IoT and edge computing go together like Sherlock and Dr. Watson: They are more successful when they work together, but they serve distinct roles to achieve desired results.


Despite how inherently interconnected IoT and edge computing are, the architect must lay the groundwork for the relationship to work. Each IoT and edge computing component affects the other. Architects must have a diverse set of skills because each design element changes how components fulfill their roles and their ability to scale and integrate.

Organizations have more than 1.5 million combinations of IoT and edge computing architectures to choose from, writes Perry Lea. In his book, IoT and Edge Computing for Architects, the Microsoft director of architecture explores IoT and edge computing basics, including the definitions, use cases and components; standards and protocols; and data analytics. Over the course of the book, readers follow the journey of IoT data to learn the intricacies of a well-designed IoT and edge architecture, starting with sensors and working through near- and long-range communication to migrate through the edge to the cloud.

Below is an excerpt from the IoT and edge computing book: Chapter 2, “IoT Architecture and Core IoT Modules.” In a high-level overview, this chapter examines the various IoT and edge computing components, how they interconnect and the architect’s approach to their role.

IoT and Edge Computing for Architects, Perry Lea

Click to learn more about the title.

Particular areas of IoT and edge computing have challenged design teams and required detailed knowledge, such as future scalability. Architects must balance the value of different design choices based on why their organization or customer wants to use IoT. They must understand sensor physics, energy consumption, telecommunications, security challenges and cloud-based machine learning to meet the desired requirements.

Lea’s book can prepare architects for the ideal design of IoT and edge computing architecture and it discusses successful real-world use cases for readers to learn more.

Click here to read Chapter 2 of IoT and Edge Computing for Architects.

Developers and engineers have improved the technology behind IoT edge computing architecture, but architects still…

Developers and engineers have improved the technology behind IoT edge computing architecture, but architects still must overcome challenges that have plagued organizations since IoT technology first emerged.


Long before “internet of things” became part of IT vernacular, organizations connected embedded systems, hardware and software, such as office printers or scanners, to move data. Technology has progressed to bring high-performance computing into small, inexpensive embedded devices in accordance with Moore’s law. Advancements over the years have led to very small IoT devices that compute at the edge of networks, and edge computing that extends the cloud closer to data sources.

Despite the progress, IoT and edge computing deployments create many obstacles that have challenged development teams since they first connected embedded systems to the network, including connectivity, security and power supply. In the book IoT and Edge Computing for Architects, Microsoft Director of Architecture Perry Lea explored what architects must know to design IoT edge computing architecture and how industry experts continue to develop the surrounding technologies.

In an interview shown below, Lea discussed common IoT edge computing hang-ups, as well as advice on designing IoT and edge architecture.

IoT and Edge Computing for Architects, Perry Lea

Editor’s note: The following interview was edited for length and clarity

What is the most challenging part of designing architecture for IoT?

Perry Lea: There’s a technical point of view and a business point of view with two separate problems. From a technical point of view, no two IoT systems are alike. They have computing elements. They have software. They have connectivity. In a lot of cases, connectivity is a hard problem because an IoT system doesn’t have good basic connectivity. A lot of technologies rely on LTE or cellular connectivity, but that doesn’t touch every square meter on the face of the earth. You lose connectivity. What do you do in those cases?

The other issue is security. IoT devices are ripe honey pots for certain security problems. If you look at the Mirai virus — the nation-state Stuxnet attack on Iran’s centrifuges — those are issues because IoT devices have not matured or haven’t gone through the growing pains of security issues. If you look at all the security issues with consumer and enterprise IT in the early 2000s with different viruses and worms, they went through the paces of hardware and software design to try to work through these types of attacks. IoT devices have been pretty lax. What you see today is a lot of malicious software exploiting 20-year-old techniques on IoT and embedded systems. It’s the weak link in the chain.

Perry Lea

Perry Lea

Another technical hurdle, besides communication, is power. A lot of these devices you simply can’t plug in. And that’s related to your communications, related to a good architecture, because if you’re based on a battery, you only get so many packets through your communication channel before you drain your battery. That’s an ongoing issue.

On the business side, the big challenge for IoT or edge computing is a lot of industries haven’t crossed the chasm going from a proof of concept to deployment or commercialization of IoT. There’s a level of maturity to see how they can capitalize on this from bringing in a better margin or customer value. That’s just the growing pains of the business.

What challenge of designing IoT and edge computing architecture interests you most?

