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New Niches for Startups Created by the COVID-19 Pandemic

Remote work and social distancing. These two approaches will define our lives behind 2020. The COVID-19 pandemic has put everyone into a new reality. The transition from our traditional lifestyle to isolation mode was anything but smooth. The whole world had to learn how to work and learn remotely and organize their leisure without leaving their homes. But the lockdown has also created a few niches for startup founders that no one thought of before.

A few months ago, we couldn’t imagine the world without public transport and traffic jams, busy restaurants and shopping malls, crowded parties and concerts. Now it is here. Governments shut down the long-awaited innovation programs to invest in healthcare technology – the industry that is getting the most attention nowadays. And for millions of people around the world, real-life has gone online – with evolving online shopping, online classes, and even online parties.

Despite restrictions easing in the vast majority of countries, no one can say when the lockdown will be completely over. Do we return to our normal lives this summer? Or the coming two years will be shaped by social distancing due to possible pandemic comeback?

One thing is already clear: we are in the worst economic downturn since the Great Depression. The unemployment rate has increased drastically. Many small businesses shut down; great economies enter the recession. This doesn’t sound optimistic, right?

But things are not that bad. The crisis opens many possibilities, as well. Here we discuss four industries that are experiencing a hard upgrade right now. If you want your company to be at the edge of improvements – hurry up and discover the potential startup niches!

Remote interaction – the new reality for private communication

For years, Zoom was a niche solution for online conferences and video calls. Since February 2020, it is the number one platform for all kinds of events: from birthday parties and blind dates to university classes and even city council meetings.

Currently, this is a forced measure, but experts predict that virtual meetings will become a substantial part of our reality even after the pandemic is over. Generation Z (also called Zoomers – what a coincidence!) prefer online communication to personal meetings. But the tools currently available still can’t provide the whole spectrum of features the young users are searching for. And this is one of the niches for a startup founder to investigate.

What do the myriad of online communication tools miss? User orientation, social features, and entertainment.

Zoom and the alike were built exclusively for business needs. Companies that couldn’t afford a custom internal communication system opted for a cost-effective SaaS solution. Their functionality fits the conference room, but not a virtual family lunch or a coffee-break. Zoom security issues are also a reason to look for alternatives.

Some of the tools start to play with enabling masks or changing backgrounds, but the complex solution for entertaining group calls is about to arrive.

There’s still the gap. And this is one of the potential startup niches to hit with a new app. First of all, analyze the apps popular among Zoomers right now. What features make them so unique? Filters, instant reactions, microformats, geolocation, augmented reality or interactive 3D models, built-in mini-games, group film streaming, etc. – any idea could be the game-changer.

To the door delivery – eliminating the need for traditional shopping

E-commerce was developing gradually, but it seemed like the full transition to online shopping was still a few decades away. Some buyers were not ready to decide on the product without having seen it with their own eyes; some others didn’t trust the seller they can’t personally talk to.

And now we are here. The only type of shopping that is available during the lockdown is online shopping. And it turns out that basically everything can be delivered to the door: food, cosmetics, consumer electronics, furniture, gardening tools, and pet care products. Now that everyone was forced to try e-commerce, they could evaluate the convenience of the process and a chance to save much time. And after taking this first step, many won’t even return to classical shopping.

We already watch online commerce making a great leap ahead. And when speaking of global e-commerce trends, to-the-door delivery is definitely one of the strongest ones. So we expect a growing number of P2P logistics services. This seems like one of the solid startup niches, right?

The international companies of on-demand delivery like Uber Eats, DoorDash, Glovo focused on food delivery from restaurants first. Now they expand their services and are ready to bring anything to the door of their clients. However, high-quality delivery is still not available in the majority of smaller cities all around the globe. This means millions of people are waiting for a local company to satisfy their needs.

Until such a solution appears, local businesses hire carriers or cooperate with taxi companies to deliver their products while clients choose to stay home.

For many small businesses, the COVID-19 pandemic was an impulse to go beyond their physical shops and start selling online. E-commerce is booming, so do related services like delivery.

Education erasing the borders

If this crisis happened twenty or even ten years ago, millions of teachers and tutors, music and art instructors, fitness trainers would become unemployed in the blink of an eye. The lockdown would make their further work impossible as such.

However, the technologies we have in 2020 make education, art, and sport accessible to everyone at home. And what is even more important – online classes have no geographical limits. You can have an online session with a trainer from the gym on the opposite side of the street, or join the online training held by the Olympics champion.

Just as online shopping, e-learning was available for years. However, only a few of us have tried learning remotely. The reasons? Some individuals complain about the lack of personal contact and instant feedback from the instructor; the others question their motivation and the ability to do their best while not being observed by a teacher.

But the lockdown happened, and thousands of people were at home without the possibility of visiting schools and universities, art classes, language courses, and sports sections. They have a lot of free time, and they are bored within four walls. However, they have the internet. So the time for online classes and training sessions comes. Many users have tried remote learning for the first time, and they are likely to keep the tradition after the quarantine is over.

Online education as one of the prospective niches for startup

What does this mean for the teachers, artists, fitness instructors, etc.? The geographical limits are down. Even living in a village, you can have hundreds of clients from any part of the country or even abroad.

Learning centers, language schools, fitness centers, and art clubs have the needed resources for a great leap: adopt e-learning to expand to new markets.

There are many platforms for online classes on the market; none of them is perfect, though. Consider it as one of the possible startup niches. You can build a software tool to make remote classes even more effective, or provide a marketplace platform for individual tutors. This type of application will be of great importance in the next few years.

On the other hand, think of the perspectives of the academic year 2020-2021. The chances are that it may be interrupted by the new wave of coronavirus. And this time, schools and universities want to be ready for this. Now they are working on the programs of remote classes and experimenting with different technical solutions. Some renowned universities can afford the development of custom learning platforms.

The rest of the educational facilities is looking for a ready solution to fit the needs of both professors and students. If you have deep experience in this domain, developing a Software as a Service platform for universities and colleagues may be a chance you shouldn’t miss.

Entertainment has gone online

The COVID-19 lockdown has taken work and education to online. The same happened to the entertainment industry.

Now when cinemas are closed, we want to watch movies online.

When a so awaited music festival is canceled, we want to listen to our favorite band online.

Our Italian vacation was postponed, but we still want to enjoy the wine and pizza while watching an online excursion around Venice.

When we can’t hang out with friends, we are looking for new fascinating things we can do together online. Something like an online game or a simultaneous cooking session?

The online entertainment is getting huge benefits from the coronavirus crisis. Basically, the industry got rid of all the competition overnight. No more hard choices like “Should I go out with friends tonight, or would I better watch another season of that hot show.” Everyone chooses the show now. And there is no clear evidence that the situation will change soon. Startup niches in the entertainment industry look especially attractive now.

Streaming services, games, and other types of online entertainment are booming. Will this remain the same after the lockdown when (or if?) the competition with offline events is back? Everything depends. At this time, new habits are born. If the new service manages to become a routine for a particular group of users – the exam is passed, it will still be popular after we are again allowed to enjoy our lives to the fullest.

How to hook your users?

Analyze the new gaps that appeared in everyday life.

One day we used to go to the cinema with friends, eat popcorn, whisper funny comments to a neighbor, and discuss the movie with all the group afterward. This option is definitely missed now. And Netflix has it covered with its new service Netflix Party. It enables you to share the watch the link to a movie or TV show with your friends, watch it simultaneously and exchange reactions, comments, or screenshots in real-time. More than 1,000,000 people already use Netflix Party, and the number will keep increasing during (and most likely after) the lockdown.

This is an example of how a simple solution has covered the needs of thousands of people.

It is much easier to enter the online entertainment industry now than it was a few months ago. This is a once in a lifetime opportunity, so don’t miss it.

What to expect from 2020 and beyond?

Unfortunately, many businesses won’t survive the coronavirus crisis. But a few of them will adjust to the new reality. We watch companies and individuals seeking ideas to make social distancing more comfortable and enjoyable for everyone. However, these innovators will succeed.

Sofiya Merenych

Business and Tech Writer

Sofiya Merenych is a business and tech writer at Clockwise Software, a web development company. Her area of interest includes startups, logistics innovations, ed-tech, travel-tech, marketplaces.

