4 innovations that are revolutionizing the Internet of Things

The Internet of Things (IoT) is reshaping every industry from manufacturing to medicine, and opportunities to transform business are nearly limitless. And while IoT is a complicated endeavor requiring multiple partners, skillsets, and technologies, new innovations are making projects easier to deploy, more secure, and more intelligent than ever.

Below I’ve called out four innovations that are revolutionizing the IoT industry. To learn more about how to take advantage of these innovations, be sure to register for our upcoming IoT in Action Virtual Bootcamp.

IoT in Action virtual event details

1. Artificial intelligence (AI) and cognitive capabilities

Cognitive services and AI used to come with a high price tag. But times have changed, and these capabilities are becoming increasingly accessible.

IoT Hub and Cognitive Services enable you to tailor IoT solutions with advanced intelligence without a team of data scientists. Not only do AI and Cognitive Services make it easier to infuse IoT solutions with capabilities such as image recognition, speech analytics, and intelligent recommendations, but they also help companies act on the data being gathered and realize the true value of IoT. Scenarios are virtually limitless. Companies like UBER are using visual identity verification to increase platform security, and Spektacom is making cricket better with its AI-infused sticker for cricket bats that can deliver insights around batting style.

2. Real-time analytics at the intelligent edge

You need data analytics to make your IoT solution complete, but all the data you need is not where you want it to be—it’s at the edge. One solution is to reproduce a cloud environment locally, but this can be costly and you may end up having to support two solutions, not one.

Now you can extend cloud intelligence and analytics to the edge. Azure IoT Edge optimizes performance between the edge and cloud, reducing latency, so you get real-time data. This secure solution enables edge devices to operate reliably even when they have intermittent cloud connectivity, while also ensuring that only the data you need gets sent to the cloud. And by combining data from the cloud and data from the edge, you get the best of both worlds.

3. More secure IoT devices

IoT security continues to evolve. Which means it’s never been easier to lock down your IoT solutions. At Microsoft, we continue to build uncompromising security into every product we make. We recently released Azure Sphere, which is an end-to-end solution for creating highly-secure, connected devices using a new class of microcontrollers (MCUs). Azure Sphere powers edge devices, combining three key components including Azure Sphere certified MCUs, Azure Sphere OS, and the Azure Sphere Security Service.

4. Provisioning IoT quickly at scale

Provisioning IoT manually is time-intensive and can quickly become a showstopper, especially when you’ve got hundreds, thousands, or even millions of devices to configure. Even if manual provisioning is possible now, building in the capability to quickly and securely provision future devices is critical.

Azure IoT Hub features a Device Provisioning Service (DPS) that enables remote provisioning without human intervention. Azure DPS provides the infrastructure needed to provision millions of devices in a secure and scalable way. DPS extends trust from the silicon to the cloud where it creates registries to enable managed identity services including location, mapping, aging, and retirement. It works in a variety of scenarios from automatic configuration based on solution-specific needs to load balancing across multiple hubs to connecting devices based on geo-location.

Register for the IoT in Action Virtual Bootcamp

To learn more about how you can take advantage of these innovations, be sure to register for an IoT in Action Virtual Bootcamp. Whether you are an engineer, software architect, or practice owner, this virtual bootcamp will give you a clear understanding of IoT from device to cloud and accelerate the development of an IoT solution for your business.

This event will help you get hands on with the latest in IoT devices and cloud services including secure MCUs, IoT OSes, and advanced application services. You will also receive trusted guidance and a singular ecosystem view, supporting you in the design of secure IoT solutions that add real-world business value and create exciting new customer experiences. Join us to establish a leadership position in the IoT ecosystem by creating new experiences and revenue streams while optimizing bottom-line performance.

Register for an IoT in Action Virtual Bootcamp in your time zone:

Interested in attending one of our in-person IoT in Action event? Register for a free event coming to a city near you.


Fast, accurate, stable and tiny: Innovative algorithms breathe life into IoT devices

——Group of guys standing around talking

In the larger quest to make the Internet of Things (IoT) a reality for people everywhere, building devices that can be both ultrafunctional and beneficent isn’t a simple matter. Particularly in the arena of resource-constrained, real-time scenarios, the hurdles are significant. The challenges for devices that require quick responsiveness—say, smart implants that warn of impending epileptic seizures or smart spectacles providing navigation for low-vision people—are multifold. Small form factors and tiny microcontrollers mean that the training and prediction, via machine learning, that would make these devices smart and helpful must take place in the cloud, requiring significant amounts of data to be amassed and uploaded in real time. This introduces very real hurdles in areas such as connectivity, bandwidth, latency, power, and even privacy and security. For an individual prone to seizures, enjoying a swim in the community center pool, timing (latency) is everything, and the ability to leave the house for an entire day on a single charge (power) is survival itself. In the case of smart spectacles, constantly uploading video to the cloud, too, would soon cause bandwidth, latency, and power concerns and almost certainly introduce privacy issues.

