Now events like Internet of Things World Europe 2017 or IoT Tech Expo Europe in Berlin need help from other technologies like AR/VR AI, Blockchain, or 5G to attract exhibitors and visitors.

The heroes of IoT have lost their past evangelizing enthusiasm. What IoT heroes need to do?

• The IoT Industry heroes need to focus on Customer Value. It is important that IoT heroes address real pain points rather than creating something gimmicky.
• IoT Heroes can not do it alone, partnership with other heroes are absolutely essential for success in the Internet of Things.
• IoT heroes need to be more creative with new Use Cases. As sensors continue to decrease in cost and IoT-specific networks get rolled out, everybody expect the number of use cases to increase exponentially.
• Raise awareness about the major concern, IoT Security
• IoT heroes should follow the trends by pairing connectivity with AI/Blockchain/AR/VR heroes

How can IoT save us from world challenges?

Gary Atkinson, Director of Emerging Technologies at ARM, identifies five main challenges that the planet is heading towards:

1.       We’re running out of agricultural land

2.       Water is our rarest commodity

3.       Energy needs to be cheaper to be efficient. 

4.       Healthcare is a growing problem

5.       Transport - Everyone will be able to afford cars, but won’t be able to afford to pay for fuel.

Save IoT, Save Agricultural land

If we all expect that IoT Agricultural solutions will be cheap, will have a long-lasting battery (+10 years), and will emit signals at least 5 miles, the smart farming will be a reality and we will not have excuses to save agricultural land.

Additional info:

• “Smart Farming Can Make Food Supply Uncertainty and Volatility a Thing of the Past”
• Some companies to follow:  Sigfox, Eightless, Enlight, Libelium, On Farm, John Deere, Trimble, and Valley Irrigation.
• Agri-Tech East is an independent, business-focussed cluster organisation, to improve the international competitiveness and sustainability of plant-based agriculture and horticulture.
• World Agri-Tech is held annually in London and San Francisco and is acclaimed as the most international gathering of agribusiness leaders, VC investors and agri-tech innovators. The next summit will take place in London on October 17-18, 2017. Find the full details here.
• Image analysis and artificial intelligence (AI) will change dairy farming
• Farm from a Box provides communities with the tools required to grow their own food and earn an income.
• Are you interested in invest in Agritech?, take a look at “How To Invest In Agritech”

Save IoT, Save the Water

Water is currently the most precious natural resource on planet Earth.

On the occasion of World Water Day, tech giant IBM entered into a pact with Ireland’s Dublin City University for a collaborative R&D pilot to leverage the internet of things (IoT) technology to help protect water.

The IoT could for instance make desalinisation coming to a cost-effectiveness point. India uses mostly a pivot irrigation system, which means 30% of land is lost and 50 to 60% of water is lost by evaporation. The switch to tape based irrigation could save 2/3 of the water used.

Back in 2014, HydroPoint Data Systems utilised the Internet of Things (IoT) to help with water conservation efforts. According to the company and its partners, this system saved local people some $137m in expenses and 15 billion gallons of water in the first year alone.

Additional info:

• Water And The Internet Of Things: 2017
• How the Internet of Things Helps in Water Management
• The Internet of Things: A Water-Saving Revolution?
• How can IoT be used in smart homes to save water?
• Conserving Water with IoT Technology

Save IoT, Make Energy renewable and cheaper

Smarter, more efficient energy consumption it’s been the dream of environmentalists for decades. Now, it’s possible through the power of Internet of Things devices. Because of their connection capabilities, energy consumption such as the power in a commercial building or even smart home can be constantly monitored and adjusted.

Energy consumption could be reduced thanks to a smarter consumption and the implementation of micro generation storage. Knowing that lightning is the second biggest consumer of energy (after motors), and that there are about 1 billion streetlights in the world, upgrading streetlights infrastructure would strongly impact the world consumption.

Experts said that thanks to the Internet of Things, we can move from about 13 percent aggregate energy efficiency to 40 percent in the next 25 to 30 years.

Creating a new connected economy powered by renewable energy will cause a temporary surge in productivity worldwide as grids are modernized and infrastructure is rolled out. Installing wind and solar is labor intensive, for example, so for two generations, people will have plenty of work to do.

Additional info:

IoT company SkyGrid which is based in Melbourne and Sydney, is developing a smart hot-water system in partnership with hot-water company Quantum Energy. The aim is to intelligently control when a building’s hot-water systems are switched on, so that energy isn’t wasted heating water when no one is around to use it – something that currently wastes as much as 50% of a system’s power.