Read More

Posted on

New Niches for Startups Created by the COVID-19 Pandemic

Remote work and social distancing. These two approaches will define our lives behind 2020. The COVID-19 pandemic has put everyone into a new reality. The transition from our traditional lifestyle to isolation mode was anything but smooth. The whole world had to learn how to work and learn remotely and organize their leisure without leaving their homes. But the lockdown has also created a few niches for startups that no one could think of before.

A few months ago, we couldn’t imagine the world without public transport and traffic jams, busy restaurants and shopping malls, crowded parties and concerts. Now it is here. Governments shut down the long-awaited innovation programs to invest in healthcare technology – the industry that is getting the most attention nowadays. And for millions of people around the world, real-life has gone online – with evolving online shopping, online classes, and even online parties.

Despite restrictions easing in the vast majority of countries, no one can say when the lockdown will be completely over. Do we return to our normal lives this summer? Or the coming two years will be shaped by social distancing due to possible pandemic comeback?

One thing is already clear: we are in the worst economic downturn since the Great Depression. The unemployment rate has increased drastically. Many small businesses shut down; great economies enter the recession. This doesn’t sound optimistic, right?

But things are not that bad. The crisis opens many possibilities, as well. Here we discuss four industries that are experiencing a hard upgrade right now. If you want your company to be at the edge of improvements – hurry up and discover the potential startup niches!

Remote interaction – the new reality for private communication

For years, Zoom was a niche solution for online conferences and video calls. Since February 2020, it is the number one platform for all kinds of events: from birthday parties and blind dates to university classes and even city council meetings.

Currently, this is a forced measure, but experts predict that virtual meetings will become a substantial part of our reality even after the pandemic is over. Generation Z (also called Zoomers – what a coincidence!) prefer online communication to personal meetings. But the tools currently available still can’t provide the whole spectrum of features the young users are searching for. And this is one of the niches for a startup founder to investigate.

What do the myriad of online communication tools miss? User orientation, social features, and entertainment.

Zoom and the alike were built exclusively for business needs. Companies that couldn’t afford a custom internal communication system opted for a cost-effective SaaS solution. Their functionality fits the conference room, but not a virtual family lunch or a coffee-break. Zoom security issues are also a reason to look for alternatives.

Some of the tools start to play with enabling masks or changing backgrounds, but the complex solution for entertaining group calls is about to arrive.

There’s still the gap. And this is one of the potential startup niches to hit with a new app, right?

First of all, analyze the apps popular among Zoomers right now. What features make them so unique? Filters, instant reactions, microformats, geolocation, augmented reality or interactive 3D models, built-in mini-games, group film streaming, etc. – any idea could be the game-changer.

To the door delivery – eliminating the need for traditional shopping

E-commerce was developing gradually, but it seemed like the full transition to online shopping was still a few decades away. Some buyers were not ready to decide on the product without having seen it with their own eyes; some others didn’t trust the seller they can’t personally talk to.

And now we are here. The only type of shopping that is available during the lockdown is online shopping. And it turns out that basically everything can be delivered to the door: food, cosmetics, consumer electronics, furniture, gardening tools, and pet care products. Now that everyone was forced to try e-commerce, they could evaluate the convenience of the process and a chance to save much time. And after taking this first step, many won’t even return to classical shopping.

We already watch online commerce making a great leap ahead. And when speaking of global e-commerce trends, to-the-door delivery is definitely one of the strongest ones. So we expect a growing number of P2P logistics services. This seems like one of the solid startup niches, right?

The international companies of on-demand delivery like Uber Eats, DoorDash, Glovo focused on food delivery from restaurants first. Now they expand their services and are ready to bring anything to the door of their clients. However, high-quality delivery is still not available in the majority of smaller cities all around the globe. This means millions of people are waiting for a local company to satisfy their needs.

Until such a solution appears, local businesses hire carriers or cooperate with taxi companies to deliver their products while clients choose to stay home.

For many small businesses, the COVID-19 pandemic was an impulse to go beyond their physical shops and start selling online. E-commerce is booming, so do related services like delivery.

Education erasing the borders

If this crisis happened twenty or even ten years ago, millions of teachers and tutors, music and art instructors, fitness trainers would become unemployed in the blink of an eye. The lockdown would make their further work impossible as such.

However, the technologies we have in 2020 make education, art, and sport accessible to everyone at home. And what is even more important – online classes have no geographical limits. You can have an online session with a trainer from the gym on the opposite side of the street, or join the online training held by the Olympics champion.

Just as online shopping, e-learning was available for years. However, only a few of us have tried learning remotely. The reasons? Some complain about the lack of personal contact and instant feedback from the instructor; the others question their motivation and the ability to do their best while not being observed by a teacher.

But the lockdown happened, and thousands of people were at home without the possibility of visiting schools and universities, art classes, language courses, and sports sections. They have a lot of free time, and they are bored with four walls. However, they have the internet. So the time for online classes and training sessions comes. Many users have tried remote learning for the first time, and they are likely to keep the tradition after the quarantine is over.

Online education as one of the prospective startup niches.

What does this mean for the teachers, artists, fitness instructors, etc.? The geographical limits are down. Even living in a village, you can have hundreds of clients from any part of the country or even abroad.

Learning centers, language schools, fitness centers, and art clubs have the needed resources for a great leap. Adopt e-learning to expand to new markets.

There are many platforms for online classes on the market; none of them is perfect, though. Consider it as one of the possible startup niches. You can build a software tool to make remote classes even more effective, or provide a marketplace platform for individual tutors. This type of application will be of great importance in the next few years.

On the other hand, think of the perspectives of the academic year 2020-2021. The chances are that it may be interrupted by the new wave of coronavirus. And this time, schools and universities want to be ready for this. Now they are working on the programs of remote classes and experimenting with different technical solutions.

Some renowned universities can afford the development of custom learning platforms. The rest of the educational facilities is looking for a ready solution to fit the needs of both professors and students. If you have deep experience in this domain, developing a Software as a Service platform for universities and colleagues may be a chance you shouldn’t miss.

Entertainment has gone online

The COVID-19 lockdown has taken work and education to online. The same happened to the entertainment industry. Now when cinemas are closed, we want to watch movies online. When a so awaited music festival is canceled, we want to listen to our favorite band online.

Our Italian vacation was postponed, but we still want to enjoy the wine and pizza while watching an online excursion around Venice.

When we can’t hang out with friends, we are looking for new fascinating things we can do together online. Something like an online game or a simultaneous cooking session?

The online entertainment is getting huge benefits from the coronavirus crisis. Basically, the industry got rid of all the competition overnight. No more hard choices like “Should I go out with friends tonight, or would I better watch another season of that hot show.” Everyone chooses the show now. And there is no clear evidence that the situation will change soon. Startup niches in the entertainment industry look especially attractive now.

Streaming services, games, and other types of online entertainment are booming. Will this remain the same after the lockdown when (or if?) the competition with offline events is back? Everything depends. At this time, new habits are born. If the new service manages to become a routine for a particular group of users – the exam is passed, it will still be popular after we are again allowed to enjoy our lives to the fullest.

How to hook your users?

Analyze the new gaps that appeared in everyday life.

One day we used to go to the cinema with friends, eat popcorn, whisper funny comments to your neighbor, and discuss the movie with all the group afterward. This option is definitely missed now. And Netflix has it covered with its new service Netflix Party. It enables you to share the watch the link to a movie or TV show with your friends, watch it simultaneously and exchange reactions, comments, or screenshots in real-time. More than 1,000,000 people already use Netflix Party, and the number will keep increasing during (and most likely after) the lockdown.

This is an example of how a simple solution has covered the needs of thousands of people.

It is much easier to enter the online entertainment industry now than it was a few months ago. This is a once in a lifetime opportunity, so don’t miss it.

What to expect from 2020 and beyond?

Unfortunately, many businesses won’t survive the coronavirus crisis. But a few of them will adjust to the new reality. Those who are brave and wise will quickly innovate. We watch companies and individuals seeking ideas to make social distancing more comfortable and enjoyable for everyone.

These innovators will succeed.

