Smart Park Solutions Power Sustainable Development

Posted on by Micah Kaplan

We all want to help reduce carbon emissions and support sustainability goals. But while individual responsibility is important, large-scale industrial campuses are a major contributor to global CO2 emissions.

This is why many countries make smart business parks a key component of their carbon-reduction strategy. Smart parks are industrial, technological, commercial, or mixed-use venues that leverage AI and IoT technologies to improve energy efficiency and reduce waste.

These low-carbon parks are crucial. But unfortunately, they can be difficult to implement and manage. “Smart parks integrate a tremendous variety of energy- and resource-consuming equipment, such as power and water, heating and air conditioning, electrical systems, and more,” says Dr. Yang Yang, Chief Scientist at Terminus Group, a provider of smart city solutions. “It’s very challenging to collect, coordinate, and analyze all of that information—and many venue managers lack the technical and operational abilities needed to run a low-carbon park.”

The good news for cities and governments is that AIoT specialists have started to offer comprehensive smart park solutions. These integrated platforms provide the hardware and software tools needed to streamline the construction of smart business parks and upgrade existing venues and campuses to be more energy-efficient.

Smart Parks in Action: A Chongqing Case Study

Terminus Group’s deployment at the Chongqing branch of China’s Western Science City project is a case in point.

Western Science City is a government initiative aimed at creating a technology hub around the cities of Chongqing and Chengdu in China’s western Sichuan Province. The initiative is intended as an engine of innovation and entrepreneurship that will house major high-tech infrastructure such as the Chongqing University Laboratory for Ultrafast Transient Facility and the Chongqing Center of the China Natural Population Resource Biobank.

The site has tremendous scientific and economic potential—but needs to overcome the challenges of high energy consumption and fossil fuel use. For this reason, the managers of Western Science City-Chongqing partnered with Terminus Group to reduce carbon emissions and use resources more efficiently.

Working with Terminus Group, venue managers implemented an intelligent solar power storage and charging infrastructure. The solution uses an edge-powered digital twinning platform to monitor storage capacity and charging loads in real time and adjust the behavior of distributed photovoltaics (DPVs) and charging equipment accordingly. This enables Western Science City-Chongqing to optimize its energy storage, charging, and discharging strategies.

The implementation has been a success: accelerating the adoption of clean energy at the park, reducing utility costs, and cutting carbon emissions while at the same time supporting distributed sustainable power generation, electric vehicle use, and demand management.

AIoT and Edge Hardware Improve Planning and Management

AIoT smart park platforms like the one developed by Terminus Group are so powerful because of their ability to collect, aggregate, and analyze huge amounts of environmental information—and then translate all of that into smarter planning, design, and management.

On the level of planning and design, a smart park platform can be used to simulate facility performance and conduct comprehensive energy-efficiency audits. This allows venue managers to gain insights into how they’re using resources sitewide and take action if problems are detected. It also helps them compare and select optimal solutions before construction begins, to ensure that future development will be as sustainable as possible.

In terms of operations and management, smart park platforms offer several ways to save power and reduce emissions:

  • Building automation tools centralize management and control of mechanical and electrical infrastructure for load optimization.
  • Smart solar power systems with integrated storage and charging capabilities foster development of clean-energy infrastructure.
  • IoT smart metering and environmental monitoring at the edge provide real-time information on resource consumption and environmental conditions.
  • AI systems generate peak consumption reports that can be used to create better energy management plans.
  • AI systems monitor the IoT devices for signs of abnormal use and alert management if a problem is detected, allowing both on-site and remote-facilities managers to quickly intervene.
  • Intelligent robotics systems for food delivery, logistics, and security can be integrated to further reduce sitewide carbon emissions and improve the day-to-day experience of workers and visitors.

Integrated control and real-time analysis require significant processing power at the #edge—and sophisticated #AI behind the scenes. @Terminus_group via @insightdottech

Integrated control and real-time analysis require significant processing power at the edge—and sophisticated AI behind the scenes. For this reason, the technology partnership between Terminus Group and Intel is crucial in bringing this solution to market. “Our edge gateways, controllers, and all-in-one systems all use Intel® processors, which offer an extremely stable, reliable, and high-performance platform for computing at the edge,” says Dr. Yang Yang. “In addition, Intel® Smart Edge Open gave us an edge-native platform that helped speed the development and deployment of our applications, and the Intel® OpenVINO™ toolkit helps optimize the AI inferencing performance of our platform.”

The Outlook for Smart Park Solutions

Smart park platforms offer a clear path to construction and operation of low-carbon venues—and thus will be highly attractive to city planners, systems integrators, and campus managers.

In addition, the AI analytics capabilities of these platforms can make retrofits of existing industrial parks and technology campuses far more cost-effective. “Our solution can be used to create detailed energy conservation retrofit plans and even design cost-saving retrofit schematics,” says Dr. Yang Yang. “For example, a site upgrade might begin with building-integrated photovoltaics (BIPVs); the carbon emission reductions provided by BIPVs can then be converted into carbon credits or green certificates and traded on the market to offset the cost of the initial stages of construction.”

The world urgently needs to meet challenging carbon emissions targets in the coming years. Smart parks and AIoT platforms that support them help put these goals within reach—and promise a greener, more sustainable future for us all.

 

Edited by Georganne Benesch, Editorial Director for insight.tech.

Time-Sensitive Networking Poised to Transform Industrial IoT

Posted on by Micah Kaplan

Early IoT proofs of concept were built on architectures that transmitted edge sensor data directly to cloud instances where it could be analyzed for operational insights. But those deployments emphasized data more than long-term outcomes—and data is helpful only if you can respond to it.

The actual value and perceived potential of IoT suffered as a result, and now the exit of Google and IBM from the IoT platform business has some wondering whether IoT has failed altogether. It undeniably has not, but the gap between insights and outcomes still exists because of disparate business and technology paradigms that govern the IT and OT sides of IoT infrastructure.

Time-sensitive networking (TSN) is a framework for synchronizing the timing of Ethernet data to flow throughout converged enterprise and operational environments. It enables near real-time decision-making between controller, sensors, and edge devices where outcomes can be realized. With TSN, information and value exchanges can happen over a single, low-latency network that maintains the ability to prioritize different types of traffic.

Now, new capabilities are coming to market to streamline the development, deployment, and configuration of TSN networks. When paired with virtualization-friendly infrastructure, these new solutions empower industrial operators to port workloads across IoT deployments and drive outcomes when, where, and how they need them.

Standardizing Time-Sensitive Networking for Seamless IoT Integration

TSN is not the first or only deterministic Ethernet technology, but others are largely proprietary and don’t provide the openness to move data seamlessly in both directions across an end-to-end IoT network. The key value of TSN is standardization. It replaces proprietary fieldbuses with a converged network that virtualizes the connection between entities on the network and satisfies the ranging requirements of industry IT and OT stakeholders. IEEE’s Time-Sensitive Networking Task Group, established in 2012, is working to finalize the set of standards.

“We’re more than 10 years in on TSN standards work, but we can’t get there until the foundational technology has been defined, implemented, and tested,” says Joel Morrissette, Product Manager at embedded software supplier TenAsys Corporation, a real-time software and service provider. “What does it mean to configure the network? What does the data structure look like? How do the hardware and software stacks need to be supported? What’s the division of duties? How do I access TSN, from an application perspective?”

The good news is that TSN standards-compatible hardware and software that streamline network deployment are finally coming to market. There is now a range of commercially available Ethernet hardware that provides native TSN offloading. Intel® CPUs provide TCC functionality that enables the software stack to achieve the real-time performance required for TSN with higher precision than non-TSN-enabled CPUs. For instance, Intel® Ethernet products, Intel Atom® processors x7000E Series, 13th Gen Intel® Core™ embedded processors, and Next-gen Intel® Xeon® D-1700/2700 processors are all equipped with Intel® Time Coordinated Computing (Intel® TCC) technology.

“Every node in the network gets the same information and synchronizes down to microseconds, ensuring everybody is in lockstep with respect to time,” Morrissette explains. “Because of that coordination, we’re able to prioritize traffic and ensure low latency and a high degree of determinism.”

Time-sensitive #networking technology can unify #IT and #OT systems to deliver industrial #IoT network interoperability and workload portability. TenAsys Corporation via @insightdottech

Industrial IoT Steps Forward

Intel TCC provides the hardware features and software tools to ensure applications can meet real-time constraints, and TSN-enabled hardware helps control when and how data packets move through a TSN network. But taking advantage of these capabilities in deterministic applications like those running on industrial IoT systems still requires a high level of expertise to configure the application and TSN network to meet real-time constraints.

TenAsys INtime IoT software supplies the missing link. It is a scalable portfolio of TSN- and TCC-compatible deterministic operating system (OS) solutions that can be deployed as either a standalone or distributed RTOS in support of applications that run on multiple nodes. It can even be implemented as a virtualized real-time companion OS to Windows or Linux hosts.

INtime abstracts the complexity of TSN network configuration through a suite of developer APIs. The software supports a variety of communications protocols that eliminate the need to understand different traffic classes and how they’re scheduled on the network. Plus, the INtime SDK provides developers with tools such as a timing analyzer that can be used to further optimize time-critical applications.

“TenAsys is taking care of the ‘how’ under the hood so developers can focus on the ‘what’ and the ‘when’ as they’re developing these applications,” Morrissette says.

INtime’s native support for TCC features and its API abstraction of underlying TSN networking capabilities are the key to unlocking the true value of IOT in time-critical industrial applications. Utilizing the native hardware virtualization features of multicore Intel processors, an instance of INtime can be allocated to a dedicated CPU core and run within a full-featured virtualized hardware environment with allocated memory, I/O, and other system resources. Applications built and deployed on the INtime platform can then be deployed in a distributed real-time OS (DRTOS) environment. This enables portability and flexibility for industrial IOT real-time applications delivering time-critical data capture, analysis, and decision-making at the edge.

