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Considering that the IoT is in its infancy and due to the last years wasted in predictions that have not been fulfilled, in disappointing statistics of successful projects and with most companies without clear strategies, it is normal to think that R & D is today so necessary for boost and accelerate this increasingly sceptical market.

R&D should be an essential part of bringing innovation to any company via IoT projects. And though we can all agree how important R&D is, it requires a great deal of experience, senior experts, and specific toolsets—resources that not every company can say they have handy.

However, there is a risk when deriving the strategic decisions that the executive directors consider to be technological towards the R & D departments. Many times, oblivious to the reality of the markets, those responsible for R & D with the invaluable aid of the subsidies of the different Administrations, they launch to develop products and technologies for problems that do not exist, just for the fact of obtaining recognition or to continue living without pressures of the Top Management. I am enemy of granted subsidies granted most of the time by unqualified Administration organisms that does not understand that need to prevail the utility, the business model, the business case and the commercialization over the innovation that R & D said to be developed.

Now, if we ask the sellers of IoT technology, products and services, they may not be so happy with the idea of having to talk with the R & D areas instead of with other areas of the company more likely to buy. Most time, R &D departments decide to do it themselves. Vendors know, that with great probability, they will not to close deals due to lack of budget of the R &D or the low visibility of this area by the rest of the departments of the company.

The Importance of R&D for the Internet of Things

Innovation in IoT is a major competitive differentiator. See below some advices to have a decisive advantage over competitors:

  • IoT-focused companies need to invest in R&D to keep up with the rapidly changing and expanding market. It is important that an organization’s R&D iteration turn times are quick, otherwise the company is not going to be able to keep pace with the expected IoT market growth. However, it’s not enough to simply speed up R&D—innovative IoT firms, both start-ups and established companies, must also make sure their R&D processes are extremely reliable.
  • You can’t solve R&D speed issues just by increasing budget.
  • Executives must maintain strong, steady communication with R&D regarding the department’s priorities over a particular time frame and how progress will be measured.
  • Guidelines are invaluable: The more structured and streamlined R&D procedures are, the better IoT companies will be able to move from conception to delivery.
  • Design innovative IoT products but accelerate time to market.
  • Internal collaboration: R&D team should share real-time data across internal departments to spur intelligent product design
  • External collaboration: Connect with customers and partners to ensure success
  • Differentiation: Drive overall business value with IoT.

 

 

Outsource or not Outsource R & D for your IoT project

Just like any other technology, IoT products and solutions require thorough research and development, and it better be done by professionals. Despite the noise generated by analysts and companies around the IoT, the reality is that there have not been many IoT projects and therefore it is not easy to find good professionals with proven experience in IoT to hire.

When I think of Outsourcing IoT projects, Eastern European and Indian companies immediately come to my mind. No doubt because the R & D talent seems to be cheaper there. Spain could also be a country to outsource IoT, but at the moment I do not see it.

The benefits of Outsourcing R&D for IoT Projects:

  • Expertise and an Eye for Innovation
  • Bring an IoT Project to Market Faster
  • Optimize Your Costs
  • Control and Manage Risks

I am not sure about the quality of most of these companies or the experience of their teams in the development of IoT products or in the implementation of IoT projects, but there is no doubt that there are benefits to Outsource R & D for some IoT Projects. You should select any of these companies after a careful evaluation.

Recommendation: Do not stop your IoT projects if you do not have the skills and professionals in house. Luckily, there are companies who offer outsourcing R&D for IoT projects.

Note: Remember I can help you to identify and qualify the most suitable Outsource R&D for your IoT project.

Spain is not different in R & D for IoT

I have not believed in R & D in Spain for years. There are exceptions without a doubt, but it seems evident that the prosperity and welfare of Spain is not due to our R & D. Fortunately we have sun and beach and a lot of brick to put in houses that are not sold because of high prices and low wages.

With the entry into the EU, I thought that we had great markets open to us. I was also optimistic that we would have great opportunities in the Latin American market, thanks to the fact that our research and development capacity would have been consolidated effectively in our companies and universities because it would be profitable and worldwide recognized.