Image Credit: Elly Fairytale; Pexels

Sofiya Merenych

Business and Tech Writer

Sofiya Merenych is a business and tech writer at Clockwise Software, a web development company. Her area of interest includes startups, logistics innovations, ed-tech, travel-tech, marketplaces.

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How Do You Create an Effective Journey Map for Your Customers?

Customers have a lot in mind when they land on a website to purchase a product or service. Some expect to find the product they have in mind instantly, while others conduct thorough research before they purchase a product. Well, that’s not all. Some end up being fickle-minded and land with no product at all. Here is how to create an effective journey map for your customers.

Landing in the “no product at all” category makes it all the more crucial for marketers to study different customer-mindsets in-depth and learn how to create your customer’s persona.

That’s why experts recommend studying situations from the customer’s point of view; to anticipate what will be their next course of action. Only then can a marketer get answers to the following questions:

  • What is the root intent when one is looking for a solution to a problem?
  • Why did the customer choose your competitor over you?
  • How did they feel for the first time after using a product?

It will allow you to create a message that instantly captures attention, and finally work upon creating a customer journey map. But besides answering these questions, you need to follow the steps below to create a journey map successfully.

Understanding Your Customers

Do you come up with a lot of questions when trying to understand your customers?

“What encourages my customers to buy the product?”

“Why do they hesitate about purchasing our product?”

“What concerns do customers have when thinking of purchasing the product?”

Well, these questions arise when you do not understand your customer’s personality as their journey begins with your brand.

But to know this, to answer your “how to create a customer journey map” question, you need to understand them in the first place. And once you know them well, mapping the customer journey also becomes simpler.

In this section, we’ll help you to understand your customers in four easy-to-follow steps. So, let’s deep dive now!

Step #1: Gather Key Data

Did you know that 68% of customers prefer version A to version B?

But you’d only know this if you understand who your customers are.

So, to understand customers, you need to gather crucial data about them. For this, use channels like:

  • Landing page performance data.
  • Customer support tickets received via help desk software.
  • Incoming customer support chats.
  • CRM data such as customer’s name, email address, products or services purchased so far, and so on.
  • Search history of the knowledge base repository.
  • Customer behavior data via an analytics tool.
  • Current social media activities.

Such data allows your business to answer the questions mentioned above and, from there, help you customize and create a customer journey map.

Step #2: Speak With Colleagues

Another way to know your customers is to communicate with your co-workers who are in customer-facing roles every day. Communication with coworkers can include your support, sales, and marketing team insights on customer behavior during a product purchasing journey.

While sometimes it may seem to be a vague attempt, experience tends to help organizations understand customers better. Those who face customer requests every day would know:

  • Your target audience better.
  • How many stages should the customer journey be divided into?
  • How customers might end up behaving during support, sales, or marketing process?

Step #3: Send Out Surveys

Capture qualitative and quantitative data via surveys to get a holistic idea of a customer’s mindset. For this, send out customer satisfaction surveys and even Net Promoter Score (NPS surveys — like qualaroom dot com) to see where your brand stands.

Plus, you learn whether the existing customers are satisfied with your services or not.

Basically, the more data you collect, the more clarity you get on customers. And thus, it becomes easy to build an audience persona. In addition to this, you get to create a seamless customer journey mapping process.

Step #4: Develop a Target Audience Persona

With all the data in hand, time to develop a target audience persona. You can create personas like:

It’s no guesswork; you can build viable personas with the quantitative and qualitative data you gather. Once you create these personas, it becomes simpler to reach out to your target audience with effective marketing campaigns that end up increasing sales.

Understanding What Customers Go Through

You’ve understood how to identify customers and what affects them when interacting with your brand. It’s time that you understand their pain points at a deeper level.

91% of customers who are unhappy with a brand will leave without complaining — this is important to note.

As a customer-oriented organization like yours, you wouldn’t like to see this happening with your customers. That’s why you need to work upon the next customer journey stage to understand what your customers go through.

Doing so will allow you to create excellent customer journey mapping examples for upcoming teams at work hassle-free.

Step #5: Consideration Phase

As you complete the process of creating a target audience persona, you should dive deeper to learn what all things do your customers consider before making a purchase.

Make a list out their concerns, such as:

These help you create counter solutions that help you answer – what is customer journey mapping and how to simplify it further.

Step #6: Purchase Phase

As you map out this phase, you see the steps your customers take to complete the product purchasing process. Here your organization can identify the problem areas and provide solutions to improve sales.

Questions you should look into can be inclusive of:

  • When did the customer lose interest in the product?
  • Should we cut-short the check out process?
  • Should we add a live chat to create upsell opportunities?
  • Should we trigger help when we see an exit-intent?

Step #7: Retention Phase

Finally, track your retention strategies and monitor how many customers you successfully retain with their help. You’d learn about things that put your customers off and why they deviate from the purchasing process. This would allow your team to further upgrade existing strategies and actually retain customers.

Track what strategies worked out fine and which ones ended up losing more customers, only to refine the existing marketing and retention strategies.

In the End

It is important not just to understand the customers but also to carve their journeys with your brand. However, learning about their thought process is crucial for your business. That’s why you need to follow the aforementioned steps to:

  • Understand your customers using:
    • Different mediums to capture crucial data on customers
    • Information collected through colleagues
    • Surveys like customer satisfaction or NPS
    • Target audience persona
  • Understand customer thought process:
    • When they consider reasons for investing in your product or service
    • When they find compelling reasons to purchase your product
    • When they find your efforts impressive and helps your brand to retain customers effectively

Once understood, it becomes easier to come up with strategies that shape their journey with your brand. We hope these easy to follow steps help you create a customer journey map hassle-free.

Vineet Gupta

Digital Marketing Team Lead

Vineet is a software engineer by qualification and an online marketer by profession. He likes studying Google search algorithms and helps businesses by improving their online presence.

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Digital twin technology on turbulent climb to stratosphere

Digital twin technology sounds inherently cool and edgy, and it is cool, in many ways.

As a computer representation of a real thing, a digital twin can be the broker to all sorts of cutting-edge applications, such as wind power sold by the hour, remotely managed automated factories and predictive maintenance tools with augmented reality.

Digital twins are everywhere, it seems — if “everywhere” means the websites and shiny brochures of brand-name manufacturers and IT vendors. But the technology is not just a figment of the IT industry’s imagination. In a survey last year, Gartner said digital twins are proliferating and slowly entering the mainstream, and predicted that two-thirds of companies that adopt IoT will have at least one digital twin by 2022.

Digital twin technology is also showing up in real implementations by farm equipment and medical device manufacturers and aerospace companies, among others.

Take Aerion Supersonic, a jet manufacturer based in Reno, Nev. Last year, it began working on a digital twin architecture for the AS2, which it claims will be the first commercial jet capable of flying at supersonic speeds that can exceed 1,000 miles per hour and cut the Los Angeles to New York trip to three hours and 17 minutes — without generating ground noise.

Bissell Smith

Bissell Smith, Aerion’s CIO and executive vice president of enterprise systems, said digital twins will be needed throughout the AS2’s lifecycle and are worth the significant effort they take to develop and maintain. They drive virtual simulation and operational and fleet management efficiency. Without digital twin technology, for example, problems with an airplane’s design may require grounding the entire fleet. Digital twins of each aircraft will make it possible to isolate issues to a single plane’s unique configuration.

“The better you’ve [digitized a jet’s] ‘secret sauce’ … the more you’ll be able to keep aircraft flying versus on the ground waiting,” he said.

Digital twin technology: Early days

The aerospace industry is not the only sector banking on digital twin technology to confer a competitive edge. Prominent users — and vendors — of digital twins include major names in industrial automation like GE and Rockwell Automation. In the enterprise software world, makers of product lifecycle management (PLM) software lead the way, including Oracle, SAP and Siemens. Digital twins also come from makers of computer-aided design (CAD) and 3D modeling and simulation software, such as Autodesk, Bentley Systems, Dassault Systemes and PTC. Public cloud vendors Amazon Web Services and Microsoft Azure IoT also have offerings. In addition, many users develop their own digital twins (see the infographic, “Sources of digital twins”).

Sources of digital twins

Still, companies interested in using digital twin technology will quickly realize that it presents significant challenges. For starters, its implementation is intertwined with another relatively new technology — IoT.