Achieving a True IT/OT Convergence Strategy

Time-sensitive networking technology can unify IT and OT systems to deliver industrial IoT network interoperability and workload portability. With over 10 years of experience in the TSN space and decades as a provider of RTOS technology, TenAsys is uniquely positioned to deliver the technology convergence required to accelerate broad TSN adoption for industrial IOT.

By integrating and abstracting TSN and Intel TCC technologies, INtime can provide developers the tools to manage the complexity of configuring, deploying, and managing converged IT/OT time-sensitive networks. This will pivot the industrial digital transformation from data to information—a key element for delivering the results that will accelerate adoption and amplify the value of IOT at the industrial edge.

 

This article was edited by Teresa Meek, Contributor for insight.tech.

No-Code Software Scales Vision AI Deployments at the Edge

Posted on by Micah Kaplan

Reinventing the wheel every time you embark on a new project is frustrating; your enthusiasm quickly begins to wane. Unfortunately, this problem plagues development of vision AI solutions for the edge, leading to stop-and-go approaches and sporadic implementations of the technology.

Dimitris Kastaniotis, Head of Product at Irida Labs, a computer vision and AI solutions software company, says one-off successes might be proof of operational efficiencies that edge vision AI can deliver, but the technology has not scaled well for mass deployment.

Irida Labs has a solution to this problem. The company’s PerCV.ai software helps edge vision AI deployments scale by keeping operational costs low and creating and using viable data. It also delivers infrastructure generic enough to work with data from the field and recalibrate on actual installation conditions.

Before AI models can hit the ground running, they need information. PerCV.ai has a data engine that attends to pre- and post-processing of data and creates, annotates, and manages it. The engine works with a cocktail of proprietary and synthetic data so projects can hit the ground running, instead of waiting months upon months to get one-off points from the field.

For further ease of deployment, PerCV.ai is a no-code solution that can be pushed directly inside an edge device. A central platform makes changing the functionality or recalibrating edge cameras a breeze. Equally important, hosting cameras and analyzing data at the edge avoids steep cloud computing costs. Using PerCV.ai helps validate business use cases quickly so companies can then deploy the projects at needed scale. And Intel technology, including the Intel® Movidius™ Myriad™ VPU, has speeded up prototyping and product development, Kastaniotis says.

Uses of edge vision #AI and PerCV.ai are practically limitless, including in #Industry40, the #manufacturing industry’s version of #DigitalTransformation. @IRIDALabs via @insightdottech

Implementations of Vision AI

Uses of edge vision AI and PerCV.ai are practically limitless, including in Industry 4.0, the manufacturing industry’s version of digital transformation.

While Industry 4.0 is a multi-pronged term applicable to a variety of operations and subsectors, Irida Labs works to implement its driving principle of AI-based automation in logistics and warehouse management. Among the primary challenges that warehousing and logistics face is finding exactly what is where at any given time. Loading operations are not automated, either. “Many operations in the warehouse could benefit from the installation of cameras and edge vision AI,” Kastaniotis says.

Take, for example, an automated guided vehicle (AGV) that loops around a warehouse picking up goods. Too often the AGV goes on a wasted errand, looking for products that are not on the shelves, decreasing productivity. PerCV.ai solves this problem through cameras installed on shelves taking accurate product inventory and integrating this information into PLC servers on the AGV. This way the AGV goes hunting only if it is told the product is actually in the location.

Such a solution is just one building block of many for an autonomous warehouse or factory, Kastaniotis says.

The PerCV.ai solution has also helped companies enforce access zones in warehouses through identification of uniforms, which becomes especially important in large-scale facilities that employ a mix of in-house workers and contractors. Using cameras and real-time alerts, warehouse management can tell when workers are trying to access areas they should not.

These two use cases are just a sample of the many ways in which the Irida platform can deliver edge vision AI. Monitoring liquid flow is another implementation. In all instances, “you have the same backbone and the same infrastructure, but real-time processing needs are vastly different, so we just approach them in the same structured way through the same platform infrastructure,” Kastaniotis points out.

Irida Labs strictly adheres to privacy laws and does not work on face recognition. Personal identifying information is not stored at the edge but used only for analytics. Irida also does not use training data from one company for another’s AI models.

Working with Systems Integrators

While Irida might help speed product development, it does not deliver complete bespoke solutions.

Instead, it helps ensure viability of approaches so customers can complete that last mile. Systems integrators are especially effective at picking up the baton and customizing solutions for their clients. SIs use PerCV.ai to test-drive the viability of projects. The software allows SIs to calibrate the solution for field-specific data and push it out directly with minimal- to no-code processes.

“SIs need one more weapon in their arsenal to start generating more revenue for themselves and for the rest of the parties involved by providing better service,” Kastaniotis says. And the sales-based model for PerCV.ai delivers just that: a quick and scalable way to generate new revenue streams with edge vision AI projects.

While leveraging edge vision AI for more sales, it also helps to understand the landscape and know the technology’s limitations. First, companies need to understand what data sets they have so they can fill any gaps with synthetic data. The technology also has performance constraints so companies must consider tradeoffs between accuracy and power consumption. Finally, using vision to understand your environment takes a bit of work. “You need to have an understanding from beginning to end of what you’re trying to do,” Kastaniotis says. “You need infrastructure that can connect these dots. If not, it’s very difficult to reach a solution and to simplify your life.”

We have just begun to scratch the surface for edge vision AI, so Kastaniotis is excited about its future and predicts the number of tasks that can be automated is going to increase significantly. Being able to detect falls in patients or drowsiness while driving are two very tangible implementations.

And edge vision AI, combined with no-code software, is making the future of autonomous operations close at hand.

 

Edited by Georganne Benesch, Editorial Director for insight.tech.

Exploring the Next Generation of Artificial Intelligence: With Intel

Posted on by Micah Kaplan

AI is rapidly evolving every day, and with it are new tools and capabilities designed to help businesses keep up with the pace of change. This was more evident than ever at the recent Intel® Innovation 2023 event, where companies showcased their AI innovations, and new solutions were announced to make it easier for developers to start solving real-world problems.

In this podcast, we explore the most significant AI innovations, trends, and opportunities for developers, as well as the impact AI has on the world and the technology making it all happen.

Listen Here

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Our Guest: Intel

Our guest this episode is Paula Ramos, AI Evangelist at Intel. Paula’s PhD in Computer Vision and Machine Vision is just the foundation for her experience in AI and technology. Prior to Intel, she worked as a researcher in applied engineering and led multiple teams designing, building, and deploying AI at the edge. Much of her career was spent helping bring technology to the agricultural industry. At Intel, she works as a computer vision and AI advocate bridging the gap between technology and developers.

Podcast Topics

Paula answers our questions about:

  • (1:54) Advancing AI and its role in real-world problem-solving
  • (4:05) Intel’s role in making AI easier and more accessible to developers
  • (6:53) The biggest announcements from Intel® Innovation 2023
  • (10:46) OpenVINO™ and its impact on the Intel partner ecosystem
  • (14:46) How developers can take advantage of the new SDK for Intel® Geti™
  • (18:22) Empowering women in AI
  • (22:30) The future of AI development and tips for new developers

Related Content

To learn more about AI trends, read Evangelizing AI: The Key to Accelerating Developers’ Success and listen to Personalized AI Shopping Experiences: With FIT:MATCH. For the latest innovations from Intel, follow it on Twitter @IntelIoT and on LinkedIn at Intel Internet of Things.

Transcript

Christina Cardoza: Hello, and welcome to the IoT Chat, where we explore the latest developments in the Internet of Things. I’m your host, Christina Cardoza, Editorial Director of insight.tech, and today we’re going to be talking about the next generation of AI development with Paula Ramos from Intel. But before we get started, let’s get to know Paula. Hi, Paula. Thanks for joining us.

Paula Ramos: Hi, Christina. Thanks for having me here. I’m so excited with this conversation.

Christina Cardoza: Yeah, absolutely. What can you tell us about yourself and what you do at Intel?

Paula Ramos: As you mentioned, my name is Paula Ramos. I am an AI Evangelist at Intel. I made my PhD in Computer Vision and Machine Learning some years ago, but before Intel I was a researcher in applied engineering. I was the tech leader of multiple teams designing, building, and deploying AI technology at the edge. And I have more than 17 years of experience bridging the gap between technology and agriculture. So now in Intel I am a computer vision and AI advocate, and with my knowledge I can also bridge the gap between the technology and developers.

Christina Cardoza: Awesome. Well, I’m very excited to get into the conversation with you today. You know, we’ve done a lot of work outside of the podcast together, so I know you have just a wealth of information in this area. And obviously a AI development, that’s a big general area that we’re talking about, but I wanted to start—the last time we spoke and last time we saw you was at Intel Innovation a couple weeks ago, so I wanted to start there. There was a lot that came out of different companies and different industries, so what were you seeing at the event, and even outside of the event, on how AI is advancing and solving these real-world problems?

Paula Ramos: That is a great question, Christina. Because AI is advancing fast. We can see new things coming every single day, and we can see also real-world problems turning into amazing solutions with AI. So AI has impacted the world for a while; now there is more awareness for AI.

So AI, for example, has helped people to communicate with others using translations. AI can translate text between 100 languages to others. Another great example is a self-driving-car system that some vehicle brands are using to control the vehicle steering, acceleration, and braking, with the potential to reduce fatalities in traffic accidents. AI also can help doctors to diagnose cancer and develop personalized treatment plans, or accelerate the deployment of new drugs and treatments based on the capability that AI must predict the 3D structure of the proteins. AI is also helping a lot of farmers to reduce the use of pesticides and herbicides by up to 90%. So AI is helping humanity to solve their problems faster, making the human race more feasible.