• EnLight works on streetlight efficiency
• Freestyle has partnered with engineering firm PowerTec, on an intelligent energy grid for Kangaroo Island in South Australia. Sensors and controllers in the grid intelligently manage energy sources to sway energy consumption towards renewables without sacrificing the reliability of the supply.
• Top 10 Internet of Things Companies Disrupting the Energy Industry -
  • PingThings is combining big data and machine learning to change the way that state utility grids operate.
  • Actility employs IoT and machine-to-machine (M2M) communication to reinvent the way the energy sector operates.
  • Tibber is a personal assistant that can regulate a house’s energy consumption and buy more energy if the need arises.
  • Wattz is implementing solar power solutions that rely not on the sun’s light, but capturing ambient light from LED and compact fluorescent bulbs to recharge the batteries in IoT devices.
  • Positive Energy uses IoT devices and software to optimize the functional efficiency of industrial buildings and smart homes alike. 
  • Smappee allows users to turn devices on and off remotely. It also has the capability to monitor solar panel output values and gas and water usage in real-time.
  • GasZen allows customers to convert their traditional “dumb,” or non-networked, propane tanks into smart tanks that can be monitored by both the gas provider and the user remotely. 
  • 75Farenheit, beyond their ability to predict and adapt to changing climates, they offer analytics and suggestions on how to make the operation of a building more efficient.
  • Inspire Energy is giving citizens the power to become a part of the growing clean energy movement.
  • Verdigris Technologies primary target is energy consumption and waste.

Save IoT, Save Healthcare

Despite incredible improvements in health since 1950, there are still a number of challenges, which should have been easy to solve.

In a 2016 report by Deloitte we can read “Change is the new normal for the global health care sector. As providers, payers, governments, and other stakeholders strive to deliver effective, efficient, and equitable care, they do so in an ecosystem that is undergoing a dramatic and fundamental shift in business, clinical, and operating models. This shift is being fueled by aging and growing populations; the proliferation of chronic diseases; heightened focus on care quality and value; evolving financial and quality regulations; informed and empowered consumers; and innovative treatments and technologies — all of which are leading to rising costs and an increase in spending levels for care provision, infrastructure improvements, and technology innovations.”

The IoT has brought many exciting advances to healthcare, improving patient experiences, increasing the quality of care provided, as well as updating and streamlining healthcare operations. From digital assistants to ‘smart’ medicine bottles, a new wave of connected devices could help people live independently for longer.

According with Goldman Sachs, IoT functions would produce an estimated $32.4 billion in annual revenue (45% from remote patient monitoring, 37% from telehealth, and 18% from behavior modification). But Healthcare IoT not only increases revenue, IoT reduces this cost by offering a more cost-effective method of managing chronic illness. The $305 billion estimated savings is accounted for by a combination of chronic disease management and telehealth.

Additional info:

• The 2020 Health Care Climate Challenge is a GGHH initiative to mobilize health care institutions around the globe to protect public health from climate change.
• 3 Ways the Internet of Things Is Improving Healthcare
• Healthcare Can Save Big, Win Big in IoT
• IoT for healthcare: Three use cases
• 6 Applications of IoT in the Healthcare Industry
• A guide to healthcare IoT possibilities and obstacles
• Predictive Health Care: How the IoT Can Save Lives
• The IoT is helping cut US healthcare costs by the billions
• Goldman Sachs Report: How the Internet of Things Can Save the American Healthcare System $305 Billion Annually

Save IoT, Save Transportation 

I leave this topic for a special post in the coming months.

Key Takeaway: Save IoT and IoT will enable Save the World

As I have commented many times the IoT is a Journey. Those who have been more time in the race know that there are easier and other more difficult stages, but not for that reason we abandon the hardness of climbing one of them.

 If we have not yet achieved that the IoT has a unique definition, it is not surprising that the term could disappear for reasons of business marketing. Nor does it matter that technologies such as AI, VR / AR, Robots, Blockchain, join to IoT to solve world problems. We could call it "Unified Information Technology".

The World of 2017 has some immense problems but It is scary to think about the challenges it for the next 10, 20 50 years. As we have seen IoT must play an important Enabler to Save the World. 

IoT heroes, save the IoT, Save the World.

 Thanks in advance for your Likes and Shares

Thoughts ? Comments ?

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.

The digital revolution has created significant opportunities and threats for every industry. Companies that cannot or do not make significant changes faster to their business model in response to a disruption are unlikely to  survive

adopt the ones which makes more sense to your business.

Finally you know when you are digital transformed?

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.

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.

It’s not uncommon to drive about any major city at night and see many buildings illuminated despite the fact that the workers went home hours earlier. Likewise, manufacturing plants the world over often have equipment unnecessarily consuming energy during idle periods. Power plants create and store energy everyday and use energy distribution grids to distribute energy to users, but are they doing it “smartly?”

With rising concerns about global warming, this immense waste of energy undoubtedly hurts the environment, but it also hurts business. Offices, manufacturing plants, commercial spaces and power grids all stand to benefit financially from better and “smarter” energy management.

