Skip to main content

Building Smart Spaces for Communities

community smart spaces

It’s easy to get excited about the latest technological bells and whistles, but when all is said and done, the point of innovation is to improve the real lives of real people. And technology needs to serve that goal. It’s one thing to collect masses of data, but what do we do with it then? How can we employ it to create a more livable world? Safer crosswalks, more personalized retail experiences, biosecurity for our food sources, even more usable dog parks.

We talk about how to get there with Ken Mills, Chief Executive Officer for global AI and IoT technology provider IntelliSite, and Justin Christiansen, General Manager of IoT Platform & Solution Sales at Intel®. They discuss the need to create smart communities—not just smart cities—the benefits of the as-a-service model, smart-space AI, and IntelliSite’s ongoing partnership with Intel®.

What is the difference between smart cities and smart communities?

Ken Mills: When you talk to users about being a smart city, or a digital city, or a safe city, they can’t always relate because often they’re not actually a city, right? They might represent a state agency, or a county, or a campus, or any small community. It makes much more sense to approach the market from a community perspective—a group of people coming together to find a solution around making their community safer, smarter, or more connected.

Most people equate technology with building blocks—a set of Legos that you put together to get your desired outcome. But most communities do not want to build Legos. They want to order a pizza. They want the whole thing delivered to them, hot and ready to eat. They don’t want to have to worry about how it was put together, or have the responsibility of putting it together themselves. They just want it delivered ready to go.

And we found that when most communities think about IoT or AI, they’re not ready to build the Lego pieces and worry about whether they put them together right. Did they follow all the directions? Do they have the right skills? Where do they start? They want to know that when they decide on a project, and they decide to spend their time and money on that project, that they’re going to get the outcome they expected when they started it.

And so by delivering it as a service, we’re able to ensure that they get the pizza and they’re not left with a bunch of Legos they don’t know how to put together.

What exactly is a community-as-a-service model and its importance?

Ken Mills: Being able to predicatively lock in cost and know what they’re going to get for that cost, and then also getting the benefit of having a company continue to innovate and provide additional features and functionality as those become available within that fixed cost—that’s very appealing to both sides of the equation. As a business owner, I have fixed revenue that I can count on that allows me to invest further in our technology. And those customers get the best product at all times, every time they need it.

It really is a whole new way for communities to consume technology, as well as to ensure that they’re never left behind—which is often the case in the public sector. Public-safety customers don’t often get the latest and greatest in technology. It’s a great opportunity for them; it’s a great opportunity for us. And we see this model taking off in many areas across the country and outside the US.

Justin, what are the trends you’re seeing in smart spaces from an Intel® perspective?

Justin Christiansen: Safety is one of the key focus areas for customers as they deploy smart city. But it’s also about giving people a better experience in places like stadiums, theme parks, and cruise ships. Personalizing their experiences. The adoption of AI really enables our customers to improve their business operations and the customer experience—for example, technology in areas like the retail environment providing more seamless checkout, or making sure that shelves are fully stocked.

And with COVID, the integration of robotics to minimize person-to-person interaction has also been important to providing a better experience and a safer experience. That’s true across all smart spaces.

Ken, can you lay out some of the use cases you’ve worked with?

Ken Mills: One is smart and safe intersections. As people are out and about more, communities are really looking to ensure that crosswalks are safe, reducing pedestrian fatalities in a concept called Vision Zero. There are a lot of different ways you could do that—better street marking, better lighting, intelligence for traffic lights.

Video technology is also a great tool for improving intersection crosswalk safety. You can do that with AI technology and edge computing, leveraging Intel chipsets and OpenVINO tool sets to really improve that process, oftentimes reducing the cost of deploying those technologies.

“It really is a whole new way for #communities to consume #technology, as well as to ensure that they’re never left behind—which is often the case in the #PublicSector,”— Ken Mills, @IntelliSiteIoT via @insightdottech

Another example is in smarter and safer parks. Parks are now becoming the town centers of a lot of communities, so ensuring that those parks are safe and accessible is really critical. Here’s one park example I love. If you’ve ever been to a dog park after it’s rained, or where the sprinklers were on too long, your dog is a mess, you’re a mess, the park gets destroyed, it can cost the city thousands of dollars to repair that torn-up grass, and the dog park gets shut down for a time. Everybody loses.

But by using edge-computing IoT sensors, you can analyze the soil moisture levels, soil quality, and get all kinds of great data. Then you know if it’s too wet to open and you can send a Facebook or Twitter message to say, “The dog park is closed today because it’s too wet.” You save the city thousands of dollars and reduce people’s frustration, so everybody wins. That’s a great example of where edge technology can be brought together to provide real citizen value. Simple problem, simple solution, profound impact.