Lea: What’s interesting about IoT is it touches hardware; you can even have inference engines running in silicon on the edge — you deal with near-range communication, long-range communication, embedded systems — and they all have to play together. What I like about challenges is constraints. If I have an unconstrained system — like, if I have the most beefy server in the cloud — and I wanted to write some software, I have complete freedom and autonomy to do that. You don’t get that with IoT. You don’t get that with a lot of edge systems. You’re dealing with a series of technical constraints.

What common issues do you see trip up organizations when they’re designing an IoT edge computing architecture?

Lea: One thing that I’ve seen pervasive is trivializing the complexity of IoT to build a really successful commercial or enterprise product. There’s a lot of thought around, ‘How hard can this be?’ An organization that’s less mature in this phase will say, ‘Well, on weekends, I played with a Raspberry Pi, and I got some sensor data running.’ If you build a system around that, or around that philosophy, it just is not commercially scalable. There’s a lot of issues when you treat the system trivially.

You have to extend yourself from the hobbyist mentality to the true engineering discipline. That’s when you have a very successful product. In the consumer and enterprise space, those are well designed from the hardware to the software, to the communications and to the system.

What advice would you give an IoT architect or development team about designing IoT and edge architecture?

Lea: You have to start with what problem you’re trying to solve from a business, technical or customer point of view.

If you have a problem at hand, the next thing is to look at the problem holistically. Look at it from a hardware, software and communication point of view.

The third thing becomes how do you anticipate scaling? Let’s say you have a proof of concept and you’re a hobbyist and you get something to work with a Raspberry Pi. That’s fine. How do you scale that? How do you scale that across regions? You have to start worrying about communication between cellular systems in Asia versus cellular systems in North America versus cellular certification in Europe. They don’t all play nice, and they’re different designs.

The fourth thing is, how are you going to monetize this? If you’re extracting value out of this device, you have to look at the whole value chain, because when you go to scale, you have to worry about paying for communication service-level agreements per node. Am I amortizing the capital expense for the IoT device itself? Is there middleware that I have to license that runs on the device? How am I paying for that? And then how am I paying for cloud and cloud provisioning? Is that per node, per the amount of data that’s adjusted in aggregate or even data retention? Am I paying for different services in the cloud? And so that all comes back to scalability. There’s some dynamics there that you have to have to work through as a business when you when you start building this. In an IoT system, your value is not just one sensor, one node. It’s working at scale to thousands, hundreds of thousands of different nodes.

What else should teams know about designing IoT and edge computing?

Lea: There’s room to grow on the edge of IoT. Scaling from a hardware level, you can rely on Moore’s law to start allowing more features and more technologies to be pushed to the edge. Putting more intelligence on the edge matters, especially when you’re dealing with latency-sensitive systems or systems that deal with huge amounts of unstructured data. That’s where the industry is growing.

The third thing that I anticipate is that there’s probably going to be room for growth in different types of sensors: flexible sensors, portable electronics, different types of elements that give a machine inherent knowledge of the environment. The fourth thing is covered by a lot of other people and that’s the buzzwords around 5G. That has to be taken with some reservation. There’s a lot of hype there. It is a communication system, but it allows for some new technologies like multi-access edge computing to become relevant. But it really is a communication system at the end of the day, and there’s all kinds of challenges with any communication system. That has to be taken with a grain of salt.

Women Tech Founders, a Chicago-based organization dedicated to advancing women in the tech industry, recognized 14 women from around the world on their achievements in tech.

The third annual Women in Tech Awards were hosted Thursday night at Galleria Marchetti. The 14 winners were chosen from 65 finalists hailing from eight different countries, said Terri Brax, the co-founder and CEO of Women Tech Founders. More than 3,000 ballots and over 40,000 votes were cast within the competition’s first week of voting.

About half of the winners hail from Chicago, while the rest come from several other U.S. cities and London. Instead of giving out plaques or trophies, Women Tech Founders gives winners MMA-style belts.

“It represents the fight that underrepresented people have in industries like tech,” Brax said.

The event also included a pitch showcase in which female founders shared their businesses in front of a panel of judges made up of female venture capitalists. Ty’Lisha Summers, the founder of student loan-repayment startup SpenDebt won the pitch competition and $1,000.

“We’re reflecting on the ways we can grow the community for all women, not just certain groups of women,” Brax said.