How IoT Reduces Energy Usage for Businesses and Manufacturing

In his article, “Report: Lofty Energy Management Goals Far Ahead of Reality,” (Panoramic Power, August 5, 2015) Jon Rabinowitz points out that most companies receive data on their energy usage only at the end of each billing cycle, which is usually a month at a time. By incorporating Internet of Things (IoT) technology, energy consumption data will be available in real-time, and energy-reducing measures can be implemented as soon as a problem gets detected (rather than waiting until the end of the month). Integrating smart devices through IoT technology will provide greater visibility into energy usage and help both industrial and commercial enterprises save energy, and as a result, save money.

Starting with simple, smart and low cost sensors, like User to User Information (UUI) and Feature Driven Development (FDD) devices, businesses can reduce energy usage and cost by dimming lights, turning off unnecessary equipment and improving the use the cooling/heating apparatus. Software that collects and correlates granular usage data, performs analytics and then converges information to increase efficiency will make manufacturing plants “smarter,” and thus more cost-effective.

Local and remote sensors that detect points of inefficiency quickly and perform triage to decrease waste will also reduce the need for maintenance as constant monitoring will detect small issues before they become big problems. Continuous optimization through 24/7 monitoring will assure that energy is not wasted during slow periods in between high-usage spans, while maximizing the use of energy-demanding equipment at critical times.

Specific Use Cases – Energy Production and Management

• General Electric’s Asset Performance Management software connects disparate data sources in power plants, enabling data analytics to guide energy usage and to increase efficiency (“10 Real-Life Examples of IoT Powering the Future of Energy,” Internet of Business, Freddie Roberts, Oct. 7, 2016).

• Duke Energy, a Florida-based electric power holding company, has developed a self-healing grid that automatically reconfigures itself when power goes out. Using digital smart sensors at sub stations and on power lines, the system automatically detects, isolates and reroutes power in the most efficient way when problems occur (Roberts).

• Pacific Gas & Electric Company is testing drones as a means to monitor and evaluate electric infrastructure systems in hard-to-reach areas. The ease of access will allow more frequent and consistent monitoring and drastically reduce the amount of methane leaks and other unwanted disruptions. (Roberts).

Energy Saving in the Auto Sector

Nissan (manufacturer of the world’s best-selling electric car, the Leaf) and ENEL (Europe’s second largest power company) have teamed to develop an innovative vehicle-to-grid (V2G) system that creates mobile energy hubs, which also integrates the electric cars and the power grid. The system allows Leaf owners to charge at low-demand, cheap-tariff periods, while allowing owners to use the energy stored in the car’s battery to power their home during peak periods, or when power goes out. Owners can store excess energy, or return it to the grid, making the entire system more efficient for everyone (“Nissan and ENEL to test first Grid Integrated Vehicles in Denmark,” Copenhagen Capacity, December 11, 2015).

Conclusions

As evidenced by these specific use cases, IoT technology is making energy-intensive systems in power generation and in manufacturing far more efficient. It’s good for the environment, but it’s also good for business. Intelligent implementation of energy saving technology stands to benefit every business, from small commercial enterprises to the largest power producing utility companies in the world. It’s time to make the move to smarter energy usage, for both the environment and for your bottom line.

Originally published on the Unified Inbox blog

About the Author

Richard Meyers is a former high school teacher in the SF Bay Area who has studied business and technology at Stanford and UC-Berkeley. He has a single-digit handicap in golf and is passionate about cooking, wine and rock-n-roll.

The world is full of normal people like you and me, but I love to think that superheroes live between us and I dream that maybe someday I could become one of them and make a better world with my super powers.

In the universe of superheroes fit gods, mutants, humans with special skills, but also the special agents. I found fun to find similarities between this fantastic world and the world of IoT platforms.  Compare and find a reasonable resemblance between IoT Platforms and Superheroes or Super villains is the goal of this article. Opinions as always are personal and subject to all kinds of comments and appreciations. Enjoy, the article.

About IoT Platforms

Many of my regular readers remember my article “It is an IoT Platform, stupid !.”. At that time, per Research and Markets, there were more than 260 IoT platforms, today some sources speak about 700 IoT platforms. I confess, I have not been able to follow the birth, evolution and in some cases death of all IoT platforms out there. I think that many enthusiasts like me also have given up keeping an updated list.

I cannot predict which IoT platforms will survive beyond 2020, or which will be the lucky start-ups that will be bought by big companies or will receive the investors' mana to become a Unicorn, but I like to speculate, and of course, I have my favourite winners and unlucky losers.

About my Own Methodology

Some reputed analysts have adapted their classification methodologies of IT solutions to put some order and consistency into the chaotic and confusing Internet of Things (IoT) platforms market. But given the moment of business excitement around the IoT, have appeared new analyst firms focused on IoT who also wanted to contribute their bit and at the same time make cash while this unsustainable situation lasts.

