How to Build a City for the Future

One Firm Creates a City OS to Tackle Data Silos and Smart Development

Cities will become top benefactors of the so-called Big Data era, if they adopt the right approach to planning and implementing infrastructure solutions that effectively leverage data. Smart solutions and systems can help increase efficiency, reduce CapEx, and extend the life cycle of existing and new infrastructure systems, according to the firm Living PlanIT, which has developed what it calls an “Urban Operating System” (UOS).

The Urban Operating System is a horizontal platform for the city that is designed to help scale, organize and integrate the vast field of data generators onto a single, open platform that can support a range of systems and solutions leveraging data to address issues such as waste management, water use, and energy costs.

“Smart technology is a means to an end,” said Dan Byles, VP of corporate development at Living PlanIT. “Nobody wants to live in a smart city or smart township. People want to live in a township where the air is clean, and the roads are not congested, and the energy works effectively.”

“My own definition of a smart city is one that eases the friction in the citizen’s path through life,” Byles added. “Ultimately it’s about improving quality of life and making things more efficient and more sustainable. The way to future-proof your city is to put in place the underlying enabling infrastructure,” he said.

The Urban Operating System

Living PlanIT, founded in 2006, is comprised of a group of real estate, financial and technology experts focused on using technology to develop better communities. The company has created a backbone platform, called the Urban Operating System, that acts something like an OS for an environment and upon which smart systems and applications can run. The company is currently working in Copenhagen, Austin, Texas, and Singapore.

The UOS platform “brings together infrastructure, sensors, devices and people,” the company states on its Website. “Most systems and technologies related to real-estate development and infrastructure operate in a vacuum, blind to the worlds of data swirling around them.”

The UOS seeks to intelligently unite data from across diverse sensors and devices in a flexible and scalable platform. The UOS is comprised of two pieces: the Core layer and the Control layer.

The Core layer handles the collection, processing and management of the data. It combines real-time data with historical data, derives insights from the data, and then applies those insights to the applicable systems. The Control layer governs device interfacing; it’s comprised of autonomous control applications and drivers that support a range of equipment and infrastructure.

“So the data from the Control layer is brought up to the Core layer, where it can be combined and integrated with third-party data sets [or] existing data sets to create a genuine, horizontal integrated platform that can be a single repository for city-wide data,” said Byles.

The UOS is compatible with both new infrastructure and “most” legacy systems, he said. The UOS can be used in small-scale environments such as shopping malls, airports, school systems, and building management systems, or in large scale environments such as an entire city or municipality. According to Living PlanIT, the platform is open, secure, flexible and scalable.

“This isn’t easy. Creating actionable insights that allow you to make interventions is difficult. Data sources are diverse, data sources are imperfect.”

The platform also helps create a functioning data economy, Byles said, “whereby data that has a value can be exchanged, can be traded, can be aggregated with further, richer data sets in order to create more value.” The data economy also helps to ensure that parties can monetize the data they’re generating and collecting.

“Once data has been combined, merged, integrated into the supervisory layer, into the big data marketplace, third-party companies, even citizens can access data through an app store, for example, and then use that data in creative and novel ways, to create new services and tackle problems in innovative ways,” Byles said.

Overcome the Data Silo

As the Internet of Things comes to fruition, smart systems aimed at leveraging big data have to date adopted a bottom-up approach, each with its own unique and proprietary platform.

“The challenges we face in city and urban environments in infrastructure at the moment is that we see systems that are disparate, isolated, fragmented,” Byles said. “They’re not connected [to one another].”

“Too many people in the IoT and smart city space make the mistake of approaching it from a vertical perspective, but the danger is that you still create a silo, you still create a system where you’re creating your own vertical, standalone infrastructure, and where the data remains isolated and unable to be integrated with diverse sets of data streams from other parts of the city or urban environment.”