Shawn DeVries

“There is a very close symbiotic relationship between the two,” said Shawn DeVries, managing director at Kin + Carta, a consulting firm. “The value of the digital twin platform is only as strong as the ability to read the data as near to real time as possible.” IoT sensors are often that data source. Conversely, digital twins are a useful mechanism for organizing and communicating IoT data so it can be analyzed and monetized in applications.

Driving value from digital twin technology and IoT, however, requires mature data management processes and sophisticated systems integration, making digital twin development a complex, multi-year effort — and therefore another challenge companies must reckon with.

Benoit Lheureux

So, while existing applications for digital twin technology range widely, from oil and gas companies optimizing oilfield production and electric utilities monitoring their equipment to hospitals keeping tabs on patients after surgery, deployments are limited, according to Benoit Lheureux, a research vice president at Gartner.

“People are still in proofs of concept and experimenting with the technology,” he said.

Richard Howells

But Richard Howells, vice president of solution management for SAP digital supply chain, said “the reality is that most people have a digital twin of some sort of their products or their facility or their process. They just don’t call it that.”

“Once you have technology in place that’s an integrated, end-to-end process — from how you design products all the way through to how they operate in a live environment — you start capturing more and more data, digitizing the processes and capturing more information about the assets that you use.”

What is a digital twin, really?

The consensus base definition of a digital twin is that it’s a digital representation of a thing, process or person.

“It becomes a proxy for the state of the thing,” Lheureux said. Digital twins date to the late 1960s when NASA used telemetry and “automated interfaces” to monitor Apollo spacecraft, he said.

Some confusion over the definition might be due to the 3D color images and 2D CAD drawings that some digital twin providers use to market their products. Visualizations that aren’t well integrated with data sources and can’t be queried about the state of the entity they represent aren’t really twins. Simulations also aren’t automatically digital twins for the same reasons, and they require complex algorithms and huge amounts of data to mimic behavior, something most digital twins don’t need.

To Lheureux, what differentiates a digital twin from digital representations that appear similar is that people can query a digital twin to learn something about the thing it represents. “A digital twin is enterprise software that ingests IoT data to produce a finding, to increase situational awareness,” he said.

DeVries said the concept has evolved from his days working in CAD 25-30 years ago when it meant a detailed digital model that could be used in the manufacturing process. What’s changed is the advent of cheap networked sensors that allow digital models to be smarter. “You can see not just what it’s doing now, but what it’s done over time for trend analysis and predictive analysis,” he said.

Above, a GE digital twin of a gas turbine. The labels refer to sensor data that is used to create a model of a component, such as a compressor. The smaller twins combine to create a model of the turbine, which in turn can be part of the digital twin of an entire power plant (below). AI can help optimize factors such as fuel levels and maintenance schedules that affect how much money the plant can make from trading electricity on the market.

Digital twin use cases in business

The most common types of digital twins deployed are for expensive equipment that is tunable, customizable and critical to a company’s business, DeVries said.

“There seems to be almost a tipping point where the more critical the asset, the greater the chance of having some sort of digital twin associated with it,” he said. “If you’re putting that kind of investment in a piece of equipment, you expect to have some level of visibility to how well that equipment is performing,” he said.

Examples of this phenomenon are the agricultural equipment makers Agco, Caterpillar and John Deere.

Farming equipment has had telemetry for decades, DeVries said. “It’s very similar to what you see in a Tesla these days. You don’t really associate tractors or combines with that type of technology integration, but it very much is the case.”

Besides heavy equipment, the other primary market for digital twins is process automation, DeVries said. ABB is a major player, along with Rockwell Automation, which has a partnership with PTC.

“They have replications of those processes running within their support centers that can basically talk to a maintenance engineer or a plant supervisor,” he said. “Those types of support touchpoints with their customers become a much richer, engaging experience, and they can get to the problem a lot quicker.”

Digital markets for digital twins are springing up, such as the Digital Twin Exchange that IBM opened in May. SAP already had a cloud-based repository for digital twins and other equipment information called the Asset Intelligence Network.

Joe Berti

“The easiest way to describe it is as an iTunes for asset information,” said Joe Berti, IBM’s vice president of offering management for AI applications. Customers include an IBM partner who uploaded digital twins for 20 kinds of bridges along with maintenance information and predictive models. A Porsche Boxster’s digital twin contains a bill of materials (BOM), parts list, error codes and metrics such as mean time between failures. IBM splits the revenue with the content producer, which continues to own the intellectual property.

Berti likened the exchange’s digital twins to resume templates for job applicants.

“It depends on the provider of the digital twin, how much information they provide,” he said. “Most manufacturers aren’t going to give away the CAD model for their products. They don’t want people copying their designs. But they’re willing to go with a parts list and the bill of materials. They do that already in their maintenance manuals.”

Companies that own heavy equipment will pay the exchange $1,000 – $5,000 for an operational digital twin, Berti said, because it saves time.

Assembling a digital twin architecture

For large, complicated equipment that is hugely expensive to maintain, has life-or-death safety implications and a useful life measured in half centuries, digital twin technology is both essential and incredibly difficult to pull off. Few industries exemplify that more than aerospace and defense. 

Capturing all the information for the digital twin of each jet Aerion Supersonic plans to start manufacturing in 2023 is “no small matter,” Smith said. He detailed the enterprise architecture the company is building, and what’s involved in pulling data from it.

Aerion digital twins start life with the engineering designs in Siemens NX CAD or a partner’s CAD tool. The company also has Siemens PLM software and will soon pick an ERP platform that includes material requirements planning (MRP), the system for calculating and scheduling raw materials and parts. The ERP will run both manufacturing and the supply chain and generate the data the digital twin needs from those processes, including quality control information, rework issues and engineering changes. The ERP will be integrated with a manufacturing execution system (MES) and data lake architectures and analytics set up.

An engineering BOM and a manufacturing BOM will be the main integration mechanisms between PLM and ERP. The BOM information also feeds into MRP, which Aerion will use to buy or make parts.

“All of that’s been captured in what’s called the digital thread that goes into, ultimately, the digital twin,” Smith said. “You have the digital thread all the way up to delivery. That digital thread will be shared with all of our major partners — they’ll be helping to create it. When we get to the digital twin, that will only be between us and the customer.”

Smith said the best way to capture the information is through the transactions handled in the different applications. “Every time an engineering update is made and put in the PLM, PLM is capturing that data. But that’s being done by the hundreds of designers that are working on our aircraft. Every time we [buy parts], we’re going to be releasing that to our supply chain and that supply chain is going to be referencing drawings, and that’s all part of the digital thread.”

People on the manufacturing side do the same as they build their production plans and “redline” the engineering plans for production issues in Siemens Active Workspace. Then mechanical and industrial engineers analyze the drawings and make suggestions, all of which also get captured in PLM.

All that data will be captured in the ERP system and the MES system tied to it. Our logistics system will be capturing more. And you have to thread all this together.
Bissell SmithCIO, Aerion Supersonic

If, during manufacturing, a deviation from the plan becomes necessary, any changes in the design will also have to be captured. “All that data will be captured in the ERP system and the MES system tied to it,” Smith said. “Our logistics system will be capturing more. And you have to thread all this together.”

“Then it’s up to us — Aerion — to decide, when we’re working on the commercial [aviation] side, what do we want that digital twin to represent?” He said the aerospace industry is “nebulous” about its expectations for digital twin technology and much clearer about how to use it in engineering than in operations. The Air Force, which made digital twins a requirement of its contract, will decide what it wants.

“If they buy aircraft from us, they’re going to expect that infrastructure,” Smith said. 

Then there is the information needed for certification, such as results of virtual tests of aircraft models for factors such as noise, weight and drag.

“Everywhere we’ve got any kind of simulated testing out on the system, we’re going to try to capture all that through the Siemens architecture,” Smith said.

The digital twin becomes each aircraft’s unique signature. “We try and get as close as possible, but there are always errors that enter the process — a mechanic drilled a hole too large that has to be filled. There’s a deviation waiver that goes with that, and approval,” he said.

Challenges of digital twin technology

Digital twin users face the same hurdles as Aerion, if not always on so massive a scale.

