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Iot and IIoT has made it a long way in the past several years. In fact, according to Forbes, trillions of dollars are at stake as the Industrial Internet of Things rolls out over the next decade. But, has the multi-tillion dollar trend lived up to the hype?

It could be many more years until certain industries reach the levels described in the hype.  Here’s the industries you should keep your eye on when it comes to IIoT technology.

The Internet of Things and the Industrial Internet of Things (IoT and IIoT, respectfully), widely encompasses many concepts, technologies, and products, but can generally be described as:

  • A system that contains wired or wirelessly connected components which relay data that can be analyzed or used to control an output of the system
  • A network that allows for automated information exchange between two devices
  • A vision where any and all systems are connected to gather masses of data that will lead to overall improved performance, insights, and control

As of 2018, we most commonly see IoT being used for location tracking, remote monitoring, and preventative maintenance.  Yet, for IIoT the most common application is preventative maintenance. Many of these IIoT systems report back to a control interface, and are not completely automated control loops that are self-evaluating or self-improving.

 

There are some industries in particular that stand out when looking at the IIoT.  We looked at trends that will progress through the end of 2018 into 2019, and asked the following questions.

  1. What industries will be most affected by IoT solutions?

According to BI Intelligence, the ‘Manufacturing’ and ‘Transportation and Warehousing’ industries have received the highest amount of investment in IoT to date.  These investments, totaling $230B between the two industries over the past few years, will continue to drive impressive progress in the development of IoT solutions. 

  1. Who will be the key players in IIoT Solutions in 2019?

We are currently witnessing a race to capture the IIoT market.  AT&T is collaborating with Honeywell, Verizon offers a machine-to-machine (M2M) management platform called ThingSpace, and startups like Uptake Technologies are raising absurd amounts of capital to compete with existing analytics giants. Uptake alone has raised $218M since 2015, and specializes in analytics of complex data sets. 

Nearly all of the corporate giants you would expect to have a stake in the race are putting serious resources behind their efforts.  GE is offering Predix, and end-to-end Industrial IoT Platform, and has incorporated capabilities like Predix Edge to allow for edge computing within the platform.  Siemens offers their own Industrial IoT platform called MindSphere, and Bosch is also getting in on the action now offering their IoT Suite publicly available on AWS Marketplace. Further, Schneider Electric developed WonderWare and SAP offers Hana.

We expect that through 2019 we will see more partnerships develop, offering cross compatibility between the many platforms which are available today.

  1. What further developments in IIoT can we expect in the near future?

Security will continue to be a major focus for all providers and users of the IIoT.   In a recent publication Steve Watson, CEO of VTO Labs, explains “security and specifically the ability to detect compromised nodes, together with collecting and preserving evidences of an attack or malicious activities emerge as a priority in successful deployment of IoT networks.” This ability to detect and preserve evidence of a cyber-attack will not only need to occur through edge computing, but it will also need to be maintain its integrity with interoperability of different systems that are linked together.

Given the amount of investment we are seeing in the ‘Manufacturing’ and ‘Transportation and Warehousing’ industries we expect to see many breakthroughs in both cyber security for the IIoT and interoperability between the many IIoT platforms. Looking into 2019 we can expect to see more partnerships between major sensor providers and network providers, such as the AT&T Honeywell collaboration we saw in 2018. With more interoperability and collaboration, 2019 may be the year that we see the major breakthroughs in IIoT we’ve been expecting.

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It is still the early days for autonomous trucks, and a report by Gartner estimates that by 2021, less than 1% of long-haul, over-the-road freight will be carried by driverless trucks. 

The trucking business already leverage the advantages of using mobile technologies, but the volatile nature of rising labor rates, fuel costs, increased traffic, and a changing regulatory environment, continuously making operations challenging.

Inefficiencies caused by lack of visibility create considerable costs. However, with the help of disruptive technology such as Internet of Things (IoT), visibility into equipment, assets, personnel, and transactions, enterprises can better support crucial operations in real-time and improve operational efficiency and performance.

By leveraging enterprise IoT asset intelligence, the trucking can tackle problems with solutions powered by IoT. 

Problem # 1: The traditional transportation model lacks the operational efficiency of the trucks.

The Solution: IoT in transportation has empowered trucking business owners to improve the operational efficiency of trucks by real-time monitoring and tracking of the fleets. With real-time monitoring capability, decision-makers can make out-of-the-box business decisions. Whenever there is an engine oil leakage, an alert is sent well before time indicating about the threshold it has reached, that’s how the internet of things makes a difference in the trucking business.

 

Problem # 2: The consumption of fuel was increasing and congestion problems start arising. 

The Solution: Usually, the traditional transportation business models consumed energy affluently due to improper route management, so an optimized route management was crucial to building a sustainable trucking business. With the help of real-time field data, efficient fleet route management eliminated almost 175 grams of carbon emission, produced by every extra mile traveled by any vehicle. With the manual monitoring getting expensive and inaccessible, the IoT enabled heat and motion sensors to utilize the energy resources more smartly, which provides huge value to the administrators. 

 

Problem # 3: Tracking of the public transport became a serious issue.

The Solution: Managing the traveling from one point to other was possible by the traditional public transport but not the tracking real-time location of the vehicle and knowing when it will arrive at a particular stop. With the help of real-time sensor data, selecting the optimal route based on real-time conditions got easy, resulting in better public transit management. The IoT sensors tell where the traffic is jammed up and reduces the congestion and find an alternate route became easy which consumed the energy and time. IoT sensors tell where the traffic is jammed and convey the alert to the fleet and find an alternate optimized route to save time and energy.

 

Problem # 4: Increase in operational cost and damage to the infrastructure.