But it has not been that way. The technology developed in Spain and more specifically that relating to the IoT has little chance of being commercialized in France, Germany and not to mention in the UK. If we add the development gap of the countries of South America and that our local market is averse to technological risk, it is difficult to flourish R & D in IoT or Industry 4.0 here in our lovely Spain.

That does not mean that we do not have public R & D budgets for these areas. What happens is that the same thing that happened during the last 30 years has happened. The incentives and aids are few and for the most part used to finance large companies with little return to society. There is no rigorous control of the aid granted and, above all, there is no plan to encourage the local and global marketing of the products developed with the talent of our scientists and researchers.

I have stopped believing and trusting in our successive Governments for the change in R & D but there are exceptions that are worthwhile to follow and work with them. For this reason, I continue help them demonstrate that “SPAIN CAN BE DIFFERENT”.

Key Takeaway

After years of unfulfilled expectations, companies are sceptical of the potential growth of the IoT market or the benefits in their business. R&D department can be a cure to boost IoT initiatives but also a poison to kill IoT initiatives.

 

IoT may have started in R&D, but their benefits don’t have to end there. To drive overall business value, it’s important to share IoT data – both internally and externally. Facilitating open collaboration, discovering new ways to innovate products, and accelerating time to market, you can differentiate R&D and your business.

As fast turn times and reliability becomes a focal part of companies’ R&D processes, these companies will be well-positioned to thrive within the IoT market.

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Heavy equipment is mainly used extensively in industries such as construction, oil and gas, mining, forestry, energy, civil engineering, military engineering, transportation, and many others. Industrial heavy machines include construction equipment, wheel loaders, oilfield pieces, manufacturing equipment, earthmovers, hydraulic cranes, bulldozers, oversized trucks, forklifts, and more. Organizations rely on heavy machinery to speed up production and to avoid human errors or health risks.

With developments in IoT, it is possible to decrease equipment downtime while improving the efficiency of the output. Companies that supply industrial machinery and components are seeing strong interest in connected machinery and components which providing many IoT consulting Companies. IoT-powered asset management solutions offer a host of benefits, including predictive maintenance to prevent equipment failure, increased asset reliability, improved asset health, accident avoidance in the workplace, and downtime reduction.

Smart Asset Monitoring with IoT

Safety of personnel and assets, theft or pilferage of assets, accidents and resulting injuries, and bottlenecks in the supply chain are some of the common challenges that are prevalent in asset-intensive industries like manufacturing, utilities, construction. By improving visibility into day-to-day operations, replacing legacy systems with an integrated solution and automating manual processes, many of these challenges can be overcome. 

Digitalization, combining connected devices with IoT-based solutions, can help to overcome these issues. End-to-end clarity on the status of the equipment enables improved decision-making, increases asset reliability, and also improves the people and process efficiency. With the advances in technology, mature organizations have heavy machinery that is computerized, automated and enabled with connectivity and big data analytics, which increases the efficiency of the overall product development process.

Use cases: IoT in heavy machinery management

Let’s take a look at some of the use cases where IoT is transforming the way heavy equipment and related assets are managed.

Smart heavy equipment in warehouse management

Material handling equipment like trucks, forklifts, pallet trucks, and pump trucks are very important for any warehouse to perform daily activities such as loading, unloading, transporting goods to different areas, and picking goods from risky areas. Needless to say, these machines and their operators need to be managed properly to minimize the chances of accidents. Warehouse operators need to take preventive measures for vehicle accidents and injuries that occur while from shifting material, and take proper care while handling hazardous materials.

Today, futuristic warehouses are using driverless robotic equipment to assist in picking and moving operations. Guidance systems like global positioning system (GPS), lasers, and radio-frequency identification (RFID) are used in such warehouses and equipment.

For example, advanced driverless pallet trucks and forklifts are equipped with audible warnings and lights and have built-in sensors to detect obstructions. These sensors come with lasers or camera systems, which are positioned to detect objects and activity from the floor and are able to determine the height and distance around all sides of vehicles and warehouse corners. This makes the equipment intelligent – it knows when to slow down and stop to avoid a collision.