See all 14 of the 2019 Women in Tech Awards winners below:

Women Tech Founder Andrea Srestha, co-founder, LuminAID (Chicago)

Ally Award Erika Jefferson, founder and president, Black Women In Science & Engineering (Chicago)

Education Award Roya Mahboob, CEO and president, Digital Citizen Fund (New York)

FinTech Award Natalie Gil, chief technology officer, The Blockchain Challenge (Boston)

Health Award Feyi Olopade Ayodele, founder and CEP, CancerIQ (Chicago)

Inspiring Innovator Award Michelle King, head of integrated strategy for gender innovation, UN Women (New York)

Intelligence & Automation Terri Foundray, founder and CEO, RUMBLE (Kansas)

Investor in Women Chenxi Wang, managing general partner, Rain Capital (California)

Lifestyle Chanay Walton, founder and CEO, My Pay Circle (Chicago)

Manufacturing & IoT Delna Sepoy Straus, co-founder and chief operations officer, KEYO (Chicago)

Media & Marketing Melissa Lederer, chief experience officer, mHUB (Chicago)

Social Impact Jamila Parham, founder, The Tech Unicorn (Chicago)

Talent Alicia Driskill, founder and CEO, EvolveHer (Chicago)

International Women in Tech Tugce Bulut, founder and CEO, Streetbees (London)


The way people talk about it, data can seem like a revolutionary notion. But data has always had value in manufacturing. You think Henry Ford wasn’t crunching numbers and keeping score as production of his Model T went from a takt time of 12 hours per unit to 2.5? Of course he was. The only thing that has changed is how vital this raw resource is to staying competitive in a post digital transformation landscape, where cutting-edge technology is slashing design, production and delivery times to a sliver of their previous state.

“Competitive” might be the wrong word. “Alive” is more like it. In the next decade, data—or rather, getting the most out of your data—could be the one thing keeping you in business.  
Hopefully this isn’t taken as a warning, or even a revelation—it’s about as insightful as saying a human needs oxygen and food to live. But it could be a gentle reminder that change is coming fast, and according to our own data—collected via a survey conducted this past July—there are far too many technology procrastinators out there who are at risk of getting left behind.
Why is this happening? Well, we’ll just have to look at the data.

First, let’s look at the respondents. We received responses from more than 600 people and winnowed that down to 386 who currently identify as manufacturing leaders, from CEOs to R&D managers. About 82% were from North America, 7% from Asia and 5% from Europe.


Industryweek Com Sites Industryweek com Files Tech Survey Title
Despite nearly 99% of U.S. manufacturers being small businesses, the representation was surprisingly balanced, with about 40% of respondents from companies with greater than $100 million in revenue and 60% below $100 million in revenue.


Industryweek Com Sites Industryweek com Files Tech Survey Company Revenue 0
Industrial Internet of Things: Haves vs. Have-Nots

The most glaring difference among manufacturers based on revenue is their adoption of the Industrial Internet of Things. If data is the commodity, this is its supply chain. Look at how many more large enterprises have deployed IIoT versus small- to medium-sized enterprises:

Industryweek Com Sites Industryweek com Files Tech Survey Iiot Revenue 0
The results are not unexpected, as big companies likely have more employees and more money to throw at a deployment.

Due to this fundamental fact, SMEs must be more selective about their investments, says Juliane Stephan, a PwC consultant who specializes in smart factories and connected supply chains.

“It’s very crucial to make the right investment, because they usually don’t have as many funds available like large companies that they can just free up,” the digital ops expert says. “They focus more on the outcomes and specific use cases.”

The average SME is more risk averse, which is backed up by a 2016 study by scholar Ralf Peter Wüstermann. But the thing is, there doesn’t seem to be a lot of risk in deploying IIoT. Among the 30% of big businesses that have been running an IIoT application for at least a year, 15 times more said the project is meeting their expectations than not. With the under $100 million crowd, it was 12 times. Singling out the under $10 million group, not one respondent said the project was not meeting expectations.

Furthermore, I have been covering the IIoT in depth since 2015, and you don’t have to look hard to find willing partners and integrators to offer an affordable go-to-market plan. One issue is finding the right partners, explains Terri Foudray, CEO of Rumble, an IoT systems integrator.

“Unlike other technologies, it takes many partnerships and vendors to make a successful IoT deployment,” Foudray says. “There are thousands of vendors out there, and each vendor has a specialty that they deliver to the stack.”

The question then is, “How does one determine which vendors to use in each segment of the project?”

Foudray rattles off an exhaustive list of things to consider in this process, from assessing hardware issues such as sensors and edge devices to managing the data, from measuring anomalies to employing proper data science. If I were an SME leader and heard how involved it is, I, too, would have serious reservations about making the IIoT a priority.

On top of that, Foudray mentions 75% of IIoT projects fail, citing a 2017 Cisco survey. “People hearing about failure is part of the problem,” she says.