“Deploying those sensors, the communications, designing the algorithms, implementing the cloud platform, integrating the digital twins with a back-end system to automate your response — that is a lot of technology. It’s not trivial,” Lheureux said. What’s more, the job takes a range of skills in integration, security, analytics and application development. Much of the technology is unproven, so people lack confidence in it.

Industry standards from entities like the Industrial Internet Consortium could help, Lheureux said, but most manufacturers have many brands in their shops, and much of the value comes from standalone digital twins.

The “blue-sky” vision is for interoperability to occur between the hierarchical levels of all the digital twins a company has — say, between the digital twin for a piece of equipment — what Gartner calls a discrete digital twin — and the digital twin for the whole factory, a type Gartner labels as composite.  That data can then feed into the highest-level category, an organizational digital twin.

“We will get there,” Lheureux said.

For now, interoperability comes from APIs, which most digital twins have. A composite twin can use an API to get data from a discrete twin. The challenge comes in normalizing the data to ensure it meets the needs of the receiving twin. One composite digital twin of a manufacturing process might reside in the AWS public cloud, while the discrete digital twins for equipment run on Microsoft Azure IoT.

“That sounds like a mess, right? And it is a mess,” Lheureux said.

Sometimes the data will be available in a discrete digital twin and the user will call APIs to access it, he said, but sometimes it won’t be. “You’ll go after other sensors, you’ll put out new sensors, you’ll collect data from different sources. You’ll do whatever it takes to get whatever data is needed to achieve a particular outcome,” he said.

Anybody who will be successful at deploying digital twins at scale must be a master of integration.
Benoit LheureuxResearch vice president, Gartner

The usual solution is for owner-operators of digital twins like GE to only develop them for a handful of the most troublesome pieces of equipment. “To create the composite, you’re going to be pulling data from many sources anyway,” he said. “Anybody who will be successful at deploying digital twins at scale must be a master of integration.”

Berti said an industry standard for equipment information is needed. Certain pieces are already covered by bodies such as the ISO. “As people see the need to electronically import information and exchange it, standards typically follow, but they typically follow over the next three to five years,” he said.

The IT infrastructure needs of the digital twins themselves are minimal, according to Berti, because most of the data is already being stored and managed in enterprise systems such as CAD and ERP as part of maintenance management.

Getting the right type and amount of data requires the equipment manufacturer to foster a close partnership between its business side, which understands customer use cases, and the engineering side, which knows the hardware integration issues, DeVries said.

“There’s almost always a business or executive sponsor who understands, and gets out there in the field and interviews the growers and other people who work with this equipment, whether it be a mining operation, construction, etc., and tries to declutter a lot of those interfaces to make sure they’re getting the right information at the right time,” he said.

But the challenges aren’t primarily technical, DeVries said. “It’s a cultural and educational shift in the frontline workers, the maintenance engineers and plant supervisors. Like anything else, they need to see the benefits of a solution to support that more advanced digital mindset.”

Do you even need digital twins?

Digital twin technology sounds a lot like the data management and analytics that have long been required to make IoT sensors practical. So why bother with a digital twin?

“A lot of people do think that a lot of this is just really event-driven analytics, and I don’t disagree with that,” Lheureux said, noting it’s similar to the event stream processing that has been around for decades.

Nevertheless, digital twins will still be important in realizing the automation potential of IoT. “Everything we do in business is event-driven,” he said. When a product breaks, the consumer contacts a call center to request a spare part. If a production-line robot breaks down, a service technician notes the problem and logs it in a help desk system.

“Right now, we respond to those events at the ‘last mile‘ of integration with humans,” Lheureux said. “That last-mile gap between things in the world and our IT systems is what we’re closing when we implement IoT and digital twins.”

He said managers who are responsible for their organization’s enterprise applications must prepare for a fundamental shift from applications in which workflows are controlled by humans managing business transactions to ones where IoT-connected things call more of the shots. “It’s going to be a thing that’s sending data to a digital twin and the digital twin will execute some new workflow that will trigger the backend systems.”

“It’s generational. It’ll be bit by bit, but it’ll be a fundamental shift by death by a thousand cuts for the enterprise application leader.”

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How an IoT botnet attacks with DDoS and infects devices

To counter the growing threat of IoT botnets, IT administrators must understand how hackers create a botnet and initiate a distributed denial-of-service attack.

The rapidly expanding number of IoT devices further presents bad actors with a vast collection of endpoints that they can co-opt into a huge bot army to do their bidding. Already, hackers have used IoT botnet to launch destructive DDoS attacks. For example, hackers used the Mirai virus to infect some 600,000 IoT devices and then launch a DDoS attack that took down the internet in much of the Eastern United States in 2016. At the time, there were billions fewer IoT devices. The number of connected devices has shot up from 17.68 billion in 2016 to an estimated 30.73 billion in 2020, according to Statista Research report titled “Internet of Things (IoT) active device connections installed base worldwide from 2015 to 2025.” It’s expected to reach more than 75 billion in 2025. The potential potency of attacks wielding IoT botnets appears to be increasing alongside the number of devices.

Researchers at Bitdefender announced in April 2020 that they identified a new IoT botnet, which they named dark_nexus and said had capabilities that go beyond other known botnets. Researchers also said the dark_nexus botnet appears to have been developed by a known botnet author suspected of selling DDoS services in the past.

How hackers infect IoT devices to create botnets

The development of a botnet generally follows a prescribed strategy. It starts with a bad actor, a single individual or a collective of hackers working together for a criminal syndicate or a nation-state, who creates code that’s programmed to infect devices. This malware can sit on any type of device that can execute code, but hackers can also create it to specifically target IoT devices.

The bad actor can use different tactics to get the malware onto devices. Phishing scams are common strategies, but the malware can also be designed to look for unprotected network ports on IoT devices or other similar specific vulnerabilities. Once designed, the hacker uses the code to infect as many devices as possible, making this collection of hijacked devices into a botnet.

Christopher McElroy

“The machines aren’t bad, it’s just the code running on them,” said Christopher McElroy, a senior consultant at management consulting firm Swingtide.

Despite the headline-making reports of malicious IoT botnet attacks, many organizations use similar technology — such as distributed computing systems — to handle certain business functions, he said. A retailer, for example, may use the technology to monitor for the lowest offered price on a given item, or an IT department might deploy the technology to monitor equipment performance. However, problematic botnets have been infected with malicious code running on the device so that the hacker can take control of the devices to launch criminal activities, such as a DDoS attack.

Orchestrators use malware code for IoT botnet DDoS attacks

Bad actors can find modularized malicious code on the internet, much of it freely available. The modules are designed for certain task, said Gregory Touhill, an adjunct faculty member at Carnegie Mellon University’s Heinz College of Information Systems and Public Policy and a retired U.S. Air Force brigadier general formerly the first federal CISO in the U.S. For example, there’s modularized code designed to detect susceptible machines, including IoT devices and industrial controls. There is also a module to camouflage the code so that it can infect its targets without being detected and one that allows communication back to home base.

Gregory Touhill

“When [the malware] gets onto the device, depending on how the code is written, at some point it will phone home like E.T. It calls command and control and tells command where it is. The message goes to command-and-control servers — most botnets have lots of those — and they’re often compromised devices themselves,” Touhill said.

Most botnet code tries to reach a primary command-and-control node. If it can’t reach that node, the code tries to reach a secondary node or a tertiary one. Once it connects, it stops. It doesn’t maintain constant contact.

Orchestrators, as bad actors using botnets to launch attacks are called, also use a module to deliver the payload — the code that can be used to launch an actual attack. Once installed on the device, the code sends information back to the home system, saying ‘I’m here, here’s the information.’ That information is collected on a master database.

“[The hacker] is doing the same thing to 1,000 or one million or however many devices,” McElroy said. “Then the code just sits there and waits for instructions from the master server; it just waits for the orchestrator to send out instructions.”

IoT botnets can put out spam or other kinds of misinformation, but they’re most frequently used to launch DDoS attacks in which the orchestrator commands the botnets to flood targets with traffic to bring down their systems.

Orchestrators can plan and execute attacks for their own reasons and for their own gain, or they can actually sell the use of their botnet inventory to others, taking instructions from their “clients” to distribute instructions for the types of attacks they want, McElroy said. The orchestrator stores the command on a server. When the bots get the command to set up, then they start.