Christina Cardoza: Yeah. It’s amazing to see AI advancing and evolving in all of these different industries. And like you said: it’s changing every day. And to make some of these capabilities —actually to make all of these capabilities possible, you really need developers building these solutions, staying on top of the next generation. And not only is AI in different industries evolving every day, but so are the capabilities, solutions, technologies to make it easier and more accessible for developers. It used to be the case where AI developers had a very specialized skill set. Now all developers are expected to have AI development skills, and the tools are making it easier for them to do so; it’s making them more accessible.

So I wanted to see what you thought about the importance of making AI more accessible for developers. What you’re seeing in this space and how developers can really leverage this transformation.

Paula Ramos: Christina, this is a great question, because this resonates a lot with the role that we have as AI evangelists at Intel. You know, we are trying to create more accessible information to developers and how they can accelerate the speed of AI innovation. So basically for that specific question I have three thoughts.

So, the first thing is just recapping what we are talking about—making  AI easier and more accessible for developers. So the first thing is to accelerate the speed of AI innovation. You know, this is super important, because the more developers who have access to AI tools, the faster the technology will advance. By making AI more accessible we can open up the field of new ideas and lead the deployment of new innovative solutions. Basically, imagine all the things that they can make right now.

So, the second point is to democratize AI. We need to be sure that AI is for everybody, and every single developer has the opportunity to benefit from this technology. By making AI more accessible we can help to bridge the gap—this adoption gap.

And the third one, but is not the less important, is that we need to solve the AI talent shortage. So, there are right now—and this is one of the top jobs that we can find—there is high demand for AI developers, and there are not enough developers in the world. There is a shortage of skilled workers to meet the demand. So making AI easier to learn and use we can help to train more developers and close this talent gap.

You know, developers should have the proper AI tools, but also access to the latest hardware improvement is important. So this is another tool, because this enables developers to build and deploy applications more efficiently and effectively.

Christina Cardoza: Yeah, absolutely. And, like you mentioned, Intel is making a lot of progress in this space to make it possible to democratize AI and give them the tools and the capabilities that they need. Like I mentioned when we caught up at Intel Innovation a few weeks ago, Intel has made a lot of these announcements solving some of these challenges or issues that we’re talking about.

So can you talk about some of the latest advancements or announcements—what’s going on at Intel exactly. What are the tools and the hardware and capabilities you guys have coming out to address some of these developer concerns?

Paula Ramos: I have a lot of fun at Innovation. That was an amazing event. We have two days full of new and exciting things coming from Intel, something that is coming in also in the next months. So it was great for me to see, for example, how startups are using silicon power with the capability of AI to solve real-world problems.

Personally, I’m so excited with the Intel announcement of the new AI PC. So, I had one of those in my hands for showing our generative-AI booth, and it showed a great performance. So, basically that new laptop or processor is a new generation; it is the Intel® Core™ Ultra processor with GPU incorporated, and also the process of a new element called NPU, Neural Process Unit.

And it’s also good to see how OpenVINO™ and the inference—you know what OpenVINO is? But maybe listeners need to be more familiar with OpenVINO. So, OpenVINO is the inference and deployment framework that Intel has. And it also has the capability to run OpenVINO in the AI PC. It is really, really good. One of the things that I also realized during the keynote of Pat Gelsinger was that OpenVINO increased downloads in the past year 90%. So it is showing us the potential we have at Intel to leverage the AI era.

A lot of people are thinking that Intel is just a hardware company, but we are making a great job showing developers how they can easily improve their solutions using frameworks or systems such as OpenVINO. And Pat Gelsinger and his team made a great job, an excellent job, on stage. So, we saw Llama 2 chatbot, an LLM model, running on an AI PC, locally in a Windows machine. He did run generative-AI chatbots locally, instead of sending that data out to the cloud. It is more secure if we allow users to utilize AI without an internet connection, for sure. We have a lot of security reasons to do that.

And another thing that also was fun to me was using also generative AI in the keynote when Pat and his team were able to generate a song in the style of Taylor Swift. So it seems that Pat is a Swiftie.

Christina Cardoza: Yeah. And just looking at OpenVINO and the, just the awareness and how it was brought to the forefront at Intel Innovation really highlights how important AI has come to be to all industries. OpenVINO is an AI toolkit; I believe it just celebrated its fifth anniversary, but a couple of years ago at Innovation we weren’t hearing much about OpenVINO, and now it’s everywhere. Everybody’s using it, and, like you said in the keynote, we saw different examples of how OpenVINO is being used—like in the fitting room experience with FIT:MATCH and things like that.

You mentioned generative AI. I know OpenVINO is keeping on top of all the trends. Obviously generative AI is a hot topic these days, and OpenVINO came out with its latest release with generative-AI capabilities. So, how are you seeing—what’s the best way for the listeners who haven’t dabbled in OpenVINO yet, or for ones that want to take their AI-development efforts even further, how are you seeing them use OpenVINO? What’s the role of OpenVINO in their AI-development efforts, and what are just some other interesting use cases you see partners in the ecosystem leveraging this toolkit?

Paula Ramos: So I think OpenVINO, as I mentioned before and also you mentioned—that is the inference and deployment toolkit that Intel provides to developers on client and edge platforms—with OpenVINO Intel is making AI more accessible. So you can optimize neural network inference across multiple hardware platforms, and OpenVINO is powering AI at the edge.

An evidence of that is what I mentioned before, that we can see that the developer downloads have increased in 90% in the past year. We can see that OpenVINO makes generative AI more accessible. We are solving the real pain points to developers. We are working—the main goal of OpenVINO is to run the optimization and quantization with the models so we can reduce the size of the models, we can reduce the memory footprint, we can also run the models faster in our wide range of hardware. I’m talking about Intel and non-Intel hardware.

And the most important thing is that once you have the model in the intermediate representation format—that is the OpenVINO format—you can deploy it everywhere. And this is some of the differences that also we have with some of the competitors. So we can see successful stories in use cases with the adoption of OpenVINO.

So we can see that we are hosting every single industry. And this is just to give you an idea, an example: the smart—and I know that you know pretty well, but for listeners, OpenVINO is everywhere: in smart cities, manufacturing, retail, healthcare, and also agriculture. And, as I mentioned, this is just to give you an example.

For the new listeners or the new people that are in this field of AI, I invite you to google OpenVINO use cases, and you can see a lot of great examples. And also we have a great way to start if you want to do that: we have created the AI reference kits, and you can find that if you put, like, “Open Potential OpenVINO” and you can find that in Google.

Christina Cardoza: Yeah, that’s great. You know, obviously OpenVINO is, just like you said, in everything. There’s so much to learn about it, and there’s so much you can do with it. But OpenVINO isn’t the only sort of software tool kit that you guys have out there or is available to the developers. So I want to get into Intel® Geti™ a little bit.

Last year at Intel Open—Intel Innovation, you guys announced Intel Geti, which is designed, like you said in the beginning, to democratize AI not only for developers, but for business domain users. And I believe that it connects with OpenVINO to really connect business users and developers together. So this year it was great to see how much that Geti had matured over the last year. And this year at Intel Innovation we learned that there was a new software development kit for developers to start working with and start leveraging this solution even further.

So can you tell us a little bit more about Geti—how it’s going to be probably another three-part question, but how Geti works with OpenVINO and what developers can use with the SDK, how developers can leverage it?

Paula Ramos: Yes, yes, yes, for sure. I really want to make first an introduction about what Intel Geti is. So maybe listeners they don’t—are not familiar with that. So, Intel Geti platform is a computer vision platform that helps organizations to rapidly develop computer vision models. So, in short words, it’s a platform that brings all necessary things together. So we have annotation, training, optimization, testing.

There are a lot of benefits for using the Intel Geti platform: data scientists, machine learning professionals, systems integrators, and domain experts can work together using the same platform. This is because Intel Geti is an easy-to-use platform that also has the potential to control multiple aspects of the training and optimization process. And as, Christina, you mentioned that OpenVINO is behind scenes of Intel Geti platform for the optimization and quantization task, but also the platform can provide us modeling different formats. And one of these formats is the intermediate representation format OpenVINO. And I can deploy my model everywhere and have all benefits of the deployment with OpenVINO.

In another way, Intel Geti platform also offers a software development kit that is the SDK that helps users to take advantage of easy-to-use functionalities. So the Intel Geti SDK utilizes OpenVINO to build deployment pipelines and accelerate inference on various Intel hardware platforms that include CPUs, GPUs, and without needing to be an expert in computer vision. That is also the beauty of this platform.

With the SDK we can have real interaction with the project in the Intel Geti platform. So we can create projects, upload your annotation, upload new production data or previous data, and you can modify the trainable features, test the deployment running in the server for the testing purposes, and also download your deployment for running that locally.

The deployment with the Intel Geti SDK makes this super easy for developers since the SDK is agnostic to the computer vision task and also agnostic to the model architecture. So developers don’t need to prepare the data to the model input and don’t need to prepare the model output for showing the results. This is straightforward how we can run the inference using the Intel Geti SDK locally. So we have the advantage to use also SDK with the OpenVINO model server. That means that we can also scale the capabilities of our models in different deployments. I’m so excited with Intel Geti.

Christina Cardoza: Yeah, no, absolutely. With Intel Geti OpenVINO and all of the improvements in the Intel hardware that are coming out, you guys have really created an end-to-end solution not only for developers for businesses to make all of this happen and make it this next-generation of AI solutions and use cases possible.

Now, we’ve been talking about making it accessible and democratizing AI for developers mostly in a general sense. I want to dig down a little bit further in a specific area that you have done a lot of work in, and that’s empowering women to get into the AI field. And you’ve done a lot of work in this, and I’ve seen interviews that you’ve had about this topic.