The Solution: From the traditional transportation model, loading the exact amount of load in the trailers was near to impossible. So, a proper check on the vehicles like size, weight, and type of vehicles is done and the load in the trailer is measured in real-time using weight sensors. Through IoT and smart devices, the overloaded vehicles can be identified and can be partially unloaded to evade fines. From the real-time tracking, alerts are sent well before time so that an optimized efficiency can be achieved.

 

Problem # 5: No advance alerts and availability of parking slots.

The Solution: The integrated smart transportation system tells the real-time information of the driver as well as the vehicle and warns them about the potential engine outbreaks. IoT in transportation can also ensure the smart parking, which tells about the lots that are presently available in real-time. Also, the multi-level parking system helps in reducing the operating and maintenance expenses. IoT sensors help in increasing the safety, comfort, and efficiency in driving and parking.

 

CONCLUSION:

Over the several recent years, the Internet of Things has unlocked a box of new opportunities in the trucking industry and has undoubtedly advanced beyond recognition. IoT is all about digitally connecting devices and analyzing the data to predict future outcomes or possibilities and the transportation industry is at a point where it can leverage the full potential of this disruptive technology.

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A field guide describing the 5 approaches to industrial IoT platform development and how to know which approach is the right one for your enterprise based on your goals, requirements, constraints, and where you are today in your digital transformation journey.
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What is a smart city? The answer depends on who you ask. Solutions providers will tell you it’s smart parking, smart lighting or anything to do with technology. City officials may tell you it’s about conducting city business online, such as searching records or applying for permits. City residents may tell you it’s the ease of getting around, or about crime reduction. Everyone is right. A smart city, built properly, will have different value for different stakeholders. They may not think of their city as a “smart”city. They know it only as a place they want to live in, work in, and be a part of. To build this type of city, you have to first build the smart city ecosystem.

 

A smart city is built on technology, but focused on outcomes

A scan of the various smart city definitions found that technology is a common element. For example, TechTarget defines a smart city as “a municipality that uses information and communication technologies to increase operational efficiency, share information with the public and improve both the quality of government services and citizen welfare”. The Institute of Electrical and Electronics Engineers (IEEE) envisions a smart city as one that brings together technology, government and society to enable the following characteristics: a smart economy, smart mobility, a smart environment, smart people, smart living, smart governance.

But what does a smart city really do? Our scan of smart city projects worldwide showed that initiatives fell into one or more smart city “outcomes” (Figure One).

Figure One. Smart city projects are aligned to one of seven outcomes.

 

As a starting point, we define a smart city is one that uses technology extensively to achieve key outcomes for its various stakeholders, including residents, businesses, municipal organizations and visitors.

 

The smart city ecosystem framework

Figure Two shows our framework for a smart city ecosystem. A vibrant and sustainable city is an ecosystem comprised of people, organizations and businesses, policies, laws and processes integrated together to create the desired outcomes shown in Figure One. This city is adaptive, responsive and always relevant to all those who live, work in and visit the city. A smart city integrates technology to accelerate, facilitate, and transform this ecosystem.

Figure Two. The smart city ecosystem framework.

 

Four types of value creators

There are four types of value creators in the smart city ecosystem. They create and consume value around one of the outcomes listed in Figure One.

When people think of a smart city, they automatically think of services provided by municipal and quasi-government agencies, such as smart parking, smart water management, smart lighting, and so on. In fact, there are three other value providers and users that co-exist in the smart city – businesses and organizations, communities, and residents.

Businesses and organizations may create services that use and create information to create outcomes for its stakeholders. Some examples of “smart” businesses include Uber and Lyft for personal mobility, NextDoor for information sharing, and Waze/Google for traffic and commute planning.

Communities are miniature smart cities, but with very localized needs. Some examples of potential smart communities include university campuses, office parks, airports, cargo ports, multi-dwelling unit (MDU) or apartment complexes, housing developments/neighborhoods, business districts and even individual “smart” buildings. They have needs for smart services that may be tailored specifically for their stakeholders.

Residents or individual citizens are also smart services providers in the smart city. A resident living near a dangerous street intersection can point a camera at the intersection and stream that information live to traffic planners and police. Residents place air quality measurement sensors on their properties to monitor pollution and pollen levels during certain times of the year, and make that information available to other community members. Residents can choose to make these smart services temporary or permanent, and free or fee based.

 

The Smart City is built on layers

A smart city is an ecosystem comprised of multiple “capability layers”. While technology is a critical enabler, it is just one of many foundational capabilities that every smart city must have. No one capability is more important than the rest. Each capabilities plays a different role in the smart city. These capabilities must integrate and coordinate with each other to carry out its mission.

 

Value layer. This is the most visible layer for city residents, businesses, visitors, workers, students, tourists and others. This layer is the catalog of smart city services or “use cases”, centered around the outcomes (Figure One), and offered by value creators and consumed by the city stakeholders.

Innovation layer. To stay relevant, value creators in the smart city must continuously innovate and update its services for its stakeholders. Smart cities proactively facilitate this through a variety of innovation programs, including labs, innovation zones, training, ideation workshops, skills development and partnerships with universities and businesses.

Governance, management and operations layer. The smart city creates disruption and results in digital transformation of existing processes and services. Smart city management models must integrate a new ecosystem of value creators and innovators. They must plan, support and monetize new business models, processes and services. They must upgrade their existing infrastructure and management processes to support “smart” services. Finally, they must measure the performance of the city with a new set of metrics.

Policy, processes, and public-private partnerships, and financing layer. The smart city doesn’t just magically appear one day. An entirely new set of engagement models, rules, financing sources, and partners are required to build, operate and maintain the smart city. Cities must develop a new set of “smart” competencies in order to get and stay in the “smart city game”.