With the recent advances in IoT for warehouse equipment, the market has a new breed of smart forklifts that come equipped with 360-degree detection forklift antenna, which is able to detect when the workers come into forklift zone. When a worker is detected within the predefined danger zone, audio and visual alarms are set off inside the forklift cab to alert the driver. This helps to reduce the risk of injuries and property damage.

Smart heavy equipment in the construction sector

According to a MarketandMarkets report, the heavy construction equipment market size is estimated to grow from USD 121.46 Billion in 2015 to USD 180.66 Billion by 2020, at a CAGR of 7.0%. Depending on the construction application, heavy machines are mainly categorized into four types:

  • Earth moving equipment
  • Construction vehicles
  • Material handling equipment
  • Construction equipment

Wireless technology has a huge impact on the construction industry to provide connectivity for heavy equipment. These machines use technology-enabled devices combined with cloud computing, allowing storage and sharing of data.

IoT is playing a key role in boosting productivity, improving preventive maintenance, minimizing downtime, and reducing repair costs. Sensors integrated with the equipment are able to detect and send automated alerts related to the status of the equipment systems and parts. They can also compile and analyze usage and maintenance data, helping with preventive and predictive maintenance.

 

One of the major problems in the construction industry are injuries caused due to accidents involving people and heavy equipment. As the number of heavy equipment continues to rise, the risk also increases. IoT can help to make the equipment smarter and safer.

Additionally, IoT can help to track assets as they move around the site, or to a different site, ensuring that the assets are never stolen or lost – an ongoing issue on large construction sites that causes delays and decreases productivity.

Smart heavy equipment in transport and logistics

Transportation and logistics businesses want to optimize the supply chain. Many transportation companies are already using mobile devices, such as barcode scanners, mobile computing devices, and radio frequency identification (RFID) to solve challenges related to the supply chain. With RFID, many companies are achieving a high level of shipping and receiving accuracy, inventory accuracy, and faster order processing, along with a reduction in labor costs.

However,  due to drivers’ careless behavior, while driving heavy trucks or conveyors, company owners have to shell out a big amount for accident-related injuries, material loss or shipping delays. By using advanced technology that is capable of monitoring driver’s behavior and delivering alerts in case of possible collisions, the risk of these issues can be minimized.

Computer vision-based techniques and ADAS solutions, with a number of onboard sensors, can help with lane detection, traffic signal detection, driver behavior detection, GPS tracking, fuel management, report generation, notification alert, and predictive maintenance.

Using such solutions, the driver receives support to detect and avoid accidents. It is also possible to monitor a driver operating a heavy machine and automatic alerts can be generated if the driver is sleepy or inactive for a long duration.

Another effective solution for tracking of heavy machines/vehicles is based on installing GPS fleet tracking devices on the vehicles to gain real-time data updates. This is an efficient and secure solution that helps to resolve issues related to operational inefficiencies, theft, and fleet maintenance, increasing the overall productivity of the machines and vehicles.

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When you have the responsibility of ensuring a manufacturing plant is operating at its full potential at all times, talk of “Industry 4.0” and “industrial automation like never before” might be exciting but far-fetched. Industry 4.0 is just an empty phrase used by marketers who want to take your money, right?

Maybe in some cases, but the ideas behind the buzzy terms can actually give you an edge over competitors. Industry 4.0 is not a phase, but it’s also not an obligation that you need to “opt in to” 100% right away.  Industrial automation is a combined result of our greater digital capacities, smarter machines, and improved cross-channel communication that have accompanied the digital age.

In 2019, the technology is here: from decentralized cloud systemsto self-correcting and self-directing machines. However, it’s not everywhere yet, and most plants are simply taking baby steps towards preparing their lines to be as compatible as possible to these new technologies so that they can gradually work their way in. Industry is slowly moving towards a more optimized, efficient, automated structure, but this transition will be happening in the industrial world over the next few decades.