So I’m curious, why are you so passionate about this initiative, and can you tell us anything about how we can get women more involved—why it’s important to, and what are some of the challenges or the barriers that they face getting into the AI space?

Paula Ramos: Yes, for sure. I’m so passionate with this topic. You know, personally I think I represent a global tech workforce of two minorities. The first minority is women in tech or in AI, and the second is Latin women in tech. We can interpret “tech” as also artificial intelligence or engineer in general. But just take a look at this statistic, and you can see also why I can see this is important—just that 50% of the global tech workforce are women and just 2% are Latin women. So this is a huge underrepresentation.

Basically, under that scenario I want to inspire more women in the world to work in AI. And I want to contribute to reduce the lack of the access to education and training, because we need to be clear that it’s also coming because we have a lack in education in Latin countries. In South America we have a lack in education, so we need to work more on that. Or maybe women are not super familiar from the very beginning in the education with technology. So we need to include more girls in STEM courses and all.

I also want to reduce discrimination and bias. You know, everyone deserves the opportunity to success in tech regardless of the gender. I think that this is a stereotype that we have in our minds. Women can also sit at these tables and have a serious discussions about technology. Women bring a unique perspective about how to solve problems. And I can see that this is a great point: that we have the unique skill to create products and services that meet the needs of all users. That doesn’t mean that the men don’t have that—for sure, they also have that, but women have that specific skill, you know, because we are moms, so we are designed to solve problems, these kind of problems.

And we can also see—and this is just an example that I have in my mind, on the top of my mind—is we have significant contributions to the field of AI. And just to give you an example, I want to talk about Dr. Fei-Fei Li. I don’t know if you’re familiar with her, but she is an AI researcher and Co-Founder of the Stanford Human-Centered AI Institute. And because of her work we started the work in deep learning. She contributed to the birth of deep learning; she developed the ImageNet initiative, and that initiative played a major role in the deployment of deep learning.

You know, this is the impact that one woman has made in AI, and this is remarkable. I can imagine how many ideas, how many women can contribute also to the field. I’m so excited, I’m so passionate with this, and I really want to inspire more women in this field.

Christina Cardoza: Absolutely. And it’s great to see women being recognized for their work in this field. You mentioned Fei-Fei: she accepted—got the Intel Innovation Award at the event earlier in October. So it’s great to see all this progress being made already in this space. And you made a great point: it’s not only about making tools and capabilities and technologies available to developers, but it’s really the education and the resource aspect—making those available so that more people can get in the field and we can make this really accessible to everybody, not just people that are already in the field. So I think that’s great.

Unfortunately, we are running a little bit out of time, but I wanted to throw it back to one last time before we go if there’s anything you wanted to add about the future of AI development, how developers can get started, and where you think this space is going.

Paula Ramos: This is a great thing, this is an important message that maybe I want to share with developers. The first question is, where are your dreams? And you can achieve those goals, because AI is a powerful tool that has the potential to make the world a better place for everyone. And we need to build an AI that is inclusive, fair, and beneficial to all.

So, try new technologies, new models and algorithms. You can use OpenVINO, why not? In my personal experience it will help you to achieve your professional and personal goals regarding AI, for sure. So try to participate and be an active contributor in an open-source project, and stay tuned for the latest trends in AI to make AI more practical. This is my other advice. AI has a lot of tools, the engine is in your imagination. That’s all, Christina. I’m glad that you invited me. That was super fun, and I hope that listeners can find this also helpful for their career in AI in general. Thank you, Christina.

Christina Cardoza: Absolutely. Thanks for joining us. It’s been a very informative and insightful conversation, and I can’t wait to see what else Intel does in this space. You know, you guys are making improvements every day, and every day we’re publishing articles on insight.tech showcasing exactly how AI is changing and transforming the world in different industries, and Intel technologies are all powered behind it.

So I would invite all of our listeners to take a look at insight.tech to see how other industries are leveraging Intel and AI, as well as keep up to date on Intel. Visit their website and some of their platforms that they have to see what else you can do. I know Intel has a lot of reference kits and, Paula, you’ve done a lot of different tutorials and videos on intel.com also, walking developers through some of these steps and capabilities. What is the link or the website how developers can get to that and learn a little bit more about what to do with the development kits, with AI experts like yourself?

Paula Ramos: Yes. You can find that if you put in Google, “Open Potential Intel OpenVINO.” You can find the link, or also we can share the link maybe in the description of this podcast and you kind of start from scratch. So, if you are not familiar with AI, also you can start from scratch developing different kinds of solutions for smart manufacturing, retail, and more. So, more things are coming to that space. We are trying to create tutorials, we are trying also to create mindful messages that you can apply in your career or in your actual positions. Stay tuned, because we have more things coming for 2024.

Christina Cardoza: Absolutely. Well, I’m excited to see what else comes out over the next year. But until then, thank you again for joining us, and thanks to our listeners for tuning in. Until next time, this has been the IoT Chat.

The preceding transcript is provided to ensure accessibility and is intended to accurately capture an informal conversation. The transcript may contain improper uses of trademarked terms and as such should not be used for any other purposes. For more information, please see the Intel® trademark information.

This transcript was edited by Erin Noble, copy editor.

AI and Personalized Shopping Experiences Are the Perfect Match

Posted on by Micah Kaplan

There are people who love to shop for clothes and people who just don’t. And even the devotees can get drained from the fitting-room aspect of shopping on occasion. Thought you were a size 6? Maybe in one brand or style you are, but in another you aren’t. And with limits to how many items you can bring in with you, this can get exhausting quickly. Retailers too can find the hunt for the right size a real headache: in wasted salesclerk time, those cluttered dressing rooms, and—worst of all—the dreaded returns.

That’s why companies are creating cutting-edge AI retail solutions for a more enhanced and much more personalized shopping experience, and one of them was featured at this year’s Intel® Innovation 2023 conference. Hillary Littleton, Head of Marketing at the AI-based retail solutions provider FIT:MATCH, joins us to talk about the AI-enhanced shopping experience and the benefits it holds out for shoppers and for retailers. Because there may be no one-size-fits-all, but AI might just be able to reveal the one size that fits you (Video 1).

Video 1. FIT:MATCH’s Hillary Littleton discusses the innovative 3D technology and AI driving the retail solutions that are making the shopping experience better for customers and retailers alike.

What is FIT:MATCH? And how does it work to create personalized recommendations for shoppers?

Earlier this year, FIT:MATCH debuted its newest in-store fitting-room experience for apparel retailers, called Fit Concierge. It gives shoppers the opportunity to be scanned in an in-store fitting room using Intel® RealSense™ LiDAR technology and Intel OpenVINO™. Using those LiDAR sensors, we create a scan in just one second, and then that data is matched back to an avatar in our extensive database that has already tried on the garments.

After their scans, the appropriate sizes just appear for shoppers, which is different from what you see in other fit tech in the industry. The entire in-store process takes 10 to 15 seconds, and the shopper gets their exact size on the spot across the retailer’s entire assortment. We can tell them not just what size they are, but also why that’s the right size for them and what they should do with that information going forward.

The process takes all the equating between scan data and brand sizes off the shoppers’ hands—and also off the brands themselves. And we don’t ask shoppers for their measurements—most people don’t know how to take their measurements correctly—we use a 3D scan, because we know that a 3D problem can be solved only by a 3D solution.

Fit preference is also something built into our technology, and we’re learning more as more consumers tell us how they like things to fit—tight or baggy or however—and then we can give back recommendations based on those preferences. The shopper can even see the item on a 3D model. So, on top of being really easy and fun, shoppers are getting this portal into data about themselves. And we’re finding that they absolutely love that. The first retailer to incorporate our concierge solution was Rihanna’s Savage X Fenty.

“#AI is really at the core of our platform. It powers our ability to interpret and leverage the #3D-shape information captured using the Intel sensors” — Hillary Littleton, @FitMatchAI via @insightdottech

What are common challenges that FIT:MATCH can help retailers solve?

There are three specific challenges that I hear about continuously from retailers. Number one is customer retention, along with drop-off rates when customers don’t know what size to buy, or their size is sold out. That results in higher churn rate, lack of loyalty, and just an unsatisfied shopper. Number two is leftover inventory due to poor buying, planning, or merchandising decisions on the part of the business. And then number three: returns.

Retailers crave products that are seamless to integrate but also lead them to achieve important KPIs for their businesses. What we learned from the Intel Innovation conference is that the need for the technology spans all sorts of customer demographics; it’s really a universal problem. Everyone knows that AI solutions are a hot commodity right now, but I think gaining access to the right solutions is the difficult part. Our tech is revolutionary and immersive for shoppers, but it’s impacting our brand partners’ bottom lines in a big way as well.

With the FIT:MATCH technology, retailers can better service their customers. That’s the beauty of it: They know what the shopper really wants and what is going to fit them, so they’re able to offer an elevated shopping experience. Then the consumer is more satisfied, which then reflects well on the brand.

What are the benefits of providing such an innovative and customized fitting experience?

We’ve seen incredible benefits for our brand partners, including an average 6x conversion rate for those that scan with FIT:MATCH versus those that aren’t, and 20% to 30% higher average order values. And those that scan are returning 80% less merchandise than those that aren’t. Also—this is a big one—fewer than 1% of consumers buy more than one size: “bracket shopping,” as it’s called in the retail space. There’s a lot of fit risk, particularly online, and retailers tell us that bracket shopping is the number-one concern they have, so it’s great to see that it’s now below 1%.

When it comes to loyalty, there’s a 2x sign-up rate to be part of a loyalty program for those shoppers who have scanned versus those who haven’t. And overall customer satisfaction has increased by 16 points on average. We’re really proud of those results.