The solution then would seem to lie in the area of making machine learning and prediction algorithms that currently reside in the cloud local to the devices themselves. And yet the hardware capacity of such devices is severely constrained, often relying on IoT endpoints having just 2 KB of RAM and 32 KB flash memory.

“We are trying to change the IoT paradigm fundamentally.” – Manik Varma, Principal Researcher, Microsoft Research India

The EdgeML team at Microsoft Research India has been examining this challenge from the point of view of machine learning and is building a library of ML algorithms—the EdgeML library—intended to have a range of both traditional ML algorithms, as well as deep learning algorithms, including the use of recurrent neural networks (RNNs) that could be used to build such devices and tackle some of these applications. RNNs are powerful deep learning models in how they make use of sequential information and incorporate context from previous inputs; just as humans don’t start thinking from scratch every second, RNNs are networks with loops in them that allow information to persist.

Squeezing RNN models and code into a few kilobytes could allow RNNs to be deployed on billions of IoT devices, potentially transforming many existing challenges for individuals and communities across myriad life scenarios. Downsizing the RNN also could significantly reduce the prediction time and energy consumption and make RNNs feasible for real-time applications such as wake-word detection, predictive maintenance, and human activity recognition.

The problem is that RNN training is inaccurate and unstable as the time interval over which the sensor signal is being analyzed increases. And in the types of resource-constrained and real-time applications that we’re talking about above, an additional concern is RNN model size and prediction time.

In FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network—being presented at the 32nd Conference on Neural Information Processing Systems (NeurIPS 2018) in Montreal, Canada—Aditya Kusupati, Prateek Jain, and Manik Varma of Microsoft Research India, along with Manish Singh of the Indian Institute of Technology Delhi and Kush Bhatia and Ashish Kumar of the University of California, Berkeley, introduce innovative new architectures for efficient RNN training and prediction on severely resource-constrained IoT devices too tiny to hold existing RNN models.

FastGRNN stands for Fast, Accurate, Stable and Tiny Gated Recurrent Neural Network algorithm, designed to address the twin RNN limitations of inaccurate training and inefficient prediction. It turns out that FastGRNN matches the accuracies and training times of state-of-the-art unitary and gated RNNs but has significantly lower prediction costs. Models range from 1 to 6 KB for real-world applications.

“We asked ourselves, how can we get machine learning to actually run on such severely resource-constrained microcontrollers and IoT devices,” recalled India’s EdgeML team member and Principal Researcher Manik Varma. “The traditional IoT paradigm has been that these devices have been too weak to do AI, so everyone thought that all the data had to be sent to the cloud and all the decision making would happen there. But, unfortunately, this traditional paradigm cannot address lots of critical scenarios where you need to make decisions on the device itself.”

The team set out to conquer the four challenge areas presented by localizing machine learning on the microcontroller itself: bandwidth, latency, power, and privacy/security.

They had started this project roughly two years ago and turned heads at ICML 2017 when they published two papers (Bonsai and ProtoNN) showing how they had managed to deploy traditional machine learning on the world’s tiniest devices—microcontrollers smaller than a grain of rice, such as the ARM Cortex M0 with just 2 KB of RAM, and miniscule IoT boards, such as the Arduino Pro Mini, based on an 8-bit Atmel ATmega328P microcontroller operating at 8 MHz without any floating point support in hardware, with 2 KB RAM and 32 KB read-only flash memory.

It may have been the first time anyone in the world had gone so small with machine learning—and it got some serious attention.

“We are tackling critical scenarios beyond the pale of the traditional IoT paradigm, where it is not feasible to transmit sensor data to the cloud due to latency, bandwidth, energy, privacy, or security concerns and where the decision making needs to happen locally on the IoT edge or endpoint device itself.” – Manik Varma

Intent on building upon the success, the team intensified its focus on the more challenging problem of deep learning. In an IoT world, almost everything happening takes the form of a time series. Think of the case of a moisture sensor embedded in the soil on a farm taking periodic readings on water moisture at a specific location; based on a series of chronological readings, it would make a decision on whether to irrigate that particular location. The state of the art for analyzing time series is RNNs. And so, they started looking at leading RNNs as a way of solving the size and resource problem.

Honest, Abe – they’re tiny! One of the chips on which the EdgeML team is deploying its ML algorithms, sitting atop a Lincoln penny.

But RNNs have a couple of issues. One is that they are not very easy to train. Most RNNs and other deep learning methods are trained based on gradient descent¬–type algorithms. Unfortunately, in the case of RNNs, the gradients are not very stable. They explode in some directions (to infinity) and vanish (to zero) in others. This has been a problem for RNNs since the time they were developed. Researchers have come up with many ways to solve this problem. One is unitary RNNs, which restrict the range of the state transition matrix’s singular values. Unfortunately, they also increase the model size, as they require a larger number of hidden units to make up for the loss in expressive power. Therefore, unitary RNNs are not ideal for these tiny devices, where you want to conserve memory and make predictions as quickly as possible.