After reading numerous reports from various sources on this topic, talking to many IoT platform vendors and seeing endless product demos, I have decided to create my own methodology that includes a questionnaire of near 100 questions around different areas: technical, functional, business, strategy, and a scoring mechanism based on my knowledge and experience to make justified recommendations to my clients.

About Super Powers Methodology

But I also had defined an alternative Methodology based on Super Powers.

Super Heroes and Super Villains usually gain their abilities through several different sources, however these sources can be divided into four categories. The Super Powers methodology is based on these four categories of Power Sources.

• Mind Powers – Powers with notable mental abilities. Companies like IBM Watson IoI or GE Predix are notable examples.
• Body Powers – Powers that are gained from genetic mutation. Companies like Microsoft or Amazon mutate to IaaS / PaaS IoT platforms.
• Spirit Powers –  Powers gained over time through extensive investment, and are easily obtainable by companies without the risk of horrible mutation or disfigurement. PTC Thingworx, Software AG/Cumulocity or Cisco-Jasper are examples.
• Artefact Powers –  Powers gained abilities through ancient objects such as networks, or hardware. Incumbent Telcos M2M Platforms, Telco vendors like Huawei, Nokia or Ericsson, and Hardware vendors like Intel IoT platform, ARM Beetle or Samsung Artik are examples.

For each Power Source category, Super Powers are divided into different levels of power that depend on how strong, or unique, their abilities are.

• Level 0 -  with useless, or minimal abilities.
• Level 1 -  they are still particularly weak compared to the higher levels.
• Level 2 -  have developed their powers to a certain point. About 75% of the platforms belong to this class,
• Level 3 - Mostly are most commonly amateur heroes or sly villains.
• Level 4 - Some of the most unique with a wider variety of powers.
• Level 5 - these fellows are seasoned veterans of their abilities, capable of using them without even needing to concentrate.
• Level 6 - Only a few beings are classified under this level, and their powers are that of being able to control multiple aspects of IoT reality.

Whatever the source of power was, I add Sandy Carter´s recommendation: If you want to become an Extreme Innovator you also need Super Intelligence, Super Speed and Super Synergy.  

About Super Heroes and Super Villains

Previously in “Internet of Things: Angels & Demons” and “Internet of Things – Kings and Servants” , I identified some IoT Platform companies as potential superheroes. What was certain is that we knew who the supervillains were. Governments, organizations and business giants that try to control us, manipulate us and frighten us with their economic, political and military powers.

Deciding which superhero can help you more or what superpower is more important for your business is an extremely important milestone in your IoT Strategy.

I've defined the six types/categories of superheroes / IoT Platforms:

a)The superhero whose power is a birthright like Amazon AWS IoT (Superman) or GE Predix (Magneto/Professor Xavier).

b)The superhero whose power is the result of power acquisitions like PTC Thingworx (The Flash) or Cisco Jasper-Parstream (Spiderman) or Autodesk Fusion Connect (FireStorm).

c)The superhero whose power is made possible by technology like Oracle IoT (Iron Man) or SAP Leonardo(Green Lantern). 

d)There is the superhero who doesn't have any superpowers but who is a superhero by extremely intensive training like Batman (Ayla Networks) or Black Widow (Exosite) or LogMeIn-Xively (Hawkeye)

e)The superhero who obtains his/her powers due to some supernatural event like Satya Nadella named new CEO for MSFT IoT Azure (Thor) or Telit DeviceWise (Dr. Manhattan) or Google acquisition of Nest (Hulk)

f)Finally, there is the superhero, usually a sentient android, who was created by a human like IBM Watson IoT (Vision) or a normal human playing with magic like Salesforce IoT Cloud Einstein (Dr Strange) or leader of a young team like Hitachi Data System(Most Excellent Superbat). 

“Do you agree with my classification system for superheroes and superpowers?”

Although the number of superheroes and supervillains is enormous (more that the IoT Platforms Universe), it would take me a long time to assign each one of the IoT platform a single superhero or supervillain. Since I do not think many companies are willing to pay to know who represents them better, at least I have done a partial and fun exercise.

The Bottom Line 

If you are an IoT Platform vendor, you could be doing yourself some questions right now:

-          If I could be a Superhero what would it be?".

-          Worth to acquire a Super Power or reach an upper level to convince customers I am their Superhero?

And remember …

“With power comes responsibility; with great power comes great responsibility”

Although the number of superheroes and supervillains is enormous (more than the IoT Platforms Universe), it would take me a long time to assign each one of the IoT platform a single superhero or supervillain. Since I do not think many companies are willing to pay to know who represents them better, at least I have done a partial and fun exercise.

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