Information and data layer. The lifeblood of the smart city is information. The smart city must facilitate this in several ways, including open data initiatives, data marketplaces, analytics services, and monetization policies. Equally important, they must have programs that encourage data sharing and privacy policies to protect what and how data is gathered.

Connectivity, accessibility and security layer. People, things and systems are interconnected in the smart city. The ability to seamlessly connect all three, manage and verify who and what is connected and shared, while protecting the information and users is crucial. The highest priorities for smart cities are to provide a seamless layer of trusted connections.

Smart city technology infrastructure layer. Most people automatically think of technology when talking about smart cities. The smart city technology infrastructure must scale beyond the traditional municipal users and support a new class of value creators, and city/user stakeholders.

 

Leveraging the smart city ecosystem framework

The smart city is a complex ecosystem of people, processes, policies, technology and other enablers working together to deliver a set of outcomes. The smart city is not “owned” exclusively by the city. Other value creators are also involved, sometimes working in collaboration and sometimes by themselves. Successful and sustainable smart cities take a programmatic approach to engage its stakeholders across the ecosystem.

Our research has found that many cities are not taking an ecosystem approach to smart city projects. This is due in part to smart city projects being managed by the Information Technology (IT) organization where their charter is on systems development and deployment. In contrast, more experienced smart cities manage their smart city programs through internal cross functional “Transformation” or “Innovation” organizations.

Regardless of where cities are in their smart city journey, they must get ahead of the “curve” with smart city projects. They begin by thinking in terms of building the broader ecosystem in order to create a sustainable and scalable smart city. Key next steps include:

  1. Understand the smart city ecosystem framework and tailor it to the realities of their specific city. Incorporate this model into the development of their smart city vision, strategy and execution plans.
  2. Relative to the smart city ecosystem framework, identify current capabilities and gaps across the various layers. Understand what is needed to support the four types of value creators.
  3. Evaluate existing and new smart city projects and initiatives against the ecosystem framework. Use this framework to identify what is missing from the project plans and what is needed to make the projects fully successful.
  4. Prioritize and develop competencies across the various ecosystem layers. A smart city requires new skills and competencies. Augment existing capabilities through strategic partnerships and contracting with service providers, as required.

 

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.

This post was co-authored with Renil Paramel, an IoT Innovation Catalyst, Strategist and Senior Partner at Strategy of Things.

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I think so.  

If you run a manufacturing factory, you have just a handful of variables that let you cut costs. Chief among them is energy use. Energy conservation saves money obviously, but turning off one switch at a time compared to controlling thousands, that would be interesting.

A lot of efforts are taken to save energy historically, for instance, use of motion sensitive bulbs, limited time use of air conditioners, or cutting the number of shifts and functioning hours is another way to save energy costs. But those actions require productivity/OEE boosting focus of the facility rather than effect energy conservation. Energy conservation is a byproduct of those efforts.

Adding IoT on the other hand, can enable direct energy savings for the smart factory of today.

Many experts recommend IoT-based real time monitoring systems to bring optimum use of energy. But the issue is more nuanced than that. Sure, real time monitoring helps you track energy consumption, but that might not lead directly to energy conservation. For that, the realtime energy monitoring should lead to better predictions of energy usage and guide to implement right load level energy equipment.

The 2 components of electrical energy billing

Let us take an example of electrical energy. Usually, electrical energy billing has two components:  Demand charge and runtime/consumption related charges. Demand load is usually the peak load provided by the electricity service providers from the power grid. This usually has a hard and fast limit. Crossing it will prompt penalties of around 20 times the usual rates.

To avoid this, there are usually two options: Reduce the total load required by the machinery. Or ensure that the threshold limit is never reached.

The problem of motors

One of the major sources of electricity usage in the plant are the electrical motors and HVAC systems. They consume a large chunk of the power. A motor is considered under-loaded when it is in the range where efficiency drops significantly with the decreasing load. Most electric motors are designed to run at 50% to 100% of rated load. Maximum efficiency is usually near 75%. Below the 50% rated load, the efficiency tends to lower dramatically.

In many cases, operating motors are either overloaded resulting in overheating or under-loaded, working at most at 40% of their capacity. That causes huge spikes in energy consumption. Oversized motors have a higher initial cost and are very expensive to repair and maintain. Undersized motors don't perform well and prompt higher losses than properly sized electric motors. Same goes with air conditioners if their tonnage and room size or room dynamics aren’t suitable, it leads to higher energy consumption.

Addressing a Wide Range of Energy Consumers:
Apart from regular electrical consumption of motors and HVAC, IoT can address a wider energy sources and resources, including: 

  • Air compressors, the source of air across plant.
  • Boilers, serving as the main source of steam used across plants.
  • Backup generators - an alternative electricity source in case of failure of the primary.
  • Fuel, including diesel, coal, wood, solar, and batteries that are used to run above systems

How the Industrial IoT can help

In the pre-IoT era, the traditional energy management system would collect a sample of energy usage at an interval. The traditional EMS is good to get energy consumption data, but it does not help you with alerts in case of spikes, curating usage pattern, predicting the seasonal demand, or suggesting appropriate configuration. Pre-IoT era, the motor load test was a lengthy and cumbersome affair. Engineers used slip tests and electrical tests with a digital stroboscope. They had to spend hours with the equipment to obtain samples. Even then, the data collected was only a sample, and not real time. With the IoT in place, the analyses can occur on real time data from the motor. That makes the analysis quick, painless and more accurate. IoT brings realtime alerts, ability to predict energy demand, usage patterns and ways to optimize energy consumption.

With the right IoT platform, you can recommend the proper sizing needed for motors. That saves money on the original investment. IoT-based conditional monitoring ensures the motor never reaches its threshold limit. That means the motor lasts longer and suffers fewer failures.