We’re also seeing use cases around biosecurity, where we’re using edge AI and IoT to bring together a robotic solution to provide food sanitation and safety. These are things like killing Salmonella or E. coli or Listeria, for instance. But also improving the shelf life of the food itself so that it can be delivered farther away without having to worry about high spoilage rates. This ultimately delivers lower cost—both to the shopper and to the producer.

How are you handling all this valuable data so users can understand it and act on it?

Ken Mills: It goes back to the pizza analogy. Communities want to buy pizzas, not Legos. Through our Deep Insights set of solutions, we can deliver it all together. We can take their IoT data, their computer vision data, their time-series data and other sensor data, bring it together, analyze it, and provide real insights.

We then use our rules engine to determine what can be done with that insight. Do they just keep it and report on it for historical purposes or trend analysis? Do they act on it and generate an event or response, like in the dog park example? Or do they tie it into a third-party tool, like ServiceNow, to create a ticket: “The park shouldn’t be this wet. We haven’t had rain in the last 24 hours, so we must have a sprinkler system issue.” Then they’re going to go out and fix it—maybe proactively, maybe quicker than they normally would.

What sorts of things have been really critical to moving all this forward?

Justin Christiansen: The ability to take multiple data points is a key trend that has really played to our strength, and helped us understand how we can support customers better in IoT deployments—specifically around AI.

You think through the early IoT deployments that we have been involved in over the past five or ten years—it was often specialized equipment, specialized software being deployed to drive a specific outcome. And often that was utilizing some accelerator technology that provided the best performance for a single workload, but wasn’t capable of aggregating all the different workloads. What we’ve found is that customers don’t want to deploy different IT devices for every outcome. They want the ability to run it all on the same IT device, if possible.

And so we’ve invested in software-optimization tools to make that easier to do. We’ve invested in features such as Intel® DL Boost—which we’ve included in the CPU—that provide much better performance on an AI workload. And that drives a lot of benefits to our collective customers with the IntelliSite team because they’re able to use less expensive infrastructure. They don’t need to invest in as much IT equipment to drive multiple use cases.

There are also the current global supply chain challenges. It’s difficult for companies to even find their favorite technology at the moment. And so having the ability to run those applications on IT infrastructure that’s easy to find or that they already have has proved critical as well.

What are your thoughts on the balance between the edge versus the cloud?

Justin Christiansen: We often talk about the cloud or the edge. But it’s really the cloud and the edge. What we’ve seen from our partners is that they want the ability to provide their customers with the service they want. Sometimes that requires an edge deployment. But sometimes it’s best served from a cost or capacity perspective in the cloud. So the reality is that we need to be able to provide both to our partners, because they have to provide both to their customers. I think it really just depends on the workload that they’re running, the outcome they’re trying to drive, and the ROI associated with the type of deployment they’re looking at.

What should communities be looking for in a technology partner?

Justin Christiansen: The technology piece is what we’re focused on because we’re a technology company. But when we look at what it takes to provide these types of outcomes to end customers, it really is a large group of partners. IntelliSite’s been an amazing ISV partner. We have channel partners. There are a lot of systems integrators to deploy this equipment, and those tend to be hyper-regionalized.

At the end of the day we’re all focused on solving the end-customer’s business challenges. We’ve talked mostly about smart spaces, but it really scales across all businesses, and the outcomes that technology can drive to.

Is there anything else that the communities you’re serving should consider going forward?

Ken Mills: Often the easy button can be the most costly one. It’s important for communities of all sizes to look at the whole solution, and really make sure that they’re not getting locked into proprietary, niche solutions that are limited in their scope, and limited in their ability to impact change or bring value. And to really look for solutions that are open and flexible, and that allow for the dynamic innovation and change that are necessary over the life cycle of any technology project.

Justin Christiansen: From a technology standpoint, the scalability of the technology they’re deploying is incredibly important. What we often find is that a customer wants to deploy something at a relatively small scale to see if it works. And if it does work, they want to quickly scale it to something much larger.

I would also add the ability to be flexible in terms of what their technology can provide for them over time. We don’t know what applications or use cases a customer may want a year or two down the road, but we want to provide technology that’s capable of serving them after they’ve purchased it. If you had told me two years ago that I would actually want to be in a restaurant where there were relatively few people and we were served by a robot, I would’ve thought you were crazy, right? That’s actually a somewhat desirable state today.

Related Content

To learn more about creating smart spaces for communities, listen to the podcast Smart Spaces for Smart Communities with IntelliSite. For the latest innovations from IntelliSite, follow them on Twitter at @IntelliSiteIoT and on LinkedIn at IntelliSiteIoT.

 

This article was edited by Erin Noble, copy editor.

About the Author

Kenton Williston is an Editorial Consultant to insight.tech and previously served as the Editor-in-Chief of the publication as well as the editor of its predecessor publication, the Embedded Innovator magazine. Kenton received his B.S. in Electrical Engineering in 2000 and has been writing about embedded computing and IoT ever since.

Profile Photo of Kenton Williston