There are also things that we can build out with brand partners going forward. That includes more insight into their consumers, with a data dashboard that we can customize and serve up to brand partners according to their preferences. That way they can make more personalized marketing and merchandising decisions and foster long-term loyalty. And that can help with product construction and with inventory management. Just getting rid of excess inventory is a huge pain point, we’ve heard. So we’re excited to tackle that as well.

What technology drives creation of the 3D model and personalized recommendations?

We’re leaning into the effects of how AI can optimize the shopping experience. Tools like this, integrated with a seamless checkout experience on e-commerce, are crucial elements for the consumer journey.

And AI is really at the core of our platform. It powers our ability to interpret and leverage the 3D-shape information captured using the Intel sensors. Intel edge computing has been so instrumental in the way we scale, and it really enhances the user experience. It’s private, it’s quick, but it’s also more cost-effective. And the OpenVINO technology really stands out as a prime example of that. We see immense value in it, and we’re dedicated to integrating it into more of our product offerings going forward.

What’s next for FIT:MATCH?

We’re rolling out the next iteration of the Fit Concierge at a popular shopping center in Los Angeles this holiday season. This new version is faster and even more accurate, with extra layers of privacy. We’re also partnering with a multibillion-dollar apparel and footwear brand in the sportswear space. And the entire experience will be accelerated by the Intel suite of products.

Our future plans are definitely focused on bringing everyone the ability to scan using their own mobile phones. With one scan, shoppers will be able to unlock a passport of sorts that will offer up recommendations in their sizes across brands. So no matter if they scan in-store or at home, their personalized shape profile will be accessible from anywhere.

We have also recently expanded into the healthcare and wellness sector, launching a scanning experience exclusively built for plastic surgeons and their patients who are going through body transformations. We’re super excited to see how our shape-matching technology can impact other use cases outside of fashion retail.

Related Content

To learn more about personalized AI shopping experiences, listen to our podcast Personalized AI Shopping Experiences: With FIT:MATCH and read Phygital Experiences Help Fashion Retail Shine. For the latest innovations from FIT:MATCH, follow them on Twitter at FIT:MATCH.ai and LinkedIn at FIT:MATCH.ai.

 

This article was edited by Erin Noble, copy editor.

IoT Brings Plug-and-Play to Smart Building Solution

Posted on by Micah Kaplan

Today’s building management systems (BMS) don’t just improve energy utilization in office buildings—they can also help industrial tenants gain control over their complex infrastructure to operate more efficiently and sustainably.

Industrial users have different, more complicated needs than office users. For instance, cold chain storage facilities, automated packaging operations, and distribution centers all contain specialized equipment with unique energy requirements. Managing these valuable appliances and instruments requires greater vigilance than adjusting the lights and thermostats in a typical office building. For these businesses, gaining the ability to see and control their HVAC, power, and lighting systems—from anywhere, at all times—is critical to operational success.

Modern BMS applications can do that, but it becomes complicated when multiple industrial tenants occupy the same building. It gets even trickier when those tenants occupy varying amounts of space within a facility from one month to the next.

The need for industrial BMS is becoming more pointed as businesses demand better control over their environments and sustainability initiatives like the Building Research Establishment Environmental Assessment Methodology (BREEAM) standards gain traction. Modern building automation solutions using open-source software can help, drawing on a large community of experts to tweak technologies so that they meet the unique requirements of highly specialized users. Building owners who can provide users discrete control over their energy estates stand to gain market share among desirable industrial tenants.

Modern building #automation solutions using open-source #software can help, drawing on a large community of experts to tweak #technologies so that they meet the unique requirements of highly specialized users. @TridiumInc via @insightdottech

Looking Under the Hood of Next-Gen Industrial Spaces

HelloParks, an Eastern European industrial real estate development company that operates four industrial parks with 380,000 square meters of building space, illustrates the complexities of energy management for multiple tenants. The buildings accommodate many heavy industrial use cases, from manufacturing to warehousing to distribution. As a result, the structures must be flexible in the utilities they provide and the services they support. And because HelloParks provides flexible leases, the company must be prepared to accommodate new tenants every few weeks, even though their BMS requirements are completely different from those of previous users occupying the same space.

That means HelloParks must equip its facilities with a sophisticated BMS allowing tenants to visualize and control all manner of building automation systems (BAS). The BMS must also be able to support many different types of infrastructure and use cases. To accomplish these goals, HelloParks worked with a local systems integrator to implement a solution.

The team selected the Tridium Niagara Framework®, a software automation solution developed by US-based automation provider Tridium, Inc. Niagara simplifies the integration of BAS like HVAC, lighting, power, and security with back-end enterprise applications, allowing users to analyze and act upon operational data using customizable visualization dashboards.

Niagara natively supports more than 250 protocols to streamline data ingestion and management for different types of BAS devices from a large number of manufacturers. The open-source solution gives manufacturing partners access to a community of more than 20,000 engineers who can develop protocols, templates, drivers, and other technologies that extend the platform for specific needs, says Tridium Senior Sales Manager Irek Pacula.

Once operational BAS data has been captured, Niagara users can view and manage infrastructure through a web-based portal providing insight into operational data flows. In the case of HelloParks, this multi-tenant portal makes data accessible to individual users without exposing the data of others. That gives the industrial real estate operator the flexibility to support a wide range of ever-changing BAS equipment and multiple environments under a single, unified BMS.

The Niagara platform also includes a flexible control engine containing a variety of predefined algorithms, as well as building blocks for creating new ones that even non-domain experts can understand. These algorithms can create custom logic sequences for functions like fault detection and diagnostics, data-based alarming, and other features empowering tenants like those of HelloParks to take control of their facilities. The data, the control engine, and resulting BAS reports can all be tailored to specific use cases via customizable dashboards.

Performance and Power Efficiency for Smart Building Solutions

While data insights can be viewed in the cloud, the action is happening at the edge. Niagara can be deployed as an agent on edge controllers like the Tridium JACE®, a rugged, compact, and easy-to-install hardware platform. Systems like this serve as primary protocol conversion gateways for communicating data and commands between BAS endpoints and the Niagara software.

When deeper insights are required or large facilities need to be managed—as with HelloParks—performance needs to scale efficiently. Tridium and its system integration partner helped HelloParks accomplish this with Intel® Core™ and Intel® Xeon® processor-based edge servers, which contain built-in features like processor virtualization to enabling scaling while ensuring data privacy and security.

“Going from one core to multicore brings so much benefit,” Pacula says. “Some customers just want a small but powerful installation running in a cabinet. Some have hyperscaler installations running on multiple different machines using Intel® Xeon® processors. To our software, it looks like a single large machine, but it is double-redundant and capable of supporting thousands of users and buildings.”

Full-Service Building Automation Through a Single Pane of Glass

The Tridium Niagara Framework allows HelloParks to navigate the complex dynamics of multi-tenant spaces by supporting ubiquitous connectivity, adaptable logic, customizable visualization, and scalable deployment solutions. With Niagara insights available to both HelloParks and its tenants, there are multiple stakeholders and a large set of “eyes” on resource utilization. Several of the company’s buildings have achieved a BREEAM rating of “outstanding,” a distinction attained by only 3% of buildings worldwide.

Still more is on the horizon for the intelligent BMS, as its extreme versatility can also incorporate business data. Today, HelloParks tenants pay a price per square meter, but tomorrow they will have the opportunity to tie billing and invoicing systems into their dashboards, enabling each tenant to pay for their specific utility consumption. Additional information, such as price per kWh, could enable the Niagara control engine to cycle resource utilization based on predefined cost thresholds.

With their ability to improve energy efficiency, increase sustainability, potentially reduce costs, and allow specialized tenants to manage everything through a single pane of glass, smart building solutions are ready to move beyond their traditional home in commercial office buildings to more complex environments. In fact, they already have.

 

This article was edited by Teresa Meek, Contributor for insight.tech.

Industrial Automation Fuels Evolution in Tech Distribution

Posted on by Micah Kaplan

As industrial automation progresses, manufacturers are becoming more agile by placing compute and analytics at the edge, where data is created. This requires new applications, hardware, and expertise to connect everything—from sensors to industrial PCs (IPCs), to on-premises servers, and to data centers in the cloud.

Ultimately, the goal is to automate as much of the manufacturing process as possible so plants can run 24/7 with minimal human interference. It’s a gradual process. Currently, manufacturers focus on building functionality at the edge. It’s another step in the continuum of industrial automation and IT/OT convergence to drive flexibility, operational efficiency, safety improvements, and cost reduction.

Technologies such as AI, computer vision, and performant edge compute enable use cases such as real-time defect detection and quality control, employee safety monitoring, inventory tracking, and predictive machine maintenance. And they enable flexibility so manufacturers can make rapid changes. For example, a production line generating thousands of units of a single product can quickly be switched to a custom order, and then back again.

“Being more agile on the factory floor certainly requires lots of processing power, and a lot of flexibility in the way you manage production,” says Ulrich Schmidt, Segment Director High End Processing at EBV Elektronik, an Avnet company.

As the IIoT becomes mainstream, electronic distributors of and hardware components must evolve with it. And EBV is moving forward to play a pivotal role in industrial automation—providing expertise and consulting services to the OEMs, machine builders, and solutions integrators that deliver industrial systems to manufacturers.

#EBV today serves as an extension of its embedded suppliers, adding value along the #SupplyChain by delivering not just industrial #hardware but also expertise. @EBVElektronik via @insightdottech

Industrial Automation: From Components to Solutions

EBV today serves as an extension of its embedded suppliers, adding value along the supply chain by delivering not just industrial hardware but also expertise. On top of its traditional services such as the logistics of sourcing products and delivering them to its assembly and integration partners, the company employs a full team of experts, including field application engineers (FAEs), who take part in designing and assembling solutions.