The IoT-based monitoring system gives early warnings of electric motor vibration/temperature problems. Condition monitoring saves time from unplanned production outages. And the unnecessary stress of carrying out urgent repairs can be avoided.

Additionally, a properly designed IoT system can not only track the energy consumptions at distribution points throughout a smart factory, but with the help of smart meters, they can track energy consumption right from its source to all the way consumption point. Moreover it can help predict leakages or voltage drops at nodes if any.

The ultimate goal of the smart factory is a generating a real-time energy audit that traditional Energy Monitoring Systems (EMS) cannot provide.  IoT enabled energy monitoring can solve a lot of issues that are core to hindering a plant from real energy conservation efforts. That not only saves money but paves the way for true implementation of Industry 4.0. If you run a factory and are looking to cut energy costs, then IoT is worth a closer look.

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The Internet of Things (IoT) enables vendors to create an entirely new line of “smart” solutions for its existing and new markets. While the decision to go “smart” is straightforward, the decision of how to do so is not. Vendors are faced with a “build, buy, partner” decision – build it themselves, buy or license it from someone, or partner with a complementary solution provider and go to market together. This article discusses some of the key considerations product managers and executives must study in order to make the most appropriate decision.

 

“Build, buy, partner” is a strategic decision

For many vendors, IoT means adding a technology layer to products that never had any before. Even for tech savvy vendors, IoT presents a whole new set of technologies that they are less familiar with. Equally important, IoT is not just technology, but includes data, security, user experience, and business/business model elements. Figure One shows an IoT product management framework developed by Daniel Elizalde of TechProductManagement. A company going “smart” has a lot of decisions to make, of which technology is just one component.

Figure One. IoT Product Management Stack.

The framework shows that the “build, buy, partner” decision is multi-dimensional. There are six decision areas, spread across components from the edge to the user applications. Each represents a different “build, buy, partner” decision point, and each takes the company down a different path. In today’s fragmented and dynamic IoT ecosystem, many companies will need to “build, buy, partner” simultaneously. For example, cybersecurity is a specialized field that many vendors cannot address on their own, and must buy or license for their solution. The actual proportion of “build, buy, partner” each vendor does varies based on their specific situations.

Build

The company creates the solution themselves with the resources they own, control or contract to. Companies who choose this option, but have limited internal expertise may contract with Original Design Manufacturers (ODM). These ODMs provide a portfolio of services, from design, prototyping, test, certification, to manufacturing.

The “Build” option enables full management oversight of the development process, the solution functionality and the intellectual property. Conversely, this option may result in a longer time to market, and require additional capital and resources beyond what is scoped.

Companies consider this approach when:

  • They have the requisite skill sets and resources to do it
  • They can do it faster, cheaper and at lower risk
  • This is a strategic competence they own or want to own
  • There is strategic knowledge or critical intellectual property to protect
  • They are fully committed throughout the company

Buy

The company procures all or part of the solution components from a 3rd party. This includes licensing technology and services. Companies may also acquire technology through mergers and acquisitions, as well as buying the rights to technology from companies willing to part with it. This option eliminates “reinventing the wheel”, enables faster time to market, maximizes resource efficiency with limited execution risk. One common variant of this approach is to buy technology platform from a vendor, and then build their specific solution components on top of that. 

The downsides of the “Buy” option include a loss of control in the development process, and limited agility to respond in a timely manner to changes in the market and customer needs.

Companies consider this approach when:

  • They don’t have the skills or resources to build, maintain and support it
  • There is some or all of a solution in the marketplace and no need to “reinvent the wheel”
  • Someone can do it faster, better and cheaper than they can
  • They want to focus their limited resources in other areas that make more sense
  • Time is critical and they want to get to market faster
  • There is a solution in the market place that gives you mostly what you want.

Partner

The company allies itself with a complementary solution or service provider to integrate and offer a joint solution. This option enables both companies to enter a market neither can alone, access to specialized knowledge neither has, and a faster time to market. This option adds additional management and solution integration complexity. For some companies, reliance on partners for some aspects of the solution may be uncomfortable due to a limited loss of control.

Companies consider this approach when:

  • Neither party has the full offering to get to market on their own.
  • Each party brings specialized knowledge or capabilities, including technology, market access, and credibility.
  • It lowers the cost, time and risk to pursue new opportunities

 

Management considerations for “build, buy, partner”

Before the company chooses a path to go “smart”, executives and managers must base their decision along three “build, buy, partner” dimensions – execution, strategy, and transformation.

Execution

The first dimension focuses on the company’s ability to execute successfully. Managers must audit and assess their capabilities and resources to answer the following questions:

  • Do I have the necessary skills in-house to successfully develop, test, support and operate an IoT enabled “smart” solution and business (Figure One)?
  • Do I have the right human, capital, financial, and management resources to do this? Is this the best use of my resources relative to other initiatives and projects?
  • What am I willing to commit, sacrifice and re-prioritize to see this through? Am I willing to redeploy top management and company resources? How long am I willing to do this?
  • How much budget and resources am I willing to commit?
  • Is there anyone that can do it better than me? Does it make sense for me to do it? What am I willing to do and not do?
  • What infrastructure (processes, policies, systems) do I have, or need to build, maintain, support and operate these new solutions?

Strategy

The second dimension relates to the company’s current and future strategic needs. These are company specific as it relates to its current situation, its customer and channel, and its position within the industry. Key considerations to be addressed include:

  • How does going “smart” align with the company’s vision and strategy? Which parts align and which doesn’t? Does the vision and strategy need to be updated to reflect the realities of going “smart”?
  • How important is time to market? Do I need or want to be a first mover? How long will it take to execute with the resources that I have?
  • Am I trying to reach existing or new markets with IoT? Do I understand their needs well enough that I can execute on meeting it?
  • Do I have any critical proprietary technology, processes, and other intellectual property that I need to protect?
  • What are the risks? How much risk am I willing to tolerate? What are the costs of those risks? How much risk can I mitigate with my current capabilities?
  • How much control do I want or need to go “smart”? What areas do I want to control myself and how? Can I afford to control those areas?
  • What is your real value to customers and your channel? Why do they buy from you, and why do they come back? What do you do well?

