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Making sense of all the terms and catchphrases being bandied about to describe the Industrial Internet of Things can be difficult. Nonetheless, a common vocabulary is critical to facilitating the education required for broader development and adoption of technology that promises seismic shifts in virtually every sector of manufacturing.

In my position as an editor, precise language is particularly important. That’s why I’ve begun compiling a list of definitions for some of the most common words and phrases I’ve encountered in my own reading on the subject. Although by no means comprehensive, this practice has proven helpful in keeping my copy (and my head) as clear as possible on a subject that’s increasingly important to our readers. Beginning with a definition of IIoT itself, here are the meanings of five common terms associated with this technology:

1. Industrial Internet of Things (IIoT) is a term derived from the broader concept of the Internet of Things (IoT), whichdescribesthe increasing interconnectedness of the stuff we all use in our daily livestoone another and to the internet (or an intranet, or both). The idea is not just to exchange and collect data, but to act on that data to make things better. (One commonly cited example is a “smart” thermostat.) IIoTis the same concept applied to industry. Examples range from “smart” buildings and power grids to “smart” transportation networks.IIoT might initially take the form of a machine tool status monitoring system.

Large-screen TVs keep everyone at CNC Swiss-turning specialist Carolina Precision Manufacturing (CPM) aware of how closely machines are meeting their goals.

2. Data-driven manufacturing implies that manufacturing processes are driven forward by data—by facts, figures and other verifiable information, as opposed to guesses, assumptions and intuition. (It’s also the name of an MMS Online Zone where you can find everything we’ve written about IIoT).

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Almost 3,000 miles from home and standing on an island that was once the site of a military installation, Ken Loo stared intently into a set of goggles, his fingers twitching over controls as he reacted to the scratchy drone video beaming directly into his eyes.

Hurtling through the air overhead at speeds as high as 60 miles per hour, his and other drones transmitted the images to pilots who were competing in the U.S. National Drone Racing Championships last weekend on New Yorks Governors Island.

Behind safety netting, a small audience gathered to sip beer and watch the devices fly around the course, weaving in and out of obstacles. Some put on orange spectator goggles, which allowed them to toggle between feeds from the drones onboard cameras.

Loo, who goes by the call sign FlyingBear, had traveled from California for the competition that he had spent months preparing for like many of the dozens of pilots. Vying for the competitions $50,000 grand prize, they are the pioneers of one of Americas newest sports.

Over the past two years, weve really seen the drone racing sport explode, he said. I started just racing with friends at a local park.

Indeed the sport has taken off in recent years.

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Big Data and IoT Solve Food Safety


Grocery stores operate on paper-thin profit margins, and cannot afford to overstock inventories or to let food go to waste. Grocers and food suppliers also want to avoid food contamination issues that can negatively impact their reputations and discourage consumers from doing business with them.

For stakeholders in both of these groups, big data is making a difference by helping them manage food chain supply challenges. Here’s what’s happening.

Barcode and sensor-based Internet of Things (IoT) data is being applied to food chains from their points of origin (e.g., in the orchard where apples are picked) to their follow-up destinations in processing plants, storage warehouses, distribution points, and in the grocery stores. The end-to-end tracking and traceability that sensors and barcodes provide enable store chains, food brands, and goods supply networks to quickly identify points of origin and distribution if it’s discovered that food is contaminated. This facilitates rapid mitigation of a situation.

In 2011, President Obama signed into law strict food monitoring and traceability measures that included traceability data such as the box or case of fruit, its point of origin, the name of the product, the name of the transportation provider, etc. The information is captured and recorded in a central database. “This information is vital for meeting the new requirement of tracing the product ‘one forward and one back,’ in each point of the supply chain,” said Don Ratliff, co-executive director of Georgia Tech’s Supply Chain & Logistics Institute, in an interview with Material Handling & Logic.