Gated RNNs, another idea that researchers have experimented with to address this issue, stabilize training by adding extra parameters. Gated RNNs can deliver state-of-the-art prediction accuracies, but the models themselves are sometimes even larger than unitary RNNs.

The EdgeML Team came up with another approach.

“What we realized is, if you take the standard RNN architecture and just add a simple residual connection, it stabilizes the RNN training and it does so provably,” said Varma. “It only has two extra scalar parameters—as compared to an RNN—and it gets you better accuracy than any of the unitary methods proposed so far.”

Based on this insight, they then modified the residual connection slightly by converting it to a gate. “This achieved an accuracy that matches the state of the art in LSTMs, GRUs, and so on, but with a model that is two to four times smaller,” explained Varma. Gated RNN that hit speed, achieved accuracy, remained stable and – was tiny. FastGRNN.

To compress this model even further, the researchers then took all the FastGRNN matrices and made them low rank, sparse, and quantized. This reduced the size by a factor of 10.

“Based on this, we were able to build a wake-word detector for Cortana using a 1KB model and fit it on the Arduino boards,” said Varma.

The team’s code is available online for free on Github.

Accommodating real world IoT off the cloud

The real-life applications brought into the realm of the possible by FastGRNN are seemingly unlimited, with ideas cropping up across smart health care, precision agriculture, augmenting of abilities for people with special needs, and even space exploration. The EdgeML team is prototyping a smart cane for low-vision people.

“We’re focusing on getting the machine learning algorithms as compact as possible. Our hope is that if you can fit them onto the tiniest microcontroller, then any other microcontroller can also run them,” said Senior Researcher and Edge ML teammate Prateek Jain.

Hence the EdgeML team’s smart cane prototype that can interpret gestures and then can interact with the user’s phone. A twirl with the cane gets the user’s phone to report present location. A double-swipe gets the cane to answer the owner’s phone. A fall detector, for example, for the blind or for the elderly could instruct the owner’s phone to call for help.

Smart spectacles for people with low-vision represent another example of on-the-spot, real-time training and prediction that could transform lives and one deeply significant to Varma, who is himself low-vision. “It would be enormously helpful to have a camera on my glasses that would tell me what’s happening in the world, who I am looking at, and so on, he said. “You can’t send the whole video stream to the cloud; it would be too costly and there wouldn’t be enough bandwidth.” And again, latency is an issue if the spectacles were to be depended upon to warn one of hazards when walking on the street.”

Privacy is paramount and a problem that is addressed by miniaturizing deep learning. “You don’t want your visual or voice data being streamed to the cloud all the time. That would be creepy, everything you say or see in your home being recorded and sent to the public cloud,” said Varma. With the EdgeML team’s methodology, voice detection is run locally and not being sent to the cloud at all.

The EdgeML team (left to right) – Aditya Kusupati, Don Dennis, Manik Varma, Harsha Vardhan Simhadri, Shishir Patil, Rahul Sharma, Nagarajan Natarajan, Prateek Jain.

“We spent a lot of time talking to many different Microsoft product groups, startups, scientists, and the government trying to figure out applications,” recalled Jain.

An interesting application the team came across was in astronomy and space exploration. Resource scarcity—specifically energy—in spacecraft and machines that are sent into deep space is a huge issue. Another is the fact that satellites and probes collect an enormous amount of data via telescopes, cameras, and other sophisticated sensors; yet astonishingly, only a miniscule fraction of the data that is sensed is ever seen by a human being. If there were energy-efficient, low-latency machine learning available on the sensors themselves, the on-chip algorithms could learn what data is most interesting, and then determine which data would be sent for human analysis.

Varma has been invited as a Visiting Miller Research Professor at UC Berkeley to work on some of these problems. “It’s one of the great things about Microsoft Research, the amount of freedom and support you get for blue skies research, to take risks and to collaborate with people inside and outside Microsoft,” he smiled. In the case of FastGRNN, we may be looking at the stars.


Sam George: What to expect from Microsoft at this week’s IoT Solutions World Congress

It’s amazing to see how IoT is transforming our customers’ businesses—from optimizing operations and reducing unplanned downtime with companies like Chevron, to powering new connected vehicle experiences as we recently announced with Volkswagen.

Beyond business transformation, IoT has the potential to create more efficient and vibrant cities and communities by providing new insights and approaches to transportation and traffic, energy reduction, construction, utilities, parking, and so much more.

We are continuing to simplify the customer journey for secure, scalable IoT solutions for the cloud and the edge with a large set of announcements last month, including the general availability of Azure IoT Central at our Ignite 2018 conference, and more just last week about bringing intelligence to the edge in Windows IoT.

This week at IoT Solutions World Congress, we look forward to connecting with companies across industries and inspiring them with new possibilities for IoT, from creating Digital Twins of physical environments to taking advantage of Vision and AI on edge devices. We’ll also be talking about how we’re breaking down common barriers to entry in IoT by addressing security from the start with solutions like Azure Sphere and Azure Security Center for IoT, and empowering organizations to provision and customize fully managed IoT solutions in minutes with Azure IoT Central. And that’s just the start.