Transformation

The third dimension is the company’s ability to manage transformation. Going “smart” doesn’t stop with the IoT technology. The entire organization, its operations, policies, systems and business models must transform to support and operate the “smart” business. Furthermore, resellers and service channels, and suppliers and partners, are also impacted.

  • What is your corporate culture and how well does it support change? Do you have the right people to manage and sustain this change? Are you nimble and agile?
  • What degree of disruption will there be to internal processes, channels, organization readiness, and business models? How agile are your current capabilities?
  • How prepared are you to operate a “smart” business? Do you have the skills and infrastructure required? Can you support a recurring revenue business model? How willing are you to invest in order to develop and sustain these capabilities?

 

What should you do next?

Each company is unique, and its situation will dictate its response to these dimensions. There is no one “right” universal answer to the “build, buy, partner” decision. Equally important, what’s right today, may not be right tomorrow. Companies that want to go “smart” start by looking inward first and doing the following:

  • Establish a current baseline. Audit and catalog current and planned offerings, strategy, human resources and skill sets, channel and suppliers, internal operations and policies, and culture.
  • Evaluate the IoT product management stack (Figure One) against your baseline using the three “smart” dimensions. The list of questions listed are starter questions, but answering those will lead to more questions to be addressed.
  • Evaluate and assess your company’s future state capabilities against the baseline using the three “smart” dimensions. Understand where the gaps are, and the extent of those gaps.
  • Identify your risk tolerance level. Going “smart” is not without risk, especially if you have never done it before. The key is to identify what and how much risk you are willing to take. Once you do so, you can develop a risk management plan and incorporate the appropriate tactics to manage it.
  • Update your business vision and strategy as applicable.
  • Develop your “build, buy, partner” decision and strategy. This strategy must align to the broader business vision and strategy.

 

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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5 IIoT Use Cases from Global Leaders

“I talk to a dozen or more companies involved in IoT every week. One thing they all have in common is their desire for the projected IoT volumes and revenues to come to fruition...the sooner the better”.

Mike Krell

Analyst at Moor Insights & Strategy covering the Internet of Things, Forbes.

 

Internet of things has always been functioning in a context of business transformation.

If you’re in business, just read on, as we are to have several working IIoT solutions to consider right now.

 

To be successful today you need to:

  1. really love what you do;
  2. move with the times;
  3. make the IIoT technology a part of your business development plan;
  4. and find an Industrial IoT company for you to cooperate with.

Here I gathered 5 IIoT solutions implemented by global industry leaders and the key examples of their efficient cooperation with IoT developers:

 

#1 Predictive Maintenance for Wind Energy

 

The IIoT solution is projected to be implemented into the maintenance of wind energy. The smart wind turbines will be applied to reveal how employees can get additional insights by using ML about the equipment performance in different conditions. Thus, smart sensors are supposed to give the information in a real-life regime.

The system can give reliable statistics for the future planning and help to replace vital parts of the engines during the less windy periods:

Source: Schaeffler Group & IBM

 

#2 Health Detectors for Caterpillar Equipments

 

Recently, the American machinery and equipment giant, Caterpillar implemented a new IIoT solution to help its customers better understand the workability and health of the equipment. It should also be said that the company uses IoT solutions for tracking fuel efficiency, idle times, location, and many more. The new project lets clients directly address the company maintenance service and timely repair the sensitive spots by using the IoT platform.

The end-to-end platform for predictive diagnostics allows for better monitoring and timely replacement of the interchangeable parts. The Caterpillar CEO, Doug Oberhelman supposes the IIoT, which is primarily applied to the fleet and fuel monitoring, will take the clients offering to the next level.

 

#3 Airbus Smart Manufacturing

 

You know the biggest European aircraft manufacturer has already applied the IoT solutions to its products. Today Airbus is working at implementing the IIoT to the tools its workers use during the manufacturing process.

For this reason, Airbus opts to involve its employees and the factory floor. The workers will manage to use smart tablets or glasses to evaluate a task and then send the data to a robotic tool that will finish it.

Jean-Bernard Henz, the head of PLM R&T Innovation at Airbus ICT, says the IoT platform manufacturing will speed up the processes and improve the reliability of the production.

 

#4 Siemens -- a 75% automated plant

 

You know the Siemens AG plant is a part of a concerted effort by the German government to develop fully automated factories. Guess what? Siemens is claimed to be 75% automated with 1,150+ employees on board.

All the employees are mainly operating computers and monitoring the process of manufacturing by using the IIoT solutions. Sinalytics, which is a critical component of the IIoT Platform was implemented in 2015. Today Siemens continues developing the Web of System, which directly connects devices to the open Internet and with each other. Besides, Siemens launched a new company in 2016 that is named Innovations AG. The company is dedicated to the search and support of the emerging start-ups that can be a good technological investment for Siemens. This has influenced the factory efficiency, opened the new technological opportunities and reduced costs.

https://twitter.com/Siemens/status/935795639472021506

 

#5 ThyssenKrupp Elevates IIoT Implementation

 

The CGI global tech firm claims ‘that thing is an elevator’ for the company. Well, let’s see it. Having joined forces with Microsoft and CGI, the ThyssenKrupp Elevator company has now obtained a predictive maintenance for elevators manufacturing.