“We were known as a typical component distributor. But over the course of time, we’re at a point where we don’t just deliver the bare components for hardware design, but also modules and industrial PCs—complete processing systems that we can sell through our channel,” says Schmidt. “We act as the extended arm for our suppliers and a consultant to our customer base. We have to have experts in-house to give them valuable guidance.”

With that comes a stronger emphasis on software. Modern manufacturing systems must increasingly be controlled by open-standards software, as opposed to running solely on proprietary controllers and protocols. EBV has invested in building expertise in software-driven areas such as automated motor control, quality control, and safety monitoring, for example.

EBV’s customers consist primarily of the OEMs that build systems for midsize manufacturers—those that aren’t large enough to source their technology directly from embedded hardware suppliers. And its solutions integrator customer base increases as EBV sharpens its focus on providing complete products and services.

“Our FAEs are basically the first line of technical support to address all sorts of questions with a customer, figuring out what the needs are and which direction a customer is heading,” Schmidt says.

When the situation calls for it, EBV uses what it calls the “speedboat” approach. This consists of getting partners involved in building a solution requiring specific types of expertise, such as electromechanics. Sometimes the partner can be a team of experts from industrial distributor giant Avnet, EBV’s parent company.

IT/OT Convergence at the Edge

With more open and standards-based IPCs play a central role in IT/OT convergence and automation, making the ability for real-time data analytics a reality. While this creates more flexibility on the factory floor, it boosts the need for more power.

“Whenever you have higher demand for processing power, that’s where Intel comes into play,” says Schmidt. “Intel provides the CPUs and modules for infrastructure at the near edge, where the data is generated, and at the far edge, where on-premises servers and systems reside.”

Need for performant computing will continue to loom large for manufacturing applications such as anomaly detection and predictive machine maintenance. And solutions based on emerging technologies like augmented reality, virtual reality, and autonomous robots are on the near horizon.

In time, perhaps the edge will even host the quantum technology that led to the 2022 Nobel Prize in Physics. “I think there will be more evolution in this area. There’s so much innovation. It’s a fascinating area we’re operating in,” says Schmidt.

 

Edited by Georganne Benesch, Editorial Director for insight.tech.

RSNA Assembly 2023: The Forefront of Radiology Innovation

Posted on by Micah Kaplan

The RSNA Scientific Assembly and Annual Meeting is without a doubt the most important week in radiology—convening thought leaders for learning, connection, and collaboration. Held at Chicago’s McCormick Place, November 26-30, the event drew more than 24,000 attendees.

Now in its 109th year, the RSNA conference is the most important and largest event of its kind. The gathering gives radiology professionals and scientists from around the world the opportunity to catch up on the latest scientific developments and research, exchange ideas, and connect with peers. A packed five-day schedule featured more than 600 exhibitors, 400 educational courses and scientific sessions, and 3,500 scientific papers.

A wide breadth of topics was covered, including the latest research in generative AI, sustainability in imaging, and imaging of immunotherapy. Other areas comprised advances in mammography and breast screening, prostate screening, MRI brain scanning, cardiac and chest imaging, and state-of-the-art Alzheimer’s disease neuroimaging.

Not surprisingly, AI-related topics featured prominently at the event, which included an AI showcase. Advances in AI are driving profound change in the field of radiology. In fact, the event’s theme “Leading Through Change” shone a spotlight on how radiology professionals can make deliberate, proactive decisions to lead their teams as the field of radiology continues to evolve.

As #radiology undergoes change, the community is focused on how to leverage #technology and scientific advances while at the same time ensuring equitable access to #healthcare for everyone. @RSNA via @insightdottech

Healthcare Equity

As radiology undergoes change, the community is focused on how to leverage technology and scientific advances while at the same time ensuring equitable access to healthcare for everyone. RSNA has made a strong commitment to DEI (diversity, equity, and inclusion).

“We believe that every person can support our mission to improve patient care—no matter their gender identity or expression, sexual orientation, age, ability, race, ethnicity, religion or other characteristics,” RSNA affirms their stance on DEI and healthcare equity.

Some of the annual meeting’s sessions dealt with DEI, providing information to attendees on changes they can make at their organizations to ensure they serve all patient populations. For instance, in one vendor workshop, GE HealthCare, a leading provider of medical imaging, monitoring, biomanufacturing, and other technologies, presented “Implementing portable ultrasound for breast cancer triage in the US and underserved communities worldwide”.

On the Forefront of Women’s Healthcare

With 13 booths and more than 600 sessions, GE HealthCare undoubtedly had a substantial presence at RSNA, with a great focus on women’s health. The company’s “AI decision support for Breast and Thyroid Ultrasound” addressed how recent AI developments are likely to streamline workflow and increase clinical confidence.

In fact, breast cancer, which in the U.S. affects one in eight women, was a widely covered topic across the entire event. Siemens Healthineers, a company that enables providers through digitalizing healthcare, presented “A practical approach to Breast Magnetic Resonance Imaging (MRI) interpretation”, followed by an interactive case review.

Treatments for another form of cancer—prostate cancer—also got a fair share of attention as it ranks as the second-leading cause of cancer deaths among men in the U.S. The Siemens Healthineers’ session “A practical approach to Prostate Magnetic Resonance Imaging (MRI) interpretation” presented a series of cases in this hands-on review.

The Hardware Essentials

Underlying the plethora of AI-powered healthcare breakthroughs is the medical-grade equipment that supports them, from all-in-one computers to OR surgical monitors. Advantech Co., Ltd., a provider of computing systems and other medical devices, demonstrated state-of-the-art hardware designed for many hospital environments and use cases: video management, all-in-one recording solutions, video archiving and screening, and surgical monitors.

For example, the company showcased its Intel® processor-powered USM-500 medical-grade edge server that provides a cost-effective and scalable solution for edge-to-HIS applications. Also on display were the PAX-3 series medical-grade, versatile surgical monitors with IP65 front-panel waterproofing and medical safety approval. There was much more to see in the company’s booth, including Advantech’s AMiS-30EP Pole Cart—yet another essential hospital tool.

Something for Everyone

For attendees looking to roll up their sleeves and take part in competitions, the game show “Oncology Imaging and Interventions: The Radiology Jeopardy” was an entertaining learning opportunity. The show wasn’t just about the most innovative technology and solution breakthroughs. The 5K Fun Run helped improve patient care by supporting research and education in radiology through the RSNA Research & Education Foundation. And with happy hours, social events, and plenty of networking opportunities, the RSNA annual meeting was most definitely the radiology event of the year.

For more on healthcare innovations, listen to our podcast Revolutionizing Cancer Research with Healthcare AI Tools and read the article Virtual Collaboration in Ultrasound Advances Clinical Care.

 

Edited by Georganne Benesch, Editorial Director for insight.tech.

Personalized AI Shopping Experiences: With FIT:MATCH

Posted on by Micah Kaplan

Shopping for a new wardrobe is an experience that should be enjoyable and stress-free. But with the range of choices available thanks to modern fashion, it can easily turn into a tedious chore of navigating the maze of sizing discrepancies among different stores and brands. Imagine if you could just step into the fitting room and have a selection of perfectly fitting garments already waiting for you.

Thanks to the advent of AI and 3D technology, this vision is becoming a reality. The future? A personalized AI shopping experience.

This podcast explores innovative ways that AI transforms the fitting room, both online and in-store, by providing shoppers with personalized recommendations tailored to their unique body measurements and preferences. This custom approach not only enhances customer satisfaction but also drives sales and conversion rates.

Join us as we delve into the future of retail fitting rooms, where AI serves as the catalyst for an immersive, personalized, and seamless shopping experience.

Listen Here

[Podcast Player]

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Our Guest: FIT

Our guest this episode is Hillary Littleton, Head of Marketing at FIT:MATCH, a provider of AI-based B2B2C retail solutions. Prior to FIT:MATCH, Hillary managed strategic client development at Saks Fifth Avenue for more than half a decade, and worked as an independent brand marketing consultant. Since joining FIT:MATCH, Hillary has worked to establish the company’s brand identity through her deep understanding of the patented, back-end technology driving the platform to development and execution of marketing plans for FIT:MATCH’s key-client base.

Podcast Topics

Hillary answers our questions about:

  • Current AI trends in the retail space (2:47)
  • Retail challenges for providing quality shopping experiences (4:31)
  • AI helping advance retail technology (6:31)
  • Benefits of improving the fitting-room experience (8:48)
  • Implementing new retail technology online and in-store (11:13)
  • Value of partnerships when creating innovative retail solutions (14:45)
  • Future of retail technology (15:31)
  • How AI can optimize the shopping experience (17:06)

Related Content

To learn more about personalized AI shopping experiences, read Phygital Experiences Help Fashion Retail Shine. For the latest innovations from FIT:MATCH, follow them on Twitter at FIT:MATCH.ai and LinkedIn at FIT:MATCH.ai.

Transcript

Christina Cardoza: Hello and welcome to the IoT Chat, where we explore the latest developments in the Internet of Things. I’m your host, Christina Cardoza, Editorial Director of insight.tech. And today we’re going to be talking about AI shopping experiences with Hillary Littleton from FIT:MATCH. But before we get started, let’s get to know a little bit more about Hillary. Hillary, thanks for joining the podcast.

Hillary Littleton: Thank you so much for having me, Christina. It’s great to be here.

Christina Cardoza: Yeah, of course. Can you tell us a little bit more about yourself and FIT:MATCH?

Hillary Littleton: Absolutely. So, at FIT:MATCH I lead all of the marketing and growth efforts for the company, and over the course of the last two and a half years I’ve established our brand identity through an omnichannel B2B2C lens. What that means is I’m really responsible for developing and executing on business strategies, designing and delivering marketing plans, and focusing on key performance indicators to drive overall success for FIT:MATCH. So my team holds a close relationship with both front-end sales and back-end tech to drive winning go-to-market strategies and product launches.

