Below is an excerpt from Kyt Dotson’s novel City of Paradigm, a science fiction tale about a fictional 21st century city situated somewhere in California. Each City of Paradigm column is two parts: an excerpt from the novel and an editorial describing the real-world context of the technologies described in the story. Readers may find more City of Paradigm here on SiliconANGLE.

Across the city, it was raining.

It didn’t rain often in the City of Paradigm; but when it did, nobody was surprised. Every raindrop that fell within city limits would be detected by something, millimeter wave doppler on rooftops, a strike against a networked pane of glass, or an impact on a smart sidewalk. Even those droplets not detected could still be modelled in a vast simulation of virtual symmetry produced from a thousand points of data. A vast ecosystem of networked devices, each of which could detect pressure changes, transmit temperature, wind speed, stress and flection–not necessarily to predict the weather, but to predict infrastructure failure.

When Steven Wolfe stepped from street level into the automated limousine sent to convey him to work, the skies had only begun to darken. Now that he stepped from a rooftop onto a gondola, the wind and rain had stirred into a storm. Skirls of rain skittered across the rooftop, chasing him into the safety of the cabin. The smell of damp and rain followed him into the cramped space.

“When they gave you this job, did you expect you’d be doing this?” The man who spoke wore a dripping poncho over his expensive suit–just like Wolfe himself. Henry Combe, Wolfe’s media manager, meant the suit to look good for the ubiquitous cameras; wet fabric still displayed around his collar and along his pants where the poncho could not cover him. On his head, Combe wore a glistening white hardhat, in contrast to Wolfe’s silver hat emblazoned with the City of Paradigm emblem.

“Yes,” Wolfe said, patting Combe on the shoulder–sending a spatter of droplets into the cabin. Two city workers wearing blue overalls and hardhats winced at the spray. Wolfe gave them an apologetic look. “It’s the part where I’m doing it in the wind and rain that I didn’t expect.”

That elicited a laugh from the other occupants of the cabin as Wolfe pulled the door closed and