IoT botnets can put out spam or other kinds of misinformation, but they’re most frequently used to launch DDoS attacks in which the orchestrator commands the botnets to flood targets with traffic to bring down their systems, according to experts.

“The vast majority of botnets lie in wait as the ‘infection’ spreads and then the bad actors decide to launch or execute the attack, and then the bots all go into attack mode and broadcast like crazy,” Touhill said.

Of course, organizations deploy layers of cybersecurity defenses to block malware from getting into devices, but, as experts pointed out, those layers aren’t always successful in preventing attacks.

Once a botnet is active, orchestrators demand payments to get the botnet activity to stop — with financial gain being the most frequent motivation for attacks.

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Overcome 5 IoT device management challenges

As IoT devices proliferate every area of business, organizations need to ensure they’re managing them and the network supporting them correctly.

Organizations rely more on IoT devices to make good decisions, out-think the competition, reduce costs and increase efficiency across the organization. Although IoT networks are quickly becoming more widespread, there are still significant challenges to managing an IoT network. Whether it’s connectivity or data obstacles, scalability or security, today’s enterprises struggle to manage it all. As IoT devices become more embedded in organizations, it’s incumbent on all stakeholders to learn more about them and participate in the process of IoT management. To succeed, IoT leaders must plan to tackle the top five challenges of managing IoT.

1. Data management

IoT networks generate unprecedented volumes of data that are increasingly critical to the regular business operations. Managing the mountains of data they produce poses a challenge, so data management must be top of mind. 

Organizations must ensure collection of only the data the team wants to log and analyze. Extra information will make it harder to draw meaningful insights. 

It’s essential for IoT experts to find the right combination of software that will track and analyze the collected data effectively and the storage option that can handle it all. Many organizations are turning to cloud offerings for their IoT data, but some still rely on on-premises products. All technology must be integrated if organizations hope to have easy access to the data and the insights it can provide. 

The neglected side of IoT data management is the bandwidth the data uses as it travels the network from device to storage to processor and back again. For IoT devices connected through cellular networks, providers offer data plans with different uptime and bandwidth service levels. Even momentary downtime could be critical for an organization handling sensitive data. 

2. Power management

Power usage is another IoT device management factor of which many enterprises are not aware. IoT devices either use regular electrical power in hard-to-reach locations or battery power in remote areas. While most technology is advancing rapidly, battery life still lags. Organizations continuously monitor remote IoT device batteries and schedule regular maintenance, recharging or replacement. Finding ways to conserve device power when not in use can help IT teams manage a fleet of remote devices. 

3. Device monitoring

With so many IoT devices on the market, IT administrators can get overwhelmed trying to manage them all. Each new sensor, beacon or controller must be installed, configured, monitored, diagnosed, updated and maintained regularly.

Each new sensor, beacon or controller must be installed, configured, monitored, diagnosed, updated and maintained regularly.

IT administrators can manage newer devices easily through online portals or IoT device management software. Earlier devices may require extra work, and IT teams must often implement additional measures to monitor and manage them, such as adding a subnet to help boost legacy device performance. 

Compounding these challenges are the devices placed in remote locations away from the enterprise’s main facilities. Deploying IoT devices capable of remote monitoring, updates and diagnostics will make it easier for the IT team responsible for them. 

4. Device connectivity

Network traffic and internet connectivity increases with each new IoT device, so the network must scale to accommodate them. Some devices use wired connections, but most rely on wireless technology. The most up-to-date Wi-Fi technology can ensure high uptime and scalability. Some organizations may turn to cellular networks to connect devices in populated or urban areas. Remote devices that rely on cellular connections may lead to an increase in the regular fees wireless providers charge and any overages the devices incur. 

5. Cybersecurity

Each IoT device is a potential entry point for bad actors to target an enterprise’s network. Provisioning and authentication can help prevent unauthorized users or devices from connecting to the organization’s devices or network. Provisioning enrolls the new IoT device to the network, while authentication verifies that it is authorized to access the network through secure credentials. 

IT administrators must plan IoT device updates because IoT technology changes rapidly. Vendors can release updates and fixes to the firmware, software or device controllers at any time, so IT admins will need to plan for them. Physically connected devices can update safely if they’re within the enterprise network. Remote device updates may require extra planning to avoid crossing into any high-peak work periods or a device’s power-saving off time. 

IT admins should also put safeguards in place to protect data transmitted over IoT networks. Hackers can intercept transmissions between devices and the network, especially remote devices. Organizations should only use secure, password-protected wireless networks. 

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Internet of Everything vs Internet of Things: What’s the Difference?

Illustration: © IoT For All

Unless you’re an expert, there’s little difference between the Internet of Things (IoT) and the Internet of Everything (IoE). However, the latter term is broader, semantically. In this post, we’ll go into the details to explain why IoT software development companies use the term IoE comparatively rarely.

The Difference

The term IoT was coined in 1999 to refer to machine-to-machine, or M2M, communication. IoE appeared a few years later, to describe interrelated elements of a whole system, including people. IoE entails not only M2M communication but also P2M (people-to-machine) and even P2P (people-to-people) communication.

To understand the differences between the three types of communication, let’s consider several examples. Say it got dark outside and you turned on a light in the office, then you sat and typed on a keyboard. This scenario provides P2M examples of IoE.

We are so used to these things that we don’t even realize they are part of a system. Another example: You make a Skype call to your colleague. That’s a simple human-to-human, or P2P, communication. An example of M2M communication, on the other hand, is the process of data exchange between your office temperature sensing devices and the HVAC mainframe.

You might think M2M communication, being technological, is the most progressive means of interaction. but IoE focuses on P2M and P2P interactions as the most valuable. According to a Cisco analysis, as of 2022, 55% of connections will be of these two types. 

IoE is now considered the next stage of IoT development. Maybe this is why there are so few IoT development companies offering IoE development services at the moment. Internet of Things solutions are now more common and widespread.

4 Main Elements of the IoE Concept

 Thing

By thing, we mean an element of the system that participates in communication. A thing is an object capable of gathering information and sharing it with other elements of the system. The number of such connected devices, according to Cisco, will exceed 50 billion by 2020. 

What are things? In the IoT, a thing could be any object, from a smart gadget to a building rig. In the IoE, that expands to include, say, a nurse, as well as an MRI machine and a “smart” eyedropper. Any element that has a built-in sensing system and is connected on a network can be a part of the IoE.

People

People play a central role in the IoE concept, as without them there would be no linking bridge, no intelligent connection. It is people who connect the Internet of Things, analyze the received data and make data-driven decisions based on the statistics. People are at the center of M2M, P2M, P2P communications. People can also become connected themselves, for example, nurses working together in a healthcare center.

Data

In 2020, it’s projected that everyone using the internet will be receiving up to 1.7 MB of data per second.

As the amount of data available to us grows, management of all that information becomes more complicated. But it’s a crucial task because, without proper analysis, data is useless. Data is a constituent of both IoT and IoE. But it turns into beneficial insights only in the Internet of Everything. Otherwise, it’s just filling up memory storage.

Process

Process is the component innate to IoE. This is how all the other elements — people, things, data — work together to provide a smart, viable system. When all the elements are properly interconnected, each element receives the needed data and transfers it on to the next receiver. The magic takes place through wired or wireless connections.

Another way to explain this is that IoT describes a network and things, while IoE describes a network, things, and also people, data, and process.

Where Is IoE Applied?

As to the market, we can say confidently that IoT is a technology of any industry. IoE technology is especially relevant to some of the most important fields, including (1) manufacturing, (2) retail, (3) information, (4) finance & insurance, (5) healthcare. 

IoE technology has virtually unlimited possibilities. Here’s one example: More than 800 bicyclists die in traffic crashes around the world annually. What if there was a way to connect bike helmets with traffic lights, ambulances, and the hospital ecosystem in a single IoE. Would that increase the chances of survival for at least some of those cyclists? 

Another example: Do you realize how much food goes to waste, say at large supermarkets, because food isn’t purchased by its best-before date? Some perishable products like fruit and vegetables are thrown away due to overstocks even before they get to the market. What happens if you find a way to connect your food stocks with the racks and forklifts of the supermarket in-stock control system using IoE?