So, a little bit about the company. For consumers, FIT:MATCH delivers an innovative, personalized, yet totally private shopping experience. During a scan, our patented algorithm actually captures a shopper’s 3D shape and matches it back to a digital twin—so, somebody in our database with the most similar body shape that has already tried on the product. And then the data that consumers receive is completely unique to them. So they get to view their own shape profile; they get to see customized product matches guaranteed to fit their shape best.

And we built it this way because we know a 3D problem can only be solved by a 3D solution. We use 3D shape on purpose; we don’t use any measurements. And the best part is that the experience is incredibly quick, simple, and intuitive.

Christina Cardoza: Yeah, absolutely. It’s amazing to see how far AI has come, and I first heard and saw FIT:MATCH at Intel Innovation during the keynote, where the company demonstrated exactly what you’re talking about. It took a 3D model of an individual and demonstrated how it could provide that personalized experience and retail options for a consumer. Which is something that I love, because I typically dread the shopping experience—you know, having to try on clothes.

Hillary Littleton: I know.

Christina Cardoza: Finding out what fits—that’s one of the worst things for me. So seeing this technology where you can actually go in and then it maps it to you, that’s great. And obviously we heard a lot at Intel Innovation about certain AI trends and advancements going on that are enabling these things to happen.

So, I’m just curious, what are you guys seeing in the AI space, particularly in retail, what trends and advancements really make FIT:MATCH possible?

Hillary Littleton: Yeah. I mean, everybody knows that AI solutions are a hot commodity right now and can be easily accessible, but I think gaining access to the right solutions is really the difficult part. We know that retailers are craving products that are both seamless to integrate, but also lead them to achieve important KPIs for their business. So our tech is revolutionary and immersive for the shoppers, but it’s also impacting our brand partners’ bottom lines in a big way.

And I love that you mentioned that about Intel Innovation, because I think what we learned a lot from the conference is that the need for the technology spans across all sorts of customer demographics. It’s really a universal problem. And it was amazing to see how many people were just so fascinated by the technology that they had to come and try it for themselves following Pat’s live keynote.

And then, just on top of that, Intel’s edge computing has just been so instrumental in the way we scale. It’s really enhancing the user experience. It’s private, it’s quick, but it’s also more cost effective. So OpenVINO™ technology really just stands out as a prime example for us to commit to the edge optimization. And we really just see immense value in OpenVINO and are really dedicated to integrating it in more of our product offerings going forward.

Christina Cardoza: I want to dig a little bit deeper into some of the challenges you were saying. Obviously in the beginning I spoke about how it’s a challenge for me to go shopping because I just dread the fit experience. But I’m curious to learn a bit more about why has it been a challenge up to date that retailers have faced to provide this type of quality customer experience, you know? And to really provide a comfortable experience for customers in a fitting-experience setting.

Hillary Littleton: Yeah, absolutely. I mean, relating to the fit experience, I know that there are three off the top of my head that I continuously hear from retailers. One is customer retention and drop-off rates—where customers just don’t know what size to buy, or their size is sold out. And just it results in churn rate, lack of loyalty, and just an unsatisfied shopper—kind of like what you were just saying about yourself.

And then number two: leftover inventory due to poor buying, planning, merchandising decisions for the business. And then three: returns. I mean returns is just something that we continuously hear due to the lack of size education for the consumer, and just communication to the shoppers in general: if they don’t know that their size is available, how would they know to go to your page?

So I think by employing our patented technology we can really derive detailed information about this person’s shape that you cannot get anywhere else, and it’s just truly unparalleled in the industry. So we’re just really proud of that. And, you know, for example, we can now not just tell you what size you are, but we can also explain why you’re that size and what you should do with that information going forward. So, yeah.

Christina Cardoza: Yeah, that’s amazing. And, you know, going to the returns and not knowing your size—issues that you mentioned. A lot of these different brands, I find there’s no one size fits all. Like, one size six is not going to be a size six at another company.

Hillary Littleton: Exactly.

Christina Cardoza: So that’s great that you’re not giving sizes really, or you’re not doing any measurements. It’s really based on that 3D scan.

Hillary Littleton: Yeah.

Christina Cardoza: And you also said that you did a 3D scan, and that maps it to a digital twin of the individual. So I’m curious what types of AI capabilities or advancements are you leveraging to provide that personalized, accurate recommendation for the customer to sort of alleviate some of the stress that businesses have been facing?

Hillary Littleton: Yeah, and I did want to just touch on one really interesting point you just made: we don’t ask the customer—the shopper, I should say—for any information up front except for just their name and email. We take the, all of the equating off of their hands and off of the brand’s hands, quite frankly, so all that a shopper sees is—after their scan is the sizes appear for them, which is really, like I said, different from what you see in other fit tech in the industry. We don’t ask you for your measurements—most people don’t even know how to take their measurements. So in that way it’s just super easy and immersive, and just hands off and fun.

But overall I think AI is just really at the core of our platform today. You know, it powers our ability to interpret and leverage that 3D shape information that’s captured using Intel’s RealSense™ LiDAR sensors. By employing that we can really just get more unique information that this shopper cannot get anywhere else. So on top of being really easy and fun, you’re getting this portal into data about yourself that you cannot get anywhere else. And so we’re finding that customers absolutely love that.

Christina Cardoza: Yeah, I can see all of the customer benefits to this. I’ve also seen through my own shopping experience online that the technology can even help with, how do you want this to fit? Do you want this to fit tight? Do you want this to fit baggy? And then it’ll give you a size

Hillary Littleton: Oh yeah.

Christina Cardoza: Based on how you want that to fit, and even show it on the 3D model. So that’s great to see that.

Hillary Littleton: Yeah. Preference is huge, for sure.

Christina Cardoza: Yeah.

Hillary Littleton: I mean preference is something that has to be built into our technology. We have it built in, we’re learning more as more consumers tell us how they like things to fit, and then we can kind of spit back recommendations based on those things, for sure.

Christina Cardoza: Yeah. So, obviously improving the whole customer experience overall, but on the business side you mentioned some of the challenges with returns and everything. So what about the benefits that businesses will get now from the customer experience from this improved, personalized fitting experience?

Hillary Littleton:  Yeah, for sure. So, we’ve seen incredible benefits so far for our brand partners, including on average a 6x conversion rate for those that are scanning with FIT:MATCH versus the ones that aren’t—20% to 30% higher average order values. Those that are scanning are actually returning 80% less than the ones that aren’t, less than 1% of consumers are buying more than one size—bracket shopping, as we call it in the retail space. And that’s a really big one, right? There’s a lot of fit risk online, and we’ve seen that retailers are telling us that bracket shopping is the number one concern that they have, so it’s great to see that that’s now down to less than 1%.

And then when we think about loyalty, there’s a 2x sign-up rate for those that want to be part of the loyalty program that have scanned versus ones that haven’t. So we’re definitely seeing long-term loyalty increased. And then overall customer satisfaction, net promoter score, has increased by 16 points on average. So we’re really proud of these results.

And then there’s also things that we can build out with brand partners going forward. So, like I mentioned, more insight into their consumers—like what is the data dashboard that we can really customize and serve up to brand partners according to their preferences so they can make more personalized marketing decisions, merchandising decisions, and long-term loyalty building from that data that we can serve up to them. And that can be on product construction, that can be on inventory management. Just getting rid of excess inventory, we’ve heard, is just a huge pain point. So we’re excited to tackle that as well.

Christina Cardoza: I’m definitely guilty of the bracket shopping online.

Hillary Littleton: Yeah.

Christina Cardoza: There’s nothing worse than falling in love with something online, and then getting it, waiting the weeks or days for it to arrive, and then it not fitting, so….

Hillary Littleton: Right.

Christina Cardoza:  I always order multiple sizes, just in case.

Hillary Littleton:  I know.

Christina Cardoza: So it’s great you can do the—you don’t have to go through that fitting experience, which size fits the best, which one should you keep—things like that. I’m curious, because obviously a lot of this sounds like it’s in the store setting, but is there an online component to this as well? How do you work with brands to implement this within the store, and then how can you expand it out, outside of the store for customers like myself who like to do online shopping more than in-store shopping?

Hillary Littleton:  Yeah, absolutely. So, a little bit of background on our products and market. Earlier this year, FIT:MATCH actually debuted our newest in-store fitting room experience for apparel retailers. We dubbed it Fit Xperience, or Fit Concierge, I should say, which gives shoppers the opportunity to get scanned in an in-store fitting room using Intel’s RealSense LiDAR technology and Intel’s OpenVINO.

So, using the LiDAR sensors we can collect that avatar, and it happens in one second. So that’s what’s amazing about our in-store retail solution. And then, like I mentioned, we’re actually able to, within that one second, match it back to an avatar of a closest digital twin that’s already tried on the garments in our extensive database. That entire in-store process takes like 10 to 15 seconds, and consumers get their exact sizes across the retailer’s entire assortment on the spot.

So, I mean, imagine not having to gauge your size or drag in many different sizes of the same product into the fitting room to just see what one fits? It’s a huge time saver for customers. And then we also email the results to the shoppers so they can be used at home. The first retailer that incorporated our concierge solution was Rihanna’s Savage X Fenty.

We’re rolling out the next iteration of the Fit Concierge at a popular shopping center in Los Angeles this holiday season. This new version is faster, with extra layers of privacy and even more accurate. And we’re also with that partnering with a multibillion dollar apparel and footwear brand in the sportswear space, and the entire experience will be accelerated by Intel suite of products. So that is to-come for in-person shopping.