What do those “baby steps” look like? Where should begin to optimize lines in the most cost-effective, long-term ROI benefits?  We have compiled a list of 5 relatively simple ways you can take this year to set your plant up for new “Industry 4.0” industrial automation technologies:

1. Integrate a Single Virtual Server

Managing the IT aspect of your plant is difficult when you need to find cost-effective storage and data processing solutions for your company that also comply with all of the regulations and contingencies of your industry. However, upgrading a server to a virtual option is probably the most important upgrade you can do to get started on the road to future industrial automation applications that use a truly decentralized communication with virtual operating system.

If your plant currently runs exclusively on physical servers, you don’t need to go virtually all at once. The wonderful thing about industry 4.0 is that much of the software integrations available will integrate with your existing hardware. You can invest in one virtual server, and then layer software integrations on to it over time.

By starting with a single server, you can cut costs, maintain a realistic learning/adaptation curve, and try out a virtual server option without committing 100% to a change. There are numerous virtual server options available, so talk to a process automation expert about what server will work best for your plant, and which server to upgrade first.

2. Get Basic Industrial Automation Security – Two-Factor Authentication

With increased adaptability and communication on virtual servers comes increased cyber threats, and unfortunately, there is no way around this. One of the easiest and fastest upgrades you can do for your company is to implement two-factor authentication (2FA) for all employees. A simple password is no longer anywhere near secure enough to protect your employees and your data.

Luckily, everything from Twitter to Cloud servers now offer 2FA options, it’s usually just a question of getting the settings implemented correctly and creating a protocol that requires every employee to use 2FA at all times. It may seem tedious or frustrating at first, but this is a small habit that can make a huge difference in your cyber security and overall functioning of your plant.

3. Make Your Next Machine Purchase a Smart Machine

You probably aren’t yet at the point of having a completely automated assembly line of smart machines that create highly customized orders while communicating with and correcting each other (like the assembly line in this German plant.) However, smart machines do exist, and if you are getting ready to purchase a new machine, finding one that has automation, optimization, and decentralized communication abilities will be a great investment in your plant’s future.

Customizable “smart machines” are virtually independent of a human operator. The ability of these machines to adapt to the demands of individualized production requirements allows for scalable, lean production processes. In other words, with these new machines, you can produce a larger variety of products faster than ever before.

If your current machines are working fine, there is no need to replace them with smart machines right away. But from this point forward, it is a good idea to consider buying a smart machine for your next upgrade. Don’t be afraid to use an automation integrator to advise you on the appropriate machine, technology, and compatibility with existing plant automation systems.

4. Implement Technology Upgrades that Overlay or Automatically Integrate Existing Plant Industrial Automation

Be choosy about the automation products you decide to implement into your current systems moving forward. You want applications that both set your systems up for future technology integrations and help move you away from expiring legacy applications.

This shouldn’t mean replacing all your old applications, programming, and platforms all at once other. Most Industry 4.0 automation tools are created in an “overlay” style, meaning they are created to be able to function on top of your existing processes and are not supposed to disrupt everything you have already built.

Embracing a new software or system should never mean that you have to throw away your existing processes and start from scratch. If this is how you feel when you are getting ready to purchase a new software, machine, or server then it probably isn’t the right product for your company.

Talking to an expert about what products will work best with your current setup is a good idea before making any changes to your industrial automation. At my company, EPIC systems, we've seen the difference that selecting the right product solutions has made for hundreds of process automation projects — it's a key step for any manufacturing plant. No matter who you work with, you don't want to bypass this step.

5. Optimize One of Your Plant’s Processes

Divide and conquer, as they say. Just as it is best to upgrade one server at a time, it is helpful to focus specifically on one plant process at a time when you are looking to optimize and automate your plant.

This could mean focusing on optimizing your shipping procedure or optimizing one assembly process. The important thing to remember is that as you do this “experimental optimization” you are not just looking for an impressive return on investment, you are also looking to get your entire team comfortable with the automation and ready to embrace even more. This is why the “how” is just as important (if not more important) than the “what” when it comes to choosing a process to optimize. Go slow, be transparent, and include everyone in the process so that it is a success all around.