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The IoT Threat to Privacy


As the Internet of Things becomes more widespread, consumers must demand better security and privacy protections that don’t leave them vulnerable to corporate surveillance and data breaches. But before consumers can demand change, they must be informed which requires companies to be more transparent.

The most dangerous part of IoT is that consumers are surrendering their privacy, bit by bit, without realizing it, because they are unaware of what data is being collected and how it is being used. As mobile applications, wearables and other Wi-Fi-connected consumer products replace dumb devices on the market, consumers will not be able to buy products that dont have the ability to track them. It is normal for consumers to upgrade their appliances, and it most likely does not occur to them that those new devices will also be monitoring them.

After an Electronic Frontier Foundation activist tweeted about the unsettling similarity of the Samsung Smart TV privacy policy which warned consumers not to discuss sensitive topics near the device to a passage from George Orwells 1984, widespread criticism caused Samsung to edit its privacy policy and clarify the Smart TVs data collection practices.

But most people do not read privacy policies for every device they buy or every app they download, and, even if they attempted to do so, most would be written in legal language unintelligible to the average consumer.Those same devices also typically come with similarly unintelligible terms of use, which include mandatory arbitration clauses forcing them to give up their right to be heard in court if they are harmed by the product. As a result, the privacy of consumers can be compromised, and they are left without any real remedy.

Increased corporate transparency is desperately needed, and will be the foundation of any successful solution to increased privacy in the IoT. This transparency could be accomplished either by industry self-regulation or governmental regulation requiring companies to receive informed and meaningful consent from consumers before collecting data.

Generally, industries will respond if their customers demand more privacy. For example, after surveys revealed that new-car buyers are concerned about the data privacy and security of connected cars, the Alliance of Automobile Manufacturers (a trade association of 12 automotive manufacturers)respondedby developing privacy principles they agreed to follow.



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Foxconn is really big, and it’s about to get bigger after completing the acquisition Friday of once-great Japanese electronics maker Sharp. Foxconn doesn’t sell books, and its $1.6 billion in R&D spending last year was about 11 percent of Amazon’s total (and also much lower than the R&D spending of the other three companies listed above). It just so happens that contract manufacturing of electronics is a really low-margin business.

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Its hard to deny that the average consumer aims for both a less expensive product and at the same time a better one. While this may seem like having one’s cake and eating it too, it is up to researchers around the world to constantly figure out a way to make this possible.

With smartphones, tablets, solar cells and LED lights already well into the mainstream and not going away any time fast, doing the above in these sectors in increasingly important to keep that competitive edge.

It seems as though researchers at RMIT and CSIRO are hoping to do just that using a method of light based printing of electrical components with the help of both an inkjet and 3D printer. The end goal of their efforts is to quickly and cheaply manufacture circuitry by first drawing the electric circuit using a uniquely formulated ink, the printer and a very powerful camera flash.

Once the flash hits the printed electronic strip, the chemical and physical properties of the material that has been printed instantly transforms from an electrically insulating to electrically conductive material.

So far, the process involves embedding onto a flexible, foldable material with possible aims of entering into the wearables market. An example of the potential is of a solar cell that can be used on your backpack or laptop while walking around without the worry of relying on traditionally rigid circuitry.

So while it seems Enrico Della Gaspera, the brains behind the research, has come up with a novel way of manufacturing state of the art circuitry, hes also managed to do it on the cheap. Since the developed method doesn’t require high temperatures traditionally seen in the manufacture of electronics and he’s using lower cost materials and less electricity intense production environments, more can be done with less.

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In the year 2000, the music business was still strong. Record companies produced albums and shipped these physical objects to the stores that sold them.The internet was slowly becoming a system of mass consumption and distribution, but most consumers still purchased physical media. And while the record industry was aware of piracy online, the threat seemed minimal.

The music industry tried to stop this large-scale piracy by pursuing both the platforms and individual downloaders including poor college students. But public opinion turned against the industry. After all, stealing digital music is intangible; its different than physically swiping actual CDs or tapes from brick-and-mortar stores. And while today many people access their music legally, its safe to say that music industry revenues have yet to recover.