And then for at home, our future plans are definitely focused on bringing everyone the ability to scan using their own mobile phones. So with one scan shoppers will be able to unlock a passport of sorts across brands, offering up recommendations in their sizes. So no matter if you scan in store or at home, your personalized shape profile will be accessible from anywhere.

Christina Cardoza: I can not only see how this would be time saving for the customers but also the business. Like you mentioned, you don’t have to bring all of those clothes into the fitting room; the retail managers or the people on the floor, they don’t have to be—store associates don’t have to be putting this all back on the shelves, so. . .

Hillary Littleton:  Exactly.

Christina Cardoza: It makes for a cleaner space too, especially in stores and you mentioned—

Hillary Littleton: Yeah. I was just going to say, and they can better service their customers. That’s the beauty of it is they know what the shopper really wants and what is going to fit the shopper, so they’re able to offer a much more elevated shopping experience to serve up to them, which reflects well on the brand and obviously that consumer is more satisfied.

Christina Cardoza: Now you mentioned using Intel LiDAR and Intel OpenVINO—which is Intel’s AI toolkit—to make some of this happen. So I’m curious, what is the value of partnerships like Intel, and using their technology and working with them to make the FIT:MATCH fitting room experience possible and to bring this to across doors and to mobile devices?

Hillary Littleton: Yeah. As I mentioned earlier, I think the edge computing is just key to how we scale this. It’s super private; it’s super quick, which customers love obviously. But for brands and for our brand partners it’s just more cost effective. So OpenVINO, it really stands out as a prime example on how we can really scale this to the next level. Partnering with Intel, and we just see this as kind of the infrastructure of how we’re going to build our products in the future.

Christina Cardoza: Now are there any—I’m just curious, are there any additional use cases to this technology that you can see this solution being expanded to, or any other plans in the future to really scale the capabilities at FIT:MATCH into other areas or industries?

Hillary Littleton: Yeah. I mean, look—I think we’re definitely leaning into the effects of how AI can optimize the shopping experience. We’ve built an AI fit assistant that can, like I mentioned earlier, not just tell shoppers what to buy, but why they should buy it. So tools like this integrated with a seamless checkout experience on e-commerce are crucial elements for the consumer journey. And knowing that, FIT:MATCH can provide that solution.

And then recently we also have broken into the healthcare and wellness sector, with launching a scanning experience exclusively built for plastic surgeons and their patients who are going through body transformation. So we’re super excited to see how our shape-matching technology can impact other use cases outside of just fashion retail.

Christina Cardoza: Well, I can’t wait to see these solutions become more mainstream and find them in my own stores or the places that I shop. I just had a baby recently, so my body has changed quite a bit.

Hillary Littleton: Yeah. Absolutely.

Christina Cardoza: So it would take a lot of stress off of me finding clothes that fit if I know exactly what’s going to fit and how it’s going to fit with technology and solutions like FIT:MATCH. So I think this is great, and I can’t wait to see where else this solution and the company goes.

Unfortunately, we are running out of time, so I just want to throw it back to you one last time, if there’s any final thoughts or key takeaways you want to leave our listeners with today.

Hillary Littleton: Well, thank you just so much for this opportunity, Christina and the Intel team. It’s always so fun for me to gush about how we’re innovating the future of retail with Intel. And I would just like to say, I guess for anybody listening, if you’re interested in following along with all that we’re building at FIT:MATCH, to just stay tuned about our news and happenings. We’re on LinkedIn at FIT:MATCH.ai. And Twitter, Instagram, and TikTok as well.

Christina Cardoza: Awesome. Well, I can’t wait to see what else FIT:MATCH does, and, like you said, I encourage all of our listeners to go on the website, follow them on social media, and see how else they are innovating in this space. So, thank you again for the insightful conversation.

Hillary Littleton:  Thank you so much.

Christina Cardoza: And, until next time, this has been the IoT Chat.

The preceding transcript is provided to ensure accessibility and is intended to accurately capture an informal conversation. The transcript may contain improper uses of trademarked terms and as such should not be used for any other purposes. For more information, please see the Intel® trademark information.

This transcript was edited by Erin Noble, copy editor.

Cloud Desktop Solutions Make Smart Hospitals More Efficient

Posted on by Micah Kaplan

The digital transformation of healthcare has given us the “smart hospital.” These next-generation facilities leverage AI, IoT, digitalized information systems, and cloud computing to unify hospital data, streamline medical workflows, and improve patient care.

Smart hospitals help address medical sector pain points like staff shortages, budget cutbacks, and aging populations in need of increased care. But as hospitals embrace digital tools and infrastructure, they’re encountering new challenges. One clear example is the operation and management of PC workstations used by hospital staff.

“Entire hospitals are now going digital, from inpatient and outpatient departments to back-office groups and training divisions,” says Han Xingkun, Senior Product Manager of H3C Cloud and Intelligence Product Line at New H3C Technology Company (H3C), a digital infrastructure provider that offers a cloud desktop service for hospitals. “But these user groups all have diverse needs. Technical staff must customize extensively—and manage and maintain different terminal environments and applications separately. It places an enormous strain on hospital IT departments.”

In addition to management and maintenance challenges, PC terminals have other limitations. They tend to be expensive and resource-intensive. They’re also difficult to secure, making them a real worry in an age of cyberattacks and ransomware.

The good news for healthcare is that there’s an alternative approach to the traditional PC terminal that addresses these issues: the cloud desktop. A cloud desktop—also called a hosted desktop, virtual desktop, or desktop as a service—is a system where a user’s OS, settings, and applications are hosted and managed in the cloud instead of on a particular PC. Users access their personalized desktop environment from any device over a network connection.

Virtual desktops are reliable and secure. They’re also more cost-effective than standard PCs, because they can be accessed using lightweight, energy-efficient terminal hardware. Best of all, cloud desktop platforms now support multiple configuration options, making it easier for IT groups to manage desktop environments for varied user groups.

Making Smart Hospitals Smarter

Modern cloud desktop solutions enable deployment and management of terminal environments through a single, cloud-based platform—and allow for the integrated management of multiple virtual desktop architectures. In a hospital setting, this is vital, because it allows IT teams to offer different departments and user groups exactly what they need:

  • Inpatient departments are 24/7 operations with teams of doctors and nurses caring for vulnerable patients. Cloud desktop services offer highly stable systems for continuous operation. They can be easily shared by medical staff working in shifts and repaired quickly by remote IT staff if a problem arises.
  • Outpatient departments serve a high volume of patients every day and combine check-in, payment, and pharmacy functions. Virtual desktops offer the high reliability and strong security needed in this setting. They also support multiple types of peripheral devices at patient service windows, such as all-in-one card readers, QR code scanners, high-definition cameras, receipt printers, and point-of-sale devices.
  • Back-office staff operate in a more traditional office environment, with the same user at the same terminal from day to day. In this scenario, cloud-hosted desktops can be configured to support a more account-based user experience, enabling greater personalization, more complex applications, and remote work options.
  • Training facilities in hospitals are essentially classrooms, with large numbers of desktop terminals and different groups of students and instructors sharing resources throughout the day. The benefits of cloud desktops here are standardized environments, fast recovery in case of an outage, and easy central management to help IT departments deliver reliable updates, upgrades, and security patches.

This degree of flexibility and performance is not easy to achieve, but H3C’s technology partnership with Intel has helped make it possible.

“Our solution is based on Intel® Ultra Cloud Client, which delivers an excellent balance in terms of performance, stability, compatibility, manageability, and personalized application support,” says Xingkun. “Intel’s platform also provides powerful management tools, including peripheral security management and control, batch software updates, software security features, permissions management, and push messaging to user desktops.”

Modern #cloud desktop solutions enable deployment and management of terminal environments through a single, #cloud-based platform—and allow for the integrated management of multiple #virtual desktop architectures. @H3CGlobal via @insightdottech

From the perspective of the end user, hosted desktops offer the best of both worlds. The experience is similar to the PC terminal they are already familiar with. But behind the scenes, the simplified IT management and increased flexibility provide a customized and highly reliable desktop environment.

Benefits for IT Teams and Hospital Managers

While frontline hospital staff and back-office employees benefit significantly from cloud desktops, perhaps the biggest beneficiaries are IT employees and hospital administrators.

For IT teams, the centralized management capabilities of virtual desktop platforms simplify routine maintenance tasks, OS upgrades, and personalized software updates for end users. In addition, the stability and security of hosted desktops lower the risk of crashes and security incidents, which further reduces the burden on hospital IT.

Hospital administrators see the benefits of cloud desktops at the macro level. Their staff have the tools needed to do their jobs, and IT groups are free to pursue higher-value tasks. The terminals themselves are more reliable and energy efficient. And thanks to built-in security features, there is less risk of a cybersecurity incident. For many healthcare business managers, cloud desktops will be a natural choice.

H3C’s implementation at a large medical center near Shanghai is a case in point. “Our cloud desktop solution was widely deployed at the Kushan Eastern Medical Center,” says Xingkun. “Hospital leadership felt they’d effectively solved the problem of their doctors’ and nurses’ workstations and daily office work in the hospital—and that a single member of the IT team could now manage thousands of desktops.”

The Future of Cloud Desktop Services

As the digital transformation of healthcare accelerates, more hospitals are likely to turn to cloud desktops to solve operational challenges and lower the total cost of ownership for their hospital workstations.

In addition, virtual desktops will find numerous use cases outside of hospital settings. H3C, for example, offers versions of its cloud desktop platform for education, telecommuting, and R&D settings. The promise is broad, and the future is bright, says Xingkun—especially in the healthcare sector.

“Medical systems face some serious challenges, but the current wave of digital transformation offers hope,” says Xingkun .“Smart hospitals, powered by innovative technologies like cloud desktop services, will help make patient care more efficient and keep our citizens and societies healthier.”

 

This article was edited by Teresa Meek, Editorial Contributor for insight.tech.