There are endless variations on uses of IoE right now, and many of them are already becoming familiar in our “smart” homes.

Summing up

In our industry, few would deny the value of IoE in improving our standard of living. Luckily, there’s a flourishing market of IoT development services. Who knows, maybe one day soon, you’ll be a “thing” in the IoE environment.

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Data Communications and Flow: Focus on What You Need

Illustration: © IoT For All

When visualizing a new IoT application; carefully consider not what data flows you want, but what data flows your application needs to be successful.

Data flows are one of the key constraints in the design of any IoT application. Data flows drive not just communications cost, but also indirectly control communication technology selection, power needs, and the actual paradigm of an application’s functionality. As you begin visualizing your new IoT application, think carefully about the data and communication patterns that support your planned features.

IoT is a confluence of smart and connected in a remote device. I assume that if you’re reading this you have a “device” side and a “user” application side that you are thinking about connecting.  Your devices could be in near proximity of your user, their home/office, or anywhere. The user application where the device data lands initially could be a smartphone, or in many cases a cloud platform. Throughout the discussion, chances are the connection will be over a wireless link. This is by far the predominant pattern for typical IoT (non-IIOT/non-manufacturing use cases).

First, let’s differentiate between “data” and “data flows.

Data: what is measured

Data Flows: what is communicated.

Sure, increased data is likely to ramp up the amount of data sent to/from your device, but more data is not a linear predictor of how much data an application needs to communicate with a user. As the power of IoT device MCU chips increases, there is a steady ability to do more processing on the device and only communicate a summary of relevant events and periodic data points.

Communications are power-hungry compared with computation and memory on an IoT device. The more you can keep your radio turned off, the more battery life that remains. There are power light wireless technologies like Bluetooth Low Energy (BLE) for near distance communications, but what if your device is far away? Radios vary in their performance profile and there are numerous articles out there about WiFi vs. LoRa vs. LTE. Know your communications stack. Next, I lay out some concepts that should be considered regardless of which type of radio is in your device.

Most IoT projects fall into two broad categories. These two patterns dictate many aspects of the data flows your application will need to perform and when your communications hardware needs to be turned on.

Interactive

Interactive applications place the user and device in virtual proximity, with physical distance ranging from a few feet to miles to wherever. The communication flows, bridge that physical distance. This application pattern is the most demanding from a communications perspective.

Communications that are interactive require that a device radio stays on to listen for user input. This could be constrained to a specific interval of interest, rather than 24 hours a day. Maybe the communications channel can be predictably enabled during “business hours” or only during predicted device “usage” times.  The key point, radio on all the time increases power consumption considerably. This in turn increases challenges for off-grid or solar applications to have enough power harvesting and storage.

Being that the interactive application pattern is so demanding that you may find variations necessary to make things work. Consider maybe delaying user input by minutes or even hours, opening times for user control of the device.

Remote Monitoring

From a communication and power budget perspective, this application pattern is much easier to implement. Devices can wake up occasionally, gather and locally store data, assess the situation, and then decide if communication is required. The radio stays off until it is needed to send data to the user before it’s back to sleep for the communications.

The remote monitoring pattern can be integrated with an interactive application by making use of when the radio is already turned on. When you periodically send data, check for user directives. This approach is standardized in LoRaWAN Class A devices which listens for user input 1 and 2 seconds after transmitting its data.

IoT applications typically use protocols such as MQTT or HTTP to package their data while in transit. MQTT, HTTP, AMQP and other IoT communication protocols add protocol data to the total amount of IoT device payload data being transmitted between the device and the user. The amount of data communicated typically increases in two ways: framing overhead and keepalives.

Framing overhead is the extra data that is sent along with an application’s data to make communications more robust and reliable. Think of protocol framing as the envelope you put your physical correspondence in. In the case of MQTT, to send data, the overhead is 6 characters + the MQTT topic name your device is publishing to. This can add up and, in some cases, exceed the size of the payload data you are sending to the user side. It is important to note that while MQTT transmits these extra characters with your message payload, MQTT is more efficient than AMQP and HTTP; which is why MQTT is so often used in IoT systems.

The other protocol tax is keepalive messaging (sometimes referred to as heartbeats). MQTT implementations typically perform a keepalive action every 1-4 minutes, this time period is referred to as the keepalive interval. Keepalives are not required if data transmission has been performed recently. To keep communications active, MQTT sends a 2-character long PING when the keepalive interval ends. The keepalive interval is reset with each transmission, for either a PING or payload data.

Most implementations afford the ability to lengthen the keepalive interval (reduce the number of keepalives sent), each system will typically impart some upper limit for the keepalive interval. Azure IoT Hub uses MQTT extensively and limits the keepalive interval to a maximum of 1177 seconds or once every 19 minutes, 37 seconds (Understand Azure IoT Hub MQTT  Support).

When reviewing data and deciding what to send back and forth, think about ways to eliminate or reduce application data flows. When reviewing data flows, take note of how big each one is, how often data is sent, and what is going on with your communications channel when nothing is happening.

There are tools online (IoT Bandwidth Estimation Tool) to help visualize your data budget and be proactive in planning your data communications.

Time adds up… fast! Sending 500 characters of data every 20 seconds:

180 times / hour                           90KB / hour

4,320 times / day                          2,160MB / day

30,240 times / week                   17,120MB / week

129,600 times / month              64,800MB / month

Remember every character you send can increase costs and draws down your device’s battery.

Some Ideas…

  • After sampling remote data, look for ways to summarize prior to sending. For example: consider sending maximum, minimum, average, and number of data points over a specific period.
  • Similarly, once a maximum and minimum are established, consider sending data only when a new outlying maximum or minimum has been observed.
  • For remote sensing consider only sending data once a day or even once a week. But send data events when something significant has been observed at the device.
  • Consider building normal limits in your device software. When the data being sensed leaves these limits, then communicate and report the event to the user.
  • Log your data locally on the device and send a block of data (a day or weeks’ worth) at one time. Once the radio is on using it, then shut it off. Every time the radio is turned on/off, power is wasted before/after when data is sent.

Only you can determine when a piece of data being sent is valuable. Is that piece of data something you want… or is it something you need?

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Shielding Frontline Health Workers with AI

Illustration: © IoT For All

We are living through an unprecedented crisis. During the COVID-19 pandemic, healthcare workers have emerged as frontline heroes, working overtime to protect our communities from the spread of novel coronavirus. But they aren’t immune to the anxious, uncertain atmosphere the pandemic has fostered nor, indeed, the coronavirus itself.

We need to protect the first responders and hospital staff who put their wellbeing on the line to support their communities during a crisis. To my mind, that means using every tool at our disposal to the fullest — with AI chief among those at hand.

Creative Solution

There’s little doubt that the current situation demands a creative solution. The United States has become the center of the global pandemic; as of April 16th, the US confirmed 644,188 cases and endured 28,579 deaths. Despite efforts to flatten the curve by ordering regional shut-downs and stay-at-home orders, hospitals across the county have been all but overwhelmed by incoming cases. The impact on provider morale has, according to reporting from NPR, been similarly problematic.

“Nearly a month into the declared pandemic, some health care workers say they’re exhausted and burning out from the stress of treating a stream of critically ill patients in an increasingly overstretched health care system,” NPR reporters Will Stone and Leila Fadel recently wrote. “Many are questioning how long they can risk their own health […] In many hospitals, the pandemic has transformed emergency rooms and upended protocols and precautions that workers previously took for granted.”

Hospitals are doing all they can to keep their caregivers safe and protected, but their resources are stretched far too thin. According to reports, some hospitals in high-infection areas like New York City can only afford to give healthcare workers one N95 mask every five days. Used masks are collected, disinfected, and returned on a cycle between uses. But some frontline workers worry that, given the highly contagious nature of the disease, they may not be adequately protected.

“It can be disheartening to have that feeling of uncertainty that you are not going to be protected,” Sophia Rago, an ER nurse based in St. Louis, told reporters for NPR.

We need to shield our frontline workers as much as possible. The obvious solution would be to increase stores of personal protective equipment (PPE) and N95 masks; however, given that we face a national shortfall and harsh state-to-state bidding wars over the gear, that fix seems unlikely. What we can do to at least lessen the risk of patient-to-provider transmission is to invest in AI-powered solutions that can automate some healthcare protocols and limit the need for close contact.