Vision and AI at the edge power breakthrough applications

Vision and AI capabilities on edge devices are the ultimate sensor and will help companies create breakthrough applications. From automatically detecting manufacturing defects, to detecting any object, to detecting unsafe conditions in the enterprise or industry—the possibilities are endless.

Today we are announcing the public preview of a Vision AI developer kit, the newest addition in the Microsoft Azure IoT starter kit family, for IoT solution makers to easily deploy AI models built using Azure Machine Learning and Azure IoT Edge. The kit includes a device using Qualcomm Visual Intelligence Platform for hardware acceleration of the AI model to deliver superior inferencing performance. To get started, visit

Vision AI developer kit

Model the physical world with Azure Digital Twins

At Ignite, we introduced Azure Digital Twins, a breakthrough new offering in our IoT platform that represents the evolution of IoT. Azure Digital Twins enables customers and partners to create a digital model of any physical environment, connect it to IoT devices using Azure IoT Hub to make the model live, and then respond to changes in it to create serverless business logic. Customers and partners can now query Azure Digital Twins in the context of a space—rather than from separate sensors—empowering them to build repeatable, scalable experiences that correlate data from digital sources and the physical world.

Today we are announcing that Azure Digital Twins is available in public preview. Several of our early partners are at IoT Solutions World Congress showcasing their solutions that span a wide range of applications that represents the broad applicability of Azure Digital Twins, including:

IoT partners

Applied innovation for smarter cities

Today, as cities and communities embrace digital transformation, technology like Digital Twins and easy-to-use machine learning is helping ideas become real, actionable solutions. Environments and infrastructure of all types—offices, schools, hospitals, banks, stadiums, warehouses, factories, parking lots, streets, intersections, parks, plazas, electrical grids, and more—can become smarter to help the people who use them live better lives. We’ll have more to share on this topic at Smart City Expo World Congress in November.

Connect with us at IoT Solutions World Congress

If you’re in Barcelona this week, connect with us at the Microsoft IoT booth (# C321) and hear from us in the following sessions:


How one nonprofit turned a golf course into a ‘no-fail’ job training program

Shawn Bennett was familiar with the feeling of failure when he was younger. Wrestling with anxiety and substance abuse, he had repeated run-ins with the law – and lacked the support needed to put his life on track.

“I was a self-run riot on cruise control to somewhere no one wanted to be,” is how he described his life after spending time in prison for operating a vehicle while intoxicated.

His situation was like many that John Schmidt, a corporate executive, had in mind when he and other founders – committed members of their community looking for solutions for people living in poverty – created Riverview Gardens. This unusual “no-fail” job training program in Appleton, Wisconsin, has helped more than 1,200 people, including Bennett, regain their footing and reclaim their lives. Schmidt, who has also served for years on the board of a local homeless shelter, knows any of us could face poverty, and even homelessness, because of bad luck and without a support system.

“There’s a very fine line today between the haves and have-nots,” says Schmidt. “There’s oftentimes this perception that there’s something wrong with someone who might be homeless. But most times, these are everyday people whose luck wasn’t quite as good as somebody else’s luck in life.”

The community center at Riverview Gardens, which was formerly a country club. This nonprofit program is supported in part by Microsoft TechSpark Wisconsin, a civic program that fosters greater economic opportunity and job creation in local communities across the country.

Riverview Gardens is situated on 72 bucolic acres of a former country club and golf course along the Fox River in Appleton, in the northeastern part of the state. Appleton has historically been known for its paper mills. It also has a legacy of firsts: The first electricity for sale came from a hydroelectric plant built by a paper company executive in the 1880s. It’s also home to the first telephone system in the country and the first electric trolley system.

In another kind of first, Schmidt and the founding members converted the Riverview Country Club into Riverview Gardens. This private country club, Wisconsin’s oldest, filed for bankruptcy in 2011.

a greenhouse
Lettuce is grown without soil in the pool at the former country club.

About 25 acres of the site are used for the certified organic farming of fruits and vegetables including beets, potatoes, carrots, herbs, tomatoes, onions and kale. There are 20 passive solar greenhouses also on site. The country club pool has gone from a place for swimming laps to growing lettuce without soil.

The hydroponic greenhouse is often tended to by individuals who are veterans who may have post-traumatic stress disorder or are experiencing homelessness.  They find it a more calming environment, in contrast to the noise and activity of the farm.

This nonprofit program is supported in part by Microsoft TechSpark Wisconsin, a civic program that fosters greater economic opportunity and job creation in local communities across the country, particularly in those outside major metropolitan centers. Appleton, with a population of about 75,000, is one of those communities, as is Green Bay, which is about 30 miles away.

Now crop land, Riverview Gardens was once home to a golf course and country club.

TechSpark is assisting Riverview Gardens in three areas. First, it provides technology that is being used in the hydroponics greenhouse to monitor and adjust water temperature, pH balance and nutrient levels in the pool. That should help to reduce the grow time. The technology is already making a difference, providing a more consistent harvest.