Industry 4.0 is creating a world where employees can delegate mundane tasks to smart machines and rely on highly communicative, agile systems in order to work faster and more effectively than ever before. There is no reason for any manufacturing plant to be left behind in this industrial evolution, with numerous products and services available to help walk you through the industrial automation process gradually and intelligently.

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A new wave of technologies, such as the Internet of Things (IoT), blockchain and artificial intelligence (AI), is transforming cities into smart cities. Many of these cities are building innovation labs and zones as part of their new civic landscape. Smart city innovation labs are vital components of the smart city ecosystem (Figure One). They provide an organized structure for cities, communities, experts, and vendors to come together to create solutions. Successful solutions piloted in smart city innovation labs are then scaled and deployed into a city’s operations and infrastructure.

Figure One. Strategy of Things Smart City Ecosystem Framework.

 
Many municipalities are considering and planning smart city innovation labs today. Over the past year, we helped to create, launch and operationalize San Mateo County’s Smart Region innovation lab (SMC Labs). From this experience, we share ten best practices for civic innovation leaders and smart city planners.
 
 
Ten Smart City Innovation Lab Best Practices
 

Develop a well defined innovation sandbox. Every smart city innovation lab has an unique mission. That mission is specific to its community, capabilities, priorities, and surrounding ecosystem. However, it is easy to get distracted and work on the “next shiny object”, vanity projects and “me too” innovation pilots. These projects don’t add value, but take resources and focus away from the problems the lab was created to address.

Build innovation discipline and focus by defining a “sandbox” from the start and updating it annually. The innovation sandbox defines clearly what types of projects are in-scope and which ones are not. The criteria includes alignment with city or department priorities, problem set type, problem owner(s) or sponsors, budget availability, cost, resource requirements, and organizational jurisdiction.

 

Create procurement policies and processes for innovation projects. Innovation pilots fall outside the “sandbox” municipal procurement processes and policies operate in. These pilots may work with start-ups with limited operating history, use immature and evolving technology, or bought in non-traditional ways (“as a service”, loans, etc.). This mismatch leads to higher risks, extra work and long sourcing times. Due to this, many vendors choose not to work with cities.

Effective smart city innovation labs are agile and responsive. They employ new procurement policies and practices designed specifically for the unique needs of innovation projects. This includes simplified processes and compliance requirements, new risk management approaches, faster payment cycles and onboarding models.

 

Build a well defined plan for every innovation project. Many innovation pilots are “successful” during the pilot phase, but fail during the scaling phase. This is because the pilots were not fully thought out at the start. Some test a specific technology or solution, and not the approaches. Others test the wrong things (or not enough of the right things). Some are tested in conditions that are not truly reflective of the environment it will be deployed into. Still others don’t test extensively enough, or over a sufficient range of conditions.

Successful projects in smart city innovation labs involve extensive planning, cross-department collaboration, and a comprehensive review process throughout its lifecycle. They have well defined problem statements. They define a targeted and measurable outcome, a detailed set of test requirements and specific success criteria. While innovation projects contain uncertainty, minimize project execution uncertainties with “tried and true” project management plans and processes.

 

Continuously drive broad support for the lab. A successful civic innovation lab thrives on active support, collaboration and engagement from stakeholders across the civic ecosystem. However, many city departments and agencies operate in silos. Launching and having an innovation lab doesn’t mean that everyone knows about it, actively funnel projects to it, or support and engage with it.

Successful smart city innovation labs proactively drive awareness, interest and support from city leaders, agencies, and the community. This includes success stories, progress updates, technology briefings and demonstrations, project solicitations, and trainings. They engage with city and agency leaders regularly, host lab open houses and community tours. They conduct press and social media awareness campaigns. Regardless of the “who, how and what” of the outreach, the key is to do it regularly internally and externally.

 

Measure the things that matter - outcomes. There are many metrics that an innovation lab can be measured on. These range from the number of projects completed, organizations engaged, number of partnerships, investments and expenses, and so on. Ultimately, the only innovation lab metric that truly matters is to be able to answer the following question - “what real world difference has the lab made that justifies its continuing existence and funding?”.