The IIoT solution securely connects tens of thousands of sensors and elevators systems across the plant. The technology allows for monitoring every stage of production starting from motor temperature and finishing with shaft alignment. The real-life IIoT gathered data lets the company identify vulnerabilities and repair them before an actual breakdown occurs:

https://twitter.com/thyssenkrupp_en/status/964787252629946368

 

What’s the bottom line?

IIoT solutions undoubtedly contribute to production efficiency. The predictive maintenance and pre-emptive repair, manufacturing automation and further spending cuts are just a tiny bit of what I recorded here.

I am almost done here...

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Blockchain and IIoT

 

Blockchain and IoT both are present in the Gartner’s Hype Cycle 2017.

Clubbing Blockchain and IoT bring the Intelligent Digital Mesh

The Intelligent Digital Mesh

Gartner calls the entwining of people, devices, content, and services the intelligent digital mesh. It’s enabled by digital models, business platforms and a rich, intelligent set of services to support digital business.

Intelligent: How AI is seeping into virtually every technology and with a defined, well-scoped focus can allow more dynamic, flexible and potentially autonomous systems.

Digital: Blending the virtual and real worlds to create an immersive digitally enhanced and connected environment.

Mesh: The connections between an expanding set of people, business, devices, content and services to deliver digital outcomes [2]

 

What is Industrial IoT? 

The term industrial Internet of things (IIoT) is often encountered in the manufacturing industries, referring to the industrial subset of the IoT.

Uses cases of Industrial IoT

Industrial Internet of Things brings a lot of advantages some of them are listed below:

  • Predictive & Proactive maintenance
  • Real-Time Monitoring
  • Asset/Resource Optimization
  • Remote Diagnosis

but all these are under the security threat. Blockchain has begun to have a significant influence on the Internet of Things by enhancing security, empowering the incorporation of an increasing number of devices into the ecosystem. The enhancements in IoT device security facilitate faster adoption of this revolutionary innovation and will open up a wide range of possibilities for enterprises in the days to come.

 

Blockchain and IIoT

IIoT solutions using blockchain can be built to maintain a continuously growing list of cryptographically secured data records protected against alteration and modification. It can set up trust, accountability, and transparency while streamlining business processes.

 

1. Blockchain reducing the cost of IIoT Solution 

It is important for IoT edge devices to reduce processing overhead and eliminate the 'middle man' (IoT gateways) from the procedure. Communication, data exchanges, and device information are conducted on a peer-to-peer basis, removing any additional traditional protocol, hardware, or communication overhead costs.

 

 2. Blockchain confirm and enable the trust

Blockchain empowering Industrial IoT solution with trust. It empowers devices to engage in transactions and communications with trusted parties. While device A may not know device B, and may not believe it verifiably, a permanent record of exchanges and information from devices stored on the blockchain confirm and enable the vital trust for organizations, individuals, and devices to cooperate.

 

3. Accelerate Data Exchanges 

Blockchain eliminates the role of “ IoT gateway” or an intermediate device, which helps in improving data exchange in the process of data transfer. Peer-to-peer device based contracts and ledgers (blockchain) decrease time required to complete device information exchange and processing time.

 

4. Blockchain scaled security in  IIoT Solution 

Decentralized technologies hold great promise for a system that needs to handle storing and retrieving information of millions—if not billions—of connected devices. These future systems have to provide low latency, high throughput, querying, permissions, and decentralized control

 

 

Conclusion

Blockchain and IoT Solution in the Framework - 

Ease of Implementation and Business Impact

High Business Impact and Ease of Implementation put this in the Quick win quadrant.

For Industrial Implementation- Lot of Frameworks, options are available from Ethereum to Hyperledger. IBM Hyperledger Fabric development in the past few months is noticeable.

Ease of Blockchain Implementation is a business challenge rather than a test of technology implementation as it involves connecting multiple parties across multiple processes.  

 

 

References:

  1. https://www.gartner.com/smarterwithgartner/top-trends-in-the-gartner-hype-cycle-for-emerging-technologies-2017/
  2. https://www.gartner.com/smarterwithgartner/gartner-top-10-strategic-technology-trends-for-2018/
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2018 Analyst IIoT Predictions

Each year we like to go inside FreeWave and ask our team what the Industrial IoT forecast looks like for the upcoming year. Throughout 2017 we were hard at work developing some of our industry-leading Edge intelligence and industrial Wi-Fi products, so this year, instead of looking inward, we decided to take a peek around the world at 2018 IIoT predictions from some of the leading experts.

Network World

Based off a Forrester report, three immediate trends spring to the forefront: specialization, security, and Edge infrastructure. Taking a bird’s eye view, as the market proliferates, many Industrial IoT providers will no longer need to be a one-size-fits-all solution, instead being able to double down on proprietary technology that has a highly specific and specialized purpose. Edge Infrastructure, already one of the hottest sectors of IoT, will possibly determine the future of big data and predictive analytics, in turn driving machine learning and beyond. And then, of course, there is the security element.

As the domains of Operational Technology (OT) and Information Technology (IT) converge, the traditionally more vulnerable standards and practices of OT will take on more of an IT flavor, incorporating more hardened cybersecurity elements as IT managers (with security ALWAYS on their minds) take on more prominent roles in industrial operations and implement the next generation of IoT-ready devices and systems.

IDC

In early November, IDC put together a list of 10 predictions for IIoT covering myriad facets of the industry, including:

  • As much as a 25 percent increase in security spending
  • 10 percent growth in IoT sensors on Blockchain distributed ledgers
  • In three years more than $1 trillion of enterprise IoT project investments will be built on net new technology spending

These are interesting predictions and fall in line with the general trend of the industry over the last five years. But there was one prediction that caught our eye:

  • “By 2020, IT spend on Edge Infrastructure will reach up to 18 percent of the total spend on IoT Infrastructure, driven by deployments of converged IT/OT systems that reduce the time to value of data collected from their connected devices.”