The SME aversion to the acronym IIoT was noticeable this year. Only 11.5% of respondents marked it as the most critical technology to their company’s success, behind both digital/additive manufacturing and automation/artificial intelligence. In 2018, 15% in the under-$100 million category said IIoT had the greatest potential to transform manufacturing.

That data point is a misleading, as the report itself does not suggest avoiding the IoT. After all, it takes failure to succeed, to learn from your mistakes and course-correct.

But if a product you make isn’t taking off like you’d expected, you don’t blame the customer. You think of a new way to make and/or market it.

“It’s difficult for the client or customer to adopt IoT right now the way it is being presented to them,” Foudray says. “As the vendors start to partner, and by doing so create more complete solutions, it will make it easier for the clients to adopt and the vendors will be more successful.”

That provides a little optimism for the future, but what about right now?


“We don’t use the word IoT a lot, because there’s only negative press around IoT,” says Bernhard Mehl, CEO at Kisi, a Brooklyn-based manufacturer of access control systems that works with cards and mobile devices. It absolutely is IoT-related. He says notorious hacks of major companies can help dissuade an IT manager from adding more potential attack surfaces.

He finds that companies often don’t have an official IoT strategy in place, but that, too, can be misleading.

“If you ask if they want their company more decentralized or if they plan to facilitate employee mobility between spaces, they would be the first to say yes,” Mehl says. “That only works if you run centrally and your devices are internet-connected.”

Mehl notes that in his operation, which assembles and packages the wall-mounted devices, collecting more data is an appealing prospect, and could provide more insight into failure rates and how many units are packaged versus produced. As a small company that just moved out of the Brooklyn Navy Yard hub of tech startups, Mehl says, Kisi likely will adopt more affordable ecommerce software for its inventory tracking and processing features.


With a few tweaks and some added hardware, even a ring scanner or two synched to the system, that would fit the definition of an IIoT deployment.
This humble solution also fits what Foudray would consider a great start for any manufacturer large or small: “You need the culture aligned and a clearly defined problem—know the business case and start small and not bite off too much.”

That’s an important thing to remember when you ingest anything, especially data. Maybe in the second half of this fourth industrial revolution, vendors will offer portions more in line with industry appetites, so no one goes hungry because they can’t afford the full dinner.

Takeaways from Other Technologies:

Industryweek Com Sites Industryweek com Files Tech Survey Tech Overall


As should surprise nobody, robots and AI won “Most Likely to Succeed.”

In the last issue, we focused on robots, so I won’t belabor the benefits here, but I am interested in their impact on jobs. Of respondents who answered “automation/AI” and who also said they use robots in their operations, 54% selected “humans will adapt to new robot coworkers and jobs will increase” on the question of human/robot relations in the next five years. That’s double the people who thought “more people will be replaced than added.” One lone soul predicted the robopocalypse.

Interestingly, among respondents with positive feelings toward automation, employment increased at 59% of these companies and decreased at 20%. Overall, 54% of respondents said jobs increased and 19% indicated they had decreased.

How important is automation overall to manufacturing? The good news, if you believe robots are eyeing your job, is that only 15% of survey respondents said they are critical, while 32% said robots sustain growth but they could get by without them. Half don’t rely on them for core business functions or use them at all. Singling out SMEs, that percentage rises to 60%.

So where are these robots? They’re everywhere. The most common locations include assembly (19%), inspection (21%), pick-and-place (30%) and material handling (48%).

Industrial Wearables

If I were to make one sweeping statement about wearables based solely off this survey’s data, it’s that very few manufacturers care about them. Seventy-seven percent replied they do not use wearables, and 17% of this group were part of $1 billion-plus enterprises. More than half of respondents who don’t use wearables also remarked that smartglasses did not provide any benefits and/or were a “waste of time.”

Industryweek Com Sites Industryweek com Files Tech Survey Smartglasses

These responses are kind of crushing to me, as this is the technology I personally see as having a substantial effect on the manufacturing plant. And the benefits, regardless of platform, are evident if you ever need both of your hands for something but need to look at instructions or a smart device.

Smartglasses enable data visualization and can connect remote experts to problems thousands of miles away, while exoskeletons boost strength and prevent injury. Wearing a personal tracking device can help you monitor health and environmental safety.

Wearables also can be personal training devices, both to capture tribal knowledge and to assist new employees by guiding them through unfamiliar tasks. BMW is deploying the RealWear HMT-1 at all 347 American service centers, where technicians will use them for maintenance and repair applications.