3D printing, another revolutionary and disruptive technology, makes it cheap and easy to produce physical objects. And just as home copying has changed the copyright industries beyond recognition, 3D printing is poised to do the same to patent-based industries.

That means practically any business that makes physical objects will potentially face a Napster scenario. It may not happen to everyone, but as printer technologies improve and more materials such as proteins, specialized polymers, metals and other chemicals become available for printing, it will happen to many.

Take the pharmaceutical industry. Just like a musical recording, where most of the costs are incurred while producing the initial release (hiring the musicians, booking the studio, editing and the like), the bulk of the cost of developing a new pill goes into the front end: research and development, clinical trials and getting through the FDA approval. In fact, the raw ingredients may cost only a few pennies. And 3D printing or digital manufacturing and distribution, as its also known will make reproducing and delivering these pills, lawfully or unlawfully, much easier.




The shop floor is rapidly changing as it evolves from a place bound by hands-on labor and interpersonal communication skills to an environment of smart machines that collect and analyze data, captured in real-time, to provide valuable insights into the manufacturing process. Meanwhile, the skills gap widens as advanced manufacturing firms struggle to find and train workers with the skills they need to keep pace with the technological-industrial revolution.

In order for our workforce to be a conduit rather than a barrier to the productivity improvements promised by Smart Manufacturing, we must take action without delay.

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For a company to succeed, it is essential that their practices are data-driven. For many companies, that means harnessing insights from Big Data. Addressing this issue head-on is Harvard-incubated Experfy. Co-founded by Harpreet Singh and Sarabjot Kaur, Experfy has built a vetted marketplace for data and Internet of Things consulting and training to help companies derive the actionable insights from Big Data that they need to be successful.

Big Data – the term used to refer to large data sets that are too complex for ordinary data processing systems to manage – is becoming an increasingly important aspect of business and innovation across the globe. For many companies, having effective tools to reveal trends and associations with sets of data is crucial. The Internet of Things (IoT) refers to tens of millions of devices connected to the Internet that are generating massive amounts of data.

Unfortunately, getting access to Big Data and IoT expertise isn’t always easy or cost effective for companies to do. According to McKinsey Global Institute, [b]y 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.

TechCrunch calls Experfya McKinsey in the cloud for big data consulting and Datanami calls it the Uber of big-data projects. With over 25,000 data experts, Experfy is now theworld’s largest Big Data and IoT consulting marketplace.

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Why Developers Are Starting To Focus On Machine Learning And Virtual Reality


Developer adoption is a sign of consumer adoption near on the horizon.

Machine learning, virtual or augmented reality and the Internet of Things have captured the general publics attention (if not yet their pocketbooks), anddevelopers are taking full advantage of all the newtechnology that will shape humanitys future.

A quarterly survey of over 16,500 developers by VisionMobile said that 41% of software buildersare now involved in data science or machine learning in one capacity or another. About33% do so in a professional capacity. According to VisionMobiles State of the Developer Nation Q3 2016 report, developers are inspired by emerging technologies, irrespective of the level of media hype leveled at any one particular industry trend.

Machine learning is slowly coming to the mainstream (think chat bots, natural language understanding and photo apps that understand what they see)but 67% of all developers see it as a viable side project, although they are still learning the ropes. The 33% of developers that are already working in the sector are biased towards enterprise and internal applications, with VisionMobiles survey suggesting that more companies will invest in machine learning in the near future as developer enthusiasm increases.

The really headline-grabbing breakthroughs in AI have come in the last year, so it is not surprising that machine learning has a lot of developers newly interested and exploring via a side project, VisionMobile said. Data science and machine learning in general have been helping companies do more with their data for several years now, so the fact that 41% of the developers in our latest survey are involved in some way makes sense too.

VisionMobiles latest quarterly report on the state of developer community was based on the online responses of more than 16,500 developers from 140 countries.

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