Essentially, IDC is predicting that in two years Edge intelligence will use nearly 20 percent of the industry’s total IoT spend. This Edge intelligence will be driven by IT/OT convergence that enables faster data transmission via Fog Computing, enabling predictive analytics and real-time data monitoring. This is a significant note, as many companies are focused almost exclusively on figuring out how to transmit data from the Edge in usable packets.

Maciej Kranz, vice president of strategic innovation at Cisco

Kranz wrote the book on IoT (literally, check it out: Building the Internet of Things), and he tends to view it from more of a business standpoint. However, as more companies attempt to jump into the IoT fray, taking a strong – and long – business perspective could be the difference between success and failure.

In his ten predictions, Kranz finds similar footing with many analysts and thought leaders (paraphrasing):

  • IoT will become the key security domain as organizations ‘finally begin to take IoT security seriously.’
  • IoT will revolutionize data analytics as technology shifts to dynamic or real-time analytics and streaming data using AI and machine learning
  • The focus of IoT will move from driving efficiency to creating new business value as companies use IoT to create new value propositions: in manufacturing mass customization, and more mass personalization.

To us, however, the most interesting prediction offered up by Kranz has to do with standardization:

  • “We will see an industry-wide, accelerated move to open standards, open architectures and interoperability.”

At FreeWave, we have been huge proponents of opening up architectures to make the creation of IIoT software applications easier and more accessible to critical industries. Currently, many IIoT software needs require sophisticated and complex development chops. But, with the rise of NODE Red – and with the growth of language agnostic hardware – development and interoperability opportunities are opening up for everyone.

2018 could be a watershed year for the Industrial IoT. We highlighted three analyst and thought leader predictions here, but many carried the same tenor: security, analytics and proliferation will drive the growth of the industry over the next few years.

We’d love to hear from the community as well: what predictions do you have for IIoT in 2018?

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The phrase, “the future is here,” is overused and has evolved into a catchphrase for companies struggling to position themselves in times of technological or digital transformations. Still, the sentiment is understood, especially in times like today, where the Internet of Things is quite literally changing the way we think about hardware and software. We’d like to offer an addendum to the phrase: “The future is here more quickly than we thought it would be.”

Digital transformation, increased computing ability, smart hardware and the growth of connectivity capabilities created a perfect storm of accelerated industry, and many were left scrambling to sift through the large amounts of information and solutions available. With that in mind, we wanted to provide some advice for companies across the industrial sector for the best ways to optimize operations for the Industrial IoT.

1) Upgrade your network and throughput capabilities.

Nothing can kill the ROI of automated processes more quickly than the literal inability to function. It’s important to understand that as you upgrade machinery and invest in the software to run it all, those systems demand greater bandwidth in order to effectively utilize the big data and analytics capabilities. Several options exist, but for most companies some combination of industrial-strength broadband (WiFi), narrow-band, cellular and RF communications will create the most effective network for the needs.

2) Invest in smart hardware.

This may seem like a no-brainer, and really, in the not-too-distant future, you may not even have a choice, but the shift toward Fog Computing is gaining momentum and being able to run decentralized computing between hardware and the Cloud can not only create greater operational efficiency, but it can also allow your data transmission to run more smoothly as well. The beauty of a Fog Computing system is that it allows a greater number of devices to transmit smaller data packets, which frees up bandwidth and speeds real-time data analytics. The core of this lies in the smart hardware.

3) Be proactive about application development.

Smart hardware means that it has the ability to host applications designed specifically for your needs. Previously, many companies shied away from app development because it required highly skilled developers and devices capable of hosting those apps – a combination that wasn’t readily available. Today, the scene has changed. With the rise of Node-RED, it is much easier today to create proprietary applications without a computer engineering degree, and any company serious about leveraging IIoT technology needs to be able to to use the full scope of its data.

4) Secure your communications.

There isn’t much more to be said about the importance of cybersecurity. If the last few years of massive data breaches haven’t rung alarm bells, then you aren’t paying attention. Cybersecurity today is a multi-layered need. Most companies building smart hardware are beginning to build encryption directly into the devices. But, since many companies use Cloud applications for computing and analytics, it is important to invest in strong security measures at that level as well. Unfortunately, the sophistication of cyber-attacks are only going to increase, along with the increase in importance of the data needing to be protected. It pays to be paranoid and act accordingly.

Further Reading:

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A recent study by Cisco suggests that 75% of IoT initiatives will fail. However, there is growing pressure to invest in IoT. Ensuring the success of enterprise IoT initiatives is definitely not easy given technology immaturity, culture obstacles as well as well as the challenges of traditional organizational structure. So put the odds of success back into your favor using a customer-centric, integrated team (IT) philosophy.
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Fog Computing is a slippery concept. It combines two critical components of data computing today, Edge and Cloud computing, into a system that leverages the strength – and necessity – of both. This idea of local computing (the Edge) combined with more complicated analytics engines (the Cloud) opens up a world of possibilities for data communications.

Fog Computing & Emergency Response

Earlier this fall, researchers at Georgia Tech looked at the application of Fog Computing in areas struck by natural disasters. In these areas, traditional means of internet connection are often knocked out of commission, leaving rescuers and victims unable to communicate with one another, even though there are many apps designed to help facilitate rescue. Where Fog Computing comes in is that rather than relying on a direct connection to the internet, different Fog nodes can be leveraged to create an ad hoc network that can still send basic messages:

However, one important advantage of a fog system is that messages can be distributed between a broad network of computers through temporary ad hoc connections, even without live internet connections.