All innovation lab projects focus on solving the problem at hand. It must quantify the impact of any solutions created. For example, many cities are monitoring air quality. A people counting sensor, mounted alongside an air quality sensor, quantifies the number of people impacted. Any corrective measures developed as a result of this project can now point to a quantifiable outcome.

 

Build an innovation partner ecosystem. A smart city innovation lab cannot address the city’s innovation needs by itself. A city is a complex ecosystem comprising multiple and diverse domains. Technologies are emerging and evolving rapidly. New digital skills, from software programming to data science, are required to build and operate the new smart city.

Successful smart city innovation labs complement their internal capabilities and resources by building an ecosystem of strategic and specialist partners and solutions providers, and subject matter experts. These partners are identified ahead of time, onboarded and then brought in on an as-needed basis to support projects and activities as needed. This model requires the lab to build strong partnership competence, processes, policies and the appropriate contract vehicles. In addition, the lab must continuously scan the innovation ecosystem, identify and recruit new partners ahead of the need.

 

Test approaches, not vendors or solutions. Real world city problems are complex. There is no magic “one size fits all” solution. For example, smart parking systems use sensor based and camera based approaches. In some cases, both approaches work equally well. In other cases, one or the other will work better. A common innovation mistake is to only test one approach or fall in love with a specific vendor solution and draw a generalized conclusion.

Effective innovation lab projects focus on testing various approaches (not vendors) in order to solve problems effectively. Given the rapid pace of technology evolution, take the time to identify, test and characterize the various solution approaches instead.

 

Employ a multi-connectivity smart city strategy. There are many options for smart city connectivity. These include, but not limited to cellular 3G/4G, Wi-Fi, LoRaWAN, SigFox, NB-IoT and Bluetooth, and so on. Use cases and solutions are now emerging to support these options. However, some smart city technologies in the marketplace work on one, while others work on more. There is no “one size fits all” connectivity method that works everywhere, every time, with everything.

To be effective, smart city innovation labs need to support several of these options. The reality is that there is not enough information to know which options work best for what applications, and when. What works in one city or region, may not work in another. Pilot projects test a possible solution, as well as the connectivity approach to that solution.

 

Make small innovation investments and spread them around. Open an innovation lab and a long line of solutions vendors will show up. Everyone has a potential solution that will solve a particular problem. Some of these solutions may even work. Unfortunately, there is not enough budget to look at every solution and solve every problem.

Focus on making smaller, but more investments around several areas. Overinvesting in one vendor or one approach, in a market where technologies are immature and still evolving, is not wise. Invest enough to confirm the pilot outcomes. A more detailed evaluation of the various solutions and vendors should be made when the pilot moves out of the innovation lab and into a formal procurement and RFP phase.

 

Simplify administrative and non-innovation workloads. While innovation pilot projects are challenging, interesting and even fun, administering and managing the projects are not. These unavoidable tasks range include managing inbound requests, proposals and ongoing projects. These tasks increasingly consume time and resources away from the core innovation activities.

Effective smart city innovation labs get ahead of this by organizing, simplifying and automating administrative activities right from the start. For example, SMC Labs reviews inbound proposals once a week and organizes follow up calls and meetings on a specific day once every two weeks. In addition, the lab uses a tracking and pilot management tool (Urban Leap) to track innovation projects. Administrative and management activities are unavoidable. However, advanced planning and tools help reduce the burden to keep the lab's focus on innovation.

 

Benson Chan is an innovation catalyst at Strategy of Things, helping cities become smarter and more responsive through its innovation laboratory, research and intelligence, 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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The benefits of using Edge Computing / Machine Learning solutions are very attractive to manufacturers because allows minimize latency, conserve network bandwidth, operate reliably with quick decisions, collect and secure a wide range of data, and move data to the best place for processing with better analysis and insights of local data.
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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.

 

About the Author: Taylor Welsh is a writer for a Speedtronic reseller, located in Fuquay-Varina, NC. To see more, visit AX Control.

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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 leverages 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 the 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 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 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...

Feel like you have something to tell about your IIoT use case?

Drop me a line below!

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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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