And training is a huge deal. When asked, “What’s the biggest leadership challenge you have when dealing with implementing new technology in your plant/facility?” 30% said training employees, customers and partners to use it.

Industryweek Com Sites Industryweek com Files Tech Survey Leadership

A simple augmented reality application I tried at Ford with Google Glass Enterprise Edition rendered a 3D model of the part I needed to assemble onto the monocular display, and I was able to put a suspension component together in a few seconds.

Just like with an IIoT deployment, setting up wearables takes planning, integration, cybersecurity actions and software development. Cost may still be an issue. RealWear plans to use some of its recently acquired Series B money to create a Wearable-as-a-Service model, paying monthly.

“There’s a necessity to bundle an offering and make it so bloody simple for mining companies in Argentina or Chile that want them on 1,000 employees but can’t pay for them upfront because they are running on low margins,” says RealWear CEO Andy Lowery. “We just charge $50 per person and they order 1,000 immediately. One or two uses, they start seeing ROI and pretty soon they pay for the device on the savings they have.”

It appears that smartglasses solve 68% of the tech problems leaders face today, yet many manufacturers are unaware of how these tools can help. Maybe the problem with all this new technology emerging on the scene is that there is too much: too much data, too many decisions to make, to many vendors to choose from, too many case studies to read. And there’s never enough time.

Maybe what the data really says this year is that people want simplicity. You don’t buy tech to make your life harder; it’s so you don’t have to worry as much.
It looks like Lowery has caught on.

“You want to leave them a little bit of optionality, but I’m finding out you don’t want to lead with a science fair project with these big businesses,” says Lowery. He mentioned that manufacturers don’t want 120 applications thrown at them like it’s a Cheesecake Factory menu. “It’s a much better route to market to say, ‘Here’s my recommendation, this is the whole package, this is who trains.'”

Here’s hoping that next year, more tech providers can follow suit. IW

OVERLAND PARK, Kan., April 17, 2019 – Kansas City start-up RUMBLE was named Industrial Internet of Things (IoT) Solution Deployment Leader of the Year by Compass Intelligence for advancing the IoT industry through leadership and supporting ROI-based deployment of connected solutions. The 7th annual Compass Intelligence awards honors the top companies, products, and technology solutions in mobile, IoT, and emerging technology industries.

“We are honored to be recognized for our commitment to helping businesses utilize disruptive technologies to create positive business outcomes. We recognized the marketplace gap for end-to-end IoT solution designers and implementers. Filling that gap with qualified expertise has proven to be a successful model for RUMBLE,” said Terri Foudray, RUMBLE Founder and CEO.

“Executives today are seeking opportunities to gain performance advantage and implementing IoT solutions provides that competitive edge. IoT is about making connections to the business data in near real-time – as it is happening. This visibility provides an ability to act when it improves outcomes. Those outcomes increase revenue, profitability, engagement, and compliance.”

“There is more data available today than ever before,” said Perry Lea, RUMBLE cofounder, “but collecting the RIGHT data is critical, data that provides business insight and allows you to make informed decisions and take action. That’s when data becomes a competitive advantage.

Compass Intelligence selected it’s “Of the Year” award winners through observation and interaction with many companies throughout the year.

“We believe there is a gap in the market in terms of core companies that bring the disparate pieces together and help expedite deployment,” said Stephanie Atkinson, CEO and founder of Compass Intelligence. “We believe RUMBLE is filling that gap and leading with business outcomes and applying it to real, live business applications. That was the key driver for the award. The industry needs more companies like RUMBLE to reach our full potential in IoT.”

“RUMBLE and the other award winners represent world-class solutions that advance the industry and provide innovation in a rapidly growing tech market.”

Here is the full list of winners.

About Compass Intelligence
Founded in 2005, is a market analytics and consulting firm specializing in metrics-driven market intelligence and insights for the mobile, IoT, and high-tech industries. Compass Intelligence provides executive insights, market sizing/forecasting and modeling, competitive analysis, strategic consulting, advisory services, trending analysis, and survey research services. Compass Intelligence helps guide strategic business decisions, and support in the success of our clients through delivering content engagement, go to market planning, competitive positioning, and strategic advisory.

RUMBLE founded March 2018, improves business performance through real-time data delivery solutions. RUMBLE’s highly specialized team partners with clients to capture the benefits from innovative technologies such as the Internet of Things, Artificial Intelligence, and Situational Awareness software. RUMBLE’s solutions are designed to eliminate siloed data, stagnant data, reporting lags, and data disconnection. Visit