The geo-distributed network of fog nodes, which could be phones, tablets or any device part of the Internet of Things, could generate communication channels in areas where there were none before, allowing the creation of population density maps in flooded areas.

Another application would allow users to check the fog network to see if their family members are safe after a crisis event.

Fog Computing applied in this setting is applicable around the world, as we are reminded daily of both the ubiquity and fragility of wireless communications against the whims of nature.

Smart Grids Need Fog Computing

Across the globe, more and more countries are jumping into smart grid deployments. The good side is that smart energy tools are critical to managing resources. The bad side is that most are not sufficiently developed with the necessary security infrastructure in place. When considering the rapid development of smart grid tech, Fog Computing quickly comes up as a viable tool for ensuring reliable data communication and information transfer between consumers, grid operators and larger energy providers. The Open Fog Consortium, a global Fog Computing group comprised of technology and academic thought leaders, has formed Resilient Information Architecture Platform for Smart Grid (RIAPS), a project aimed at developing software for Fog Computing platforms:

RIAPS is very different from conventional platforms as it was designed for inherently distributed and decentralized applications. An application is composed of interconnected real-time software components (similar to micro-services) that can be event- and/or time-triggered and that interact via well-defined communication patterns, including publish/subscribe and synchronous and asynchronous service invocations. Such components are location transparent and agnostic about the underlying messaging framework.

Although the project is based out of Vanderbilt University, in the United States, the repercussions will be felt throughout the world.

Is Fog Computing the Final Answer?

While Fog Computing has yet to be standardized and applied across the wide range of IoT technologies out in the field today, its ability to combine both local and Cloud data analytics is something that can have an impact in both the consumer and the Industrial IoT. However, the first adapters, companies that play in IIoT settings, will be largely responsible for driving the growth of this concept moving forward into the future.

Additional Reading:

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The manufacturing industry is undergoing many changes. Those specializing in traditional manufacturing are finding it difficult to keep up with the changes. Perhaps the biggest change has been how traditional manufacturing has come under pressure to manage vast amounts of data captured from different sources. Here are some of the reasons the Internet of Things (IoT) can help.

1. KEEPING AN EYE ON SUPPLIERS

Quality control has become easier because IoT helps keep an eye on suppliers. This makes for easier manufacturing processes. Keeping an eye on suppliers is all about looking at all the constituents that the supplier offers. Capturing data about these constituents through IoT helps make for faster data processing and better quality control.

2. MORE PRODUCTIVITY

Thanks to IoT, many manufacturers are now building self-correcting systems. Missing parts are replaced and parts are replenished, giving rise to greater productivity. Since manufacturing industries are looking in particular for ways to boost productivity, there is no way for them to overlook what IoT can do for them. In addition to greater productivity, there is also more convenience since the need for human labor reduces.

3. MAINTAINING SUPPLY LINES

The Internet of Things is expected to help manufacturers stick to lean manufacturing while at the same time helping maintain supply lines. Since lean manufacturing often requires smart management of the supply lines – to ensure that components are never in short supply but there is no overstock – IoT is expected to help resolve many problems. It will help ensure that suppliers located in different regions can be kept in the loop and supply lines can be managed smoothly so that there is no shortage. It will also help reduce waste and optimize the use of resources.

4. UNINTERRUPTED MANUFACTURING PROCESS

Usually, manufacturing is divided into many processes, from sourcing of raw materials to production, transportation and reaching the customer. However, with the Internet of Things, experts envision something extra. The entire process will be smooth and effective. The raw materials will be already marked for production, intended to reach a particular buyer. This is how experts see things play out as IoT advances to new levels.

5. REDUCED COST

As IoT gains more efficiency, manufacturers can expect to see lowered costs. This is one of the primary reasons manufacturing experts are enthusiastic about the role of IoT. It will become easier to track information about products and processes and more automation would help bring about greater efficiency, thus eventually reducing costs. Lowered costs are expected to boost profit margins. If your manufacturing plant has not invested in IoT yet, this might be the right time to start.

6. LAUNCH NEW PRODUCTS

With IoT, studying needs and launching new products becomes easier. There is less jostle and inefficiency than traditional systems. Manufacturing is thus one of the key areas where you can expect a lot of improvement, thanks to the Internet of Things.

7. INTEGRATING OFFLINE AND ONLINE PROCESSES

Traditionally data and manufacturing have been treated as separate entities. However, in manufacturing industries where IoT advances, this is expected to change. As products begin to carry information about them, it becomes easier to assign a processing and logistics path to them. This is why it becomes critical to involve IoT in your manufacturing plant.

8. CONNECTED TO THE CONSUMER

Products are, in the end, manufactured to suit the consumer. Thanks to IoT, it becomes easier to stay connected to the consumer and create products that match their requirements. This offers two-way benefits, as the consumer gets the best products and the manufacturing plant is able to manufacture products per exact specification. There are a lot of benefits that manufacturers can expect in the long term, thanks to the Internet of Things.As manufacturing processes undergo change, it becomes imperative for manufacturers to make the most of the coming revolution. Supply chains and logistics will become smoother thanks to the industrial Internet of Things. According to many experts, we are at the cusp of another major revolution that will change not only how things are manufactured but also the market economy. It is a good idea to be prepared for these changes by investing in the right IoT system.

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Why Edge Computing Is an IIoT Requirement

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.

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The Digital Twin: Key Component of IoT

A Digital Twin uses data from sensors installed on physical systems to represent their near real-time status, working condition or position. This modelling technology allows us to see what is happening inside the system without having to be able to get inside the system. It forms a critical step in the information value chain without which it is often impossible to get from raw data to insight, and therefore to value. As the Internet of Things grows, Digital Twins will become a standard tool for Data Scientists and Engineers wishing to use all this new data to automatically understand and respond to what is going on in the real world.
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