“Traditional processes — those that rely on people to function in the critical path of signal processing — are constrained by the rate at which we can train, organize, and deploy human labor. Moreover, traditional processes deliver decreasing returns as they scale,” a team of digital health researchers recently wrote in an article for the Harvard Business Review.

“Digital systems can be scaled up without such constraints, at virtually infinite rates. The only theoretical bottlenecks are computing power and storage capacity — and we have plenty of both. Digital systems can keep pace with exponential growth.”

These AI-powered, digitally-facilitated solutions generally fall into two broad categories: disease containment and patient management.

Assessing AI’s Ability to Limit Disease Transmission

When it comes to limiting disease spread, the aim is to use AI tools to allocate human resources better while still protecting patients and staff. Take the screening system that was recently deployed at Tampa General Hospital in Florida, for example. This AI framework was designed by the autonomous care startup Care.ai and intended to facilitate early identification and interception of infected people before they come into contact with others. According to a report from the Wall Street Journal, the Care.ai tool taps into entryway cameras and conducts a facial thermal scan. If the system flags any feverish symptoms such as sweat or discoloration, it can notify healthcare staff and prompt immediate intervention.

Other technology companies––Microsoft, for one––have rolled out similar remote diagnostic and alert tools in facilities across the globe. Their unique capabilities vary, but their purposes are the same: to prevent the spread of infection and provide support to overworked personnel.

As representatives for Microsoft shared in a recent press release, “[AI technology] not only improves the efficiency of epidemic prevention, but it also reduces the work burden of frontline personnel so that limited human resources can be used more effectively.”

In these resource-strapped time, the aid is undoubtedly needed.

AI’s Applications for Diagnostics and Patient Management

Fighting a pandemic is a task that requires speed. Now more than ever, providers must be able to accurately and quickly identify infected patients so that they can trace and hopefully contain the viral spread. But doing so isn’t an easy order.

To borrow a quote from Forbes contributor Wendy Singer, “Analyzing test results nowadays requires skilled technicians and a lot of precious time, as much as a few days. But in our current reality, healthcare systems need to analyze thousands of results instantly, and to expose as few lab workers as possible to the virus.”

We don’t have that kind of time––and we can’t put our lab workers at undue risk. Thankfully, cutting-edge AI technologies may provide a solution. With AI, hospitals can automate some steps of the testing process, cutting down on the time and effort needed to process test results. These capabilities aren’t just hypothetical; in the weeks since the start of the pandemic, the health tech startup Diagnostics.ai has provided laboratories in the US and UK with a diagnostic tool that streamlines the testing process by automating DNA analysis.

However, the applications of AI diagnostics aren’t limited to testing alone. Some have also used artificial intelligence to support population management in overstretched hospitals. One Israeli medical-device developer, EarlySense, recently developed an AI-powered sensor that can identify which patients will most likely face complications like sepsis and respiratory failure within six to eight hours. This can give a hospital the information it needs to best allocate limited resources and staff attention.

No AI innovation — no matter how brilliant or helpful — will fix our resources shortfall. There is no question that healthcare providers need more PPE and support, or that they need it immediately. However, the benefits that AI provides to screen and patient management efforts are evident. It seems reasonable that we at least consider the weight the deployment of such tools could remove from our exhausted front-liners’ shoulders.

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IoT in Sustainability and Circular Economy

How will the IoT support sustainability and a circular economy? Perhaps we might want to first ask ourselves are these all just buzzwords in a long list of words? Or are businesses, governments, and citizens truly stepping up and making significant commitments to use technology to change their wasteful behaviors? Before we can answer these questions, we might need to properly define these terms.

Sustainability is about finding ways to meet the needs of the present without compromising the ability of future generations to meet their own needs. With that in mind, we should note that depending on who you ask, everyone has their own perspective about the world and how they perceive it differently from others. In the enterprise, sustainability programs and strategies direct businesses in these directions.

The Ellen MacArthur Foundation is considered an authority, so let’s work off its definition to explain it. The circular economy is restorative and regenerative by design, in contrast to the “take-make-waste” linear model.

In a circular economy, economic activity builds and rebuilds overall system health. A circular economy is sustainable, because resources are used and reused and reused again. There are three principles as part of a circular economy: designing out waste and pollution, keeping products and materials in use, and regenerating natural systems.

Consider the first principle (designing out waste and pollution), which removes negative impacts of economic activity, such as the release of greenhouse gases and other types of pollution.

In a circular economy, we’re keeping products and materials in use. It’s a circular track instead of a one-way road to a landfill, basically. Reuse requires design that prioritizes durability and remanufacturing or recycling. By avoiding non-renewable resources like fossil fuels, a circular economy also helps regenerate natural systems by using renewable energy sources or returning nutrients back to where they came from after use.

This is very different from the more linear economic model we typically follow today, which is: use, discard, repeat, repeat, repeat.

In fact, gadgets and connected devices have been a huge culprit in undermining a more circular economy. Cellphones, for instance, use precious metals in their construction, but, for the most part, these devices aren’t recovered for future use. We all know that better, faster smartphones are always on the horizon. As consumers there is no question most of us will take the bait and replace our phones within the next couple of years whether our “old” phones are truly at the end of their lives or not.

Consider this: if the manufacturer of new devices is using non-renewable resources, and we’re not reusing these devices, but rather using them and discarding them, then how long will it be until the resources we need to build these devices are exhausted?

The resources themselves will be trapped in the discarded devices sitting in some landfill somewhere. They are not helpful to consumers anymore at that point. They are no longer supporting the economy. Based on the point discussed so far, it’s not a sustainable model at all to think that as an industry or consumers we can continue to use resources in devices without designing in the ability for reuse and/or recycling.

So how can the IoT (Internet of Things) help support a more circular economy? One way is by making products easier to maintain and repair. By adding intelligence to a product or device, the Internet of Things technologies can create an asset that can signal problems, determine when it needs to be repaired, and schedule its own maintenance.

This helps ensure that the product or device is kept in working condition for longer and needs to be replaced less frequently. Another way the IoT can contribute to a circular economy is by enabling a shared-use model.

To date, companies like Uber and Airbnb have exploded in popularity in the past decade, because temporarily using other people’s cars and holiday homes for a fee makes so much more sense in some cases than the alternatives.

This begs the question why can’t consumers and businesses start to think about all the things that are owned that are rarely used and have a shared-use scenario? Consider things like camping equipment you only use once a year? How about tools?

Automobiles have proven to be the biggest offender of the circular economy. Most of the time, our personal vehicles are just sitting there, taking up space. In order to manufacture those cars, we had to use resources, and those resources won’t get recycled back into the economy as long as your car is “in use,” which actually means just waiting around in parking lots and garages waiting to be driven.

And while most suburbanites fully appreciate the convenience of owning a personal vehicle, (I personally live in the suburbs myself), many families own vehicles, one can’t help but realize that this is a pretty flawed system overall. Perhaps that’s why the current generation doesn’t want to get a driver’s license at the age of 16, much like previous generations couldn’t wait to do. So today, there are plenty of car-share apps and companies out there to help address this conundrum.

But in terms of smaller items, like tools or gear or appliances, IoT sensors can turn a product into a sharable asset.

The Ellen MacArthur Foundation provides a great example of a drill. Do we consume a drill or use it? Most people use it, of course. It’s a distinction that raises the question of owning things that we use versus things we consume.

If you only use a drill once a year to hang something on the wall, do you need to own it? How many fewer drills would the world need if everyone approached it this way?

So this begs the question, should more companies be providing trade-in programs and recycling programs to decrease the impact on the environment and allow used devices to return value back into to the economy?

This only leaves the question, how does all this fit into the United Nations’ Sustainable Development Goals? In fact, if you look around you will see hundreds of companies actively seeking to meet the UN’s sustainability goals.

The UN’s Sustainable Development Goals include things like achieving clean energy, creating sustainable cities and communities, and pursuing responsible consumption and production as we have been talking about for months. This is all part of the same bigger sustainability picture.

A circular economy is one that uses clean energy and pursues responsible consumption and production to ultimately create a more sustainable earth. It’s all connected, in a world that’s highly connected, and very wasteful.

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