Second, Microsoft’s FarmBeats initiative is being employed. FarmBeats, also an AI for Earth feature project, uses ground-based sensors, Power BI, the Internet of Things (IoT) and TV white spaces (which leverage unused broadcasting frequencies to deliver broadband connectivity) to measure soil irrigation needs. It also helps determine the right time to apply fertilizer and other inputs, as well as how much to apply, to grow a more productive crop. Third, Microsoft is helping Riverview Gardens undergo a digital transformation. In the past, the organization has kept much of its data – records like the seed distribution log, grow crop log, even handwashing logs – on paper. Riverview Gardens is now moving some of it to electronics records for better efficiency.

Riverview Gardens took 25 acres of the former golf course and converted it to a rich growing environment for fruits and vegetables, as well as a growing environment for the people it serves.

With these tools, Riverview Gardens can increase its farm yields and raise more money from the sale of produce, which funds the program’s operations. These tools also help give the Riverview Gardens staff more time to spend with the people who need it: their clients.

The technology is “helping us understand our farming better, our water quality better, streamlining our business processes and taking a lot of variability out of the entire operation so that we can focus on the people that we’re serving, and not have to worry as much about other aspects of the business,” says Schmidt.

Photo of John Schmidt
John Schmidt, CEO of U.S. Venture, is among the founders of Riverview Gardens.

Those who participate in Riverview Gardens’ program also can work in the kitchen or otherwise help with setup at events at the club, now a community center. They also work to help clean Appleton’s downtown streets, early in the morning, after they’ve received training on equipment used for cleanup. Or they might do maintenance – such as painting, lawn care or snow removal – at other nonprofits and businesses in town.

Once participants complete 90 hours of work – known as ServiceWorks – along with ongoing counseling about job and life skills, Riverview Gardens helps them find – and keep – jobs by following their progress for three years.

“No matter how long it takes you to do 90 hours, whether that’s three weeks or three years, we will always accept you back into the program, and you will just continue where you left off,” says Pilar Martinez, the director of community engagement at Riverview Gardens.

Baked into Riverview Gardens’ recipe for success is its “no-fail” policy. Those who may have experienced roadblocks in the past are provided the tools and opportunities to not fail.

“’Success’ is a subjective term and can be different for many different people,” says Martinez. “We look at the resiliency of the people we serve and the barriers they overcome to move themselves forward.”

No matter how long it takes you to do 90 hours, whether that’s three weeks or three years, we will always accept you back into the program.

Shawn Bennett at Riverview Gardens’ Earn-A-Bike shop. Those going through Riverview Gardens’ program, as well as volunteers who help out on the farm, can earn a refurbished bike by working a certain number of hours.

For Bennett, “coming out of prison, not having any family – there was no real support, no real comfort,” he says. Bennett, 49, earned his high school equivalency diploma in prison, and is now working as a tech intern at Fox Valley Technical College, which serves about 50,000 students a year.

There, he has earned an associate degree in computer support, and is working on two other related degrees. He was awarded a Fox Valley Technical College Foundation scholarship for an essay about his personal story, something he wrote after going through Riverview Gardens five years ago.

“The sense of community at Riverview Gardens really helped me,” says Bennett. “To be in a place like this, it makes you feel like you’re welcome here. You’re part of something.”

Carl Gustavson says Riverview Gardens made a huge difference in his life.

Carl Gustavson, 29, is also among those who found success after going through a tough time. Things became difficult for him after moving to Nashville to pursue his dream of being a musician.

“I thought I was going to be like Woody Guthrie; he rode the rails and played his guitar for people,” says Gustavson. “I kind of had a romantic view of being a musician. But the reality is you can end up living in a tent, like I did, and just start feeling like you can’t do anything.”

Gustavson is grateful for the help he has received at Riverview Gardens.

“I was frustrated – by society and by my situation,” he says. “I didn’t think it was ever going to get better. I thought I was going to be stuck in a rut forever.”

After completing ServiceWorks, he was placed in a job doing detail work at a car dealership last spring. He feels optimistic about the future, and at some point, says he would like to use the bachelor’s degree in marketing he earned in 2011.

’Success’ is a subjective term and can be different for many different people,” says Martinez. “We look at the resiliency of the people we serve and the barriers they overcome to move themselves forward.

Much of the spark and enthusiasm at Riverview Gardens comes from its staff, led by executive director Cindy Sahotsky. She is often right in the middle of the action, no matter the job. When program participants visited Sacred Heart Parish to help remove large stones where a tree once stood, Sahotsky grabbed a shovel and plunged into the work at hand.

“She values people, and she expects that if she’s going to ask them to do something, she has to do her part,” says Laura Savoie, the parish’s business manager. “She pitches right in. And she does have high expectations. She expects you to do what you said that you’d do.”

Riverview Gardens executive director Cindy Sahotsky, front, center, wearing a dark sweatshirt, surrounded by some of the nonprofit’s staff, and Microsoft TechSpark Wisconsin manager Michelle Schuler, front, third from left.