The proliferation of these “single-use systems,” as Byles calls them, has lead to a forest of data silos and multiple, redundant platforms and applications. “Overall, a city is a hodge-podge of different disaggregated systems,” Byles said, and that leads to unnecessary costs. “The ideal is to try to unite different ways of gathering data, different ways of running infrastructure and services onto a common, horizontal platform.”

The UOS addresses this issue by combining data from diverse sensors and sources into one open platform that anyone, whether a municipal department, tech start-up or even regular citizen can access. Meanwhile the entire ecosystem benefits from the data aggregation.

“Some people shy away from the platform because it sounds very top-down; and you often get this top-down versus bottom-up discussion,” he said. “A proper, open platform that’s well designed like [the UOS] is an enabler for a bottom-up solution. You do need an underlying enabling infrastructure if you’re going to prevent lots of little IoT and smart city projects popping up all over the place that are simply silo’d.”

Computing at the Data Source

As software-defined networks begin to populate across all sorts of industries and businesses, companies have been moving more computation and processing to the cloud. Byles, however, warned that moving everything to the cloud — including all the big data being generated by millions of sensors and devices — is not a feasible solution.

“Half of the battle with Big Data is knowing what data to throw away, knowing what data you don’t need; and you only know that if you’re doing the analysis as close to the edge, as close to where you’re gathering the data as possible,” Byles said.

An effective smart infrastructure system instead will need to rely on intelligence and processing that is distributed throughout the ecosystem, meaning computing that is done on the data-collecting devices themselves, with only the metadata being transported to the cloud to drive insight and ultimately response.

“A lot of device manufacturers are still making the mistake of thinking that in this brave new world of IoT, smart cities can operate in a pure device-to-cloud environment. That creates all sorts of problems, particularly when you try to scale up.”

“So part of this intelligent infrastructure is embedding the intelligence as close to the infrastructure as possible, so that ultimately you’re only streaming the results of the analysis,” he said, adding that in Living PlanIT’s UOS, the Core layer relies on edge computing, which helps it to “reduce latency and lag, increase the resiliency of the system, and reduce the amount of data you have to transport.”

Cost-Benefit Analysis

The goal of any smart solution should be ultimately to get more bang out of a buck. Smart systems can be used in a variety of scenarios to increase efficiency, reduce costs, extend the lifespan of products or infrastructure, reduce carbon emissions, the list goes on and on. But adding smarts to anything requires a little extra money up front.

According to Frost and Sullivan, smart system costs represent between 2%-5% of total infrastructure costs, but smart systems help to realize up to 30% in savings down the road. “We’ve got to get away from viewing the CapEx and OpEx separately,” Byles said, suggesting instead the use of “TotEx,” which would refer to expenditure across initial investments and deployments, as well as operating expenditures over the lifetime of the piece of infrastructure.

“The total life-cycle cost of running that piece that infrastructure over many decades, it’s often significantly less,” Byles said. “In a short number of years, we’ll stop making the distinction between smart infrastructure and infrastructure. We’ll recognize it as just the way we have to do business.”

“This is often the first question leaders ask: How are we going to fund this? When people view this as an unnecessary add-on, or a gold-plated nice to have, they’re viewing it totally wrong. It’s not a question of can we afford to do this, it’s a question of can we afford not to do this.”

The next step is to begin experimenting, and ultimately proving, business models for smart systems and solutions. “We’re early enough in the roll-out of smart solutions that there isn’t a huge number of clear cut use-cases you can point to and say, ‘Look, this city did it and saved 20% on energy’,” Byles said. “We are getting there. I think the next 12 months or so is going to be a really interesting time, and we’ll see more use-cases that demonstrate the ROI.”

“The technology is absolutely there, we no longer need really to be demonstrating the technology,” he added. “What we now need to be demonstrating is the business models. How do we take this disruptive technology and turn it into replicable business models that people can have confidence in?”

Listen to Frost and Sullivan’s Webinar here.

Feature image:
Creative Commons Creative Commons Attribution 2.0 Generic License   by  plindberg 


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