There is also a three-year “follow” program, based on findings that show individuals who have been incarcerated and are tracked for that length of time, with guidance and counseling, have the lowest recidivism rate, according to Sahotsky.

The follow program offers support with Riverview Gardens alumni who are now employees elsewhere, and also offers those employers guidance regarding behavior. For employees, it can include concerns like how to get a bus pass or feeling like a boss doesn’t like a worker. For employers, it might mean getting Riverview Gardens’ help coaching an employee who is taking breaks too often, or guiding an employee to be more patient in the workplace.

“The people we serve are individuals who have multiple barriers to long-term employment,” says Sahotsky. “Riverview Gardens really came to be to address that root cause of homelessness. It’s not because our folks can’t get jobs. It’s that they struggle to keep them because they have barriers.”

To be in a place like this, it makes you feel like you’re welcome here. You’re part of something.

Sahotsky, who also oversees the COTS homeless shelter in Appleton, the same place where Schmidt volunteers, is a former corporate human resources manager. She knows how such issues can loom large for the clients Riverview Gardens serves.

“Getting the job is just one part of that whole process,” says Sahotsky. “Keeping that job, getting to work, getting along with others – those are all part of it. Having expectations that people who have multiple barriers to stable employment are just going to get a job and keep it is probably not realistic. They’re going to need support to continue along in this process.”

The program is free to participants. In addition to the money raised from the sale of produce grown at Riverview Gardens, revenue from the rental of the country club building for special events is used to run Riverview Gardens.

Volunteers often work on the farm alongside program participants and staff. “We believe all people have value and contribute to the community in which they live,” is part of the nonprofit’s credo.

And not only are area employers involved in hiring Riverview Gardens’ clients, but many from throughout the state also come to work on the farm as volunteers. So do many residents of Appleton. It’s a true partnership. Working together in the fields, no one knows the other person’s title, or background, or standing. They just know one another by the smiles and first names they share.

“The partnerships Riverview Gardens has with employers and the larger community, to create economic opportunities for those who need them, is one of the things that makes it so effective,” says Microsoft TechSpark Wisconsin manager Michelle Schuler. She also serves on this nonprofit’s board. “It’s a real pleasure for those of us at Microsoft to work with Riverview Gardens to help digitally transform their services, and as a result, even more lives.”

That transformation, Schmidt points out, is about recognizing that any of us could be in a position in which we need retraining or other support to help put our lives on better paths.

Top photo: Microsoft’s FarmBeats initiative is being employed at Riverview Gardens in Wisconsin. FarmBeats uses ground-based sensors, Power BI, the Internet of Things (IoT) and TV white spaces to measure soil irrigation needs. Follow @MSFTissues on Twitter. 

Photos courtesy of


Microsoft announces the public preview of Windows 10 IoT Core Services

Woman holding a Windows IoT device

The Internet of Things (IoT) is transforming how businesses gather and use data to develop competitive insights and create new financial opportunities. As IoT technology matures and our partners gain more experience, they are evolving their business models to increase the overall return on investment of their IoT solutions. This includes adding recurring revenue, enhancing security, and reducing support costs.

At Computex a few weeks back, we announced Windows 10 IoT Core Services, which enables our IoT partners to commercialize their solutions running on Windows 10 IoT Core. We are now excited to announce the public preview of this service along with details on purchasing and pricing. As described in our previous blog, IoT Core Services provides 10 years of operating system support along with services to manage device updates and assess device health.

Windows 10 IoT Core Services helps our partners monetize their solutions by creating a business model that provides ongoing long-term value. IoT devices are often in service for many years, so device support costs are important considerations that are either included in the initial purchase cost or often paid over time through a service contract. Windows 10 IoT Core Services provides our partners with the ability to distribute maintenance costs over the life of the device while also giving them tools to streamline and reduce maintenance overhead. This service can be purchased up front with a device or through a recurring subscription and provides 10 years of operating system support, including updates for security and reliability.

Device Update Center is part of the Windows Hardware Device Center and is used to create, control, and distribute device updates for the OS, custom apps, drivers, and other files. The steps to register a new Windows 10 IoT Core device are described in the Device Update Center User Guide. Entries can be created in Device Update Center for each unique device model as shown below.

Device Update Center

Device Update Center

OS updates and custom updates (apps, drivers and files) are delivered through the same content distribution network that is used daily by hundreds of millions of Windows users around the world. Updates can be flighted in three distinct rings – Preview (test devices), Early Adopter (self-host devices) and General Availability (production devices) to have a controlled roll-out process where new changes can be validated with smaller sets of devices before broader deployment.

Flight 2

In addition to long-term support and device update control, Windows 10 IoT Core Services includes rights to commercialize with Device Health Attestation. This cloud-based service evaluates device health and can integrate with a device management system to improve the security of an IoT solution. These features give our partners the foundation to build sustainable business models based on Windows 10 IoT Core.

The Windows 10 IoT Core operating system remains royalty-free. Windows 10 IoT Core Services is a paid offering that can easily be added depending on the scenario.

  • Businesses and solution integrators can purchase IoT Core Services through an Azure subscription. The subscription price will be $0.30 per device per month when the product releases later this fall. During the preview period, the price is $0.15 per device per month.
  • Partners enrolled in our Cloud Solution Provider (CSP) program will be able to resell the service and establish ongoing relationships with their customers. They can sell a flexible, pay-as-you-go subscription as needed to meet device requirements. This option will be available later in the year.
  • OEMs can license the service with a device by pre-paying for the service. This option will be available later in the year.

Microsoft is committed to offerings to help our partners provide compelling solutions and achieve their business goals. Along with our recently announced support for NXP silicon platforms, long-term support, and the Windows AI Platform, Windows 10 IoT Core Services is another step in meeting our partners’ needs.

To learn more about developing with Windows 10 IoT, enroll in our Early Adopter Program at and to learn more about Windows 10 IoT Services, see the technical details at the Windows IoT Core Dev Center.


Microsoft announces Windows 10 IoT Core Services at Computex 2018

Man standing working in a factory.

Similar to the embedded devices that came before them, modern IoT devices are often used in places where physical servicing is difficult and expensive. For example, it’s expensive for an oil company to put a technician on a helicopter to service equipment on a platform at sea. As a result, commercial IoT devices need to be supported and in service for far longer than their consumer counterparts.

Today at Computex 2018, we are excited to announce Windows 10 IoT Core Services. This offering will provide 10 years of support along with services to manage device updates and assess device health, enabling our IoT partners to create solutions to address their customers’ needs.

Windows 10 IoT Core is an edition of Windows 10 designed for building smart things and optimized to power intelligent edge devices. First released in 2015, it has been adopted by industry innovators such as Johnson Controls, Askey, and Misty Robotics.

Building on the Windows 10 IoT Core operating system, Windows 10 IoT Core Services will be a paid offering for IoT devices. The free edition of Windows 10 IoT Core will still be available via the Semi-Annual Channel (SAC).

  1. 10 years of Windows OS support via the Windows Long-Term Servicing Channel (LTSC) which provides quality updates to keep device security up to date. Devices using the LTSC release won’t receive feature updates, enabling them to focus on stability by minimizing changes to the base operating system. Microsoft typically offers new LTSC releases every two to three years, with each release supported over a 10-year lifecycle.
  2. Update control with the newly announced Device Update Center (DUC) which provides the ability to create, customize, and control device updates. These updates are distributed by the same Content Distribution Network (CDN) as Windows Update which is used daily by millions of Windows customers around the world. Updates can be applied to the operating system, device drivers, as well as OEM-specific applications and files. Updates can be flighted to test devices prior to broader distribution.
  3. Device Health Attestation (DHA) enables enterprises and OEMs to raise the security bar of their organization with hardware-attested security. Evaluating the trustworthiness of a device at boot is essential for a trusted IoT system and a device cannot attest to its own trustworthiness. Instead, this must be done by an external entity such as DHA Azure cloud service. This service evaluates device health and can be combined with a device management system, such as Azure IoT Device Management. With this, you can take actions, for example, re-imaging the device, denying network access or creating a service ticket.

With these features, you can commercialize a device built on Windows 10 IoT Core and know that you have the enterprise-grade support and security that is synonymous with Windows. We are currently in limited preview with this service; to join, please email A broader preview will be ready in July 2018, with general availability later this year.

Earlier in the year, we announced that with the next release of Windows 10 IoT, we will provide 10 years of support for both Windows 10 IoT Core and Windows 10 IoT Enterprise. We also announced a partnership with NXP to support Windows 10 IoT Core on their i.MX 6 and i.MX 7 processors. The Windows 10 IoT Core Services offering builds on these announcements, as we continue to evolve the platform and make investments to support the IoT devices of today and tomorrow. We are excited about the possibilities and hope you will join us to create the future of IoT.

Windows 10 IoT – Tomorrow’s IoT today

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Updated June 5, 2018 11:03 pm


Enable deeper connections with patients through medical IoT

It should come as no surprise that the internet of things (IoT) has tremendous potential to transform healthcare. Consumers are already familiar with IoT wearables, such as smartwatches and fitness bands, that enable them to track and improve their health at home. But at-home monitoring is just the start. Today, healthcare organizations are looking at how they can leverage IoT in their patient populations to enhance patient engagement, forge deeper connections, deliver more personalized care experiences, and improve adherence to care plans.

Helsa, one of Sweden’s largest private healthcare companies, recently implemented the Health360 ImagineCare Experience. The solution, from ImagineCare and Tribridge, a DXC Technology company, combines IoT monitoring, a patient engagement app, and care coordination tools to enable healthcare organizations to deliver right-size, right-time care, based on trusted information.

David Turcotte, Microsoft Global Industry Director, sat down with Helsa Regional Manager Jessica Hård Svensson, Helsa District Nurse Marie Blomster, and Gustav Hjelmgren, Cofounder of ImagineCare, to discuss how IoT is improving the lives of Helsa patients.

David Turcotte: Tell us about Helsa and the patient population you serve.
Jessica Hård Svensson: Helsa is a healthcare company with fifteen primary care units in Sweden. Our six outpatient units in southern Sweden, which I manage, serve 35,000 patients. As a general primary care practice, we care for the whole family, treating conditions from the common cold to severe chronic diseases.

Before piloting medical IoT, did you experience challenges implementing patient engagement initiatives?
Jessica: Of course! When you see your patients only once or twice a year, it’s very difficult to keep them motivated to stick to their treatment plans. Patients need ongoing engagement to make and maintain the shifts in lifestyle, like diet and exercise, necessary to manage chronic diseases.

I understand your pilot of the Health360 ImagineCare solution is still in its early phases, but you are already leveraging its medical IoT capabilities with select patients. What patient populations have you rolled it out to so far?
Marie Blomster: IoT remote medical sensing is ideal for patients with chronic diseases who need to frequently monitor their vital signs or levels. Right now, we are primarily using IoT for patients with diabetes and hypertension, since these patients need to continually track blood glucose levels and blood pressure. IoT remote medical sensing has improved the quality of care we can offer them.

What results have you seen from implementing IoT for this population?
Marie: Since patients can be monitored remotely with IoT, we have been able to respond much more quickly to undesirable metrics, such as high blood pressure and high blood glucose, which means that we can address potential emergencies before they happen.

Moreover, our doctors can make treatment decisions based on more accurate data. Without IoT, doctors often need to make medication decisions and dosage adjustments based on only one or two blood pressure values. With IoT, on the other hand, hypertension patients can monitor their blood pressure at home every day and automatically transmit the data to their care team, providing our doctors assurance that their medication decisions are based on accurate, representative data.

This has reduced the use of unnecessary medications, for example. Some patients present higher blood pressure in a clinical setting but have normal blood pressure when measured at home. Because our doctors now have the IoT data to see this, they are no longer prescribing blood pressure medications to patients who don’t need them.

Jessica: Moreover, since we engage with patients remotely, we have been able to reduce both planned and unplanned in-person visits to our primary care center.

What feedback have you received from patients on their experience with IoT and the ImagineCare solution?
Marie: Our patients have found IoT data highly motivating. For instance, we’ve given some of our patients IoT fitness trackers to encourage them to exercise more. ImagineCare gamifies exercise for them. They have become competitive around improving their metrics, which has motivated them to exercise more and meet the exercise goals recommended by their doctors.

Gustav Hjelmgren: On our side at ImagineCare, we’ve heard from Helsa patients that they feel much more connected to their care teams and that their care teams better understand their priorities. This closer connection makes them feel more secure. Moreover, because they have an ongoing conversation with their care team, rather than just being seen once or twice a year, there’s more continuity of care over time. This is fundamentally a new way of delivering care and it’s inspiring to see how patients are responding to it.

How do you anticipate IoT data will help you optimize the day-to-day flow of patients when you roll ImagineCare out to the larger population?
Jessica: IoT data will help us identify the high-risk patients who really need to be seen in person, so that we can prioritize them when scheduling appointments. That way we can focus on the patients who need in-person care. The rest of our patients—those who are in a place where they can effectively self-manage their care—we can engage with via the ImagineCare app. This will help us overcome a key healthcare challenge: the growing population of senior citizens coupled with the shortage of healthcare workers.

This will also be useful for managing the care of patients who are particularly anxious about their health. Because we will be able to monitor them and keep a close connection through ImagineCare, we hope they will feel less anxious and not feel the need to visit the clinic as frequently.

Are there other specific populations that you expect will see major benefits from IoT?
Gustav: There are a number of patient groups at Helsa with whom we are looking to use IoT. Beyond diabetes and hypertension, we see significant potential for IoT to benefit patients with chronic conditions like asthma, congestive heart failure, and chronic obstructive pulmonary disease.

Why did you choose ImagineCare over other IoT solutions on the market?
Jessica: The deciding factor was that ImagineCare is more complete than other applications on the market. Most IoT applications are designed to be used for only a very small sub-segment of the patient population. ImagineCare struck us as much more applicable to a wide range of patients, both those with specific chronic diseases and the general population. The connection between ImagineCare and Microsoft was also an attraction.

Gustav: We feel that Microsoft shares ImagineCare’s values and our ambition to create a new way to deliver care based on the preferences of each patient. A benefit of our relationship with Microsoft is that we partner with them to make ongoing improvements. For instance, right now we’re talking to Microsoft about how to add more AI and machine learning to the solution to enhance its intelligence. Microsoft also connects us to industry-leading partners to further enhance our total healthcare offering.

What do you anticipate for the future of IoT in healthcare and specifically at Helsa?
Jessica: I expect the technology and its applications in healthcare to become increasingly sophisticated, and we hope to keep Helsa on the cutting edge. Most importantly, though, I anticipate we will continue to use IoT and digital engagement strategies in combination with in-person care as a way to enhance the human connection at the heart of care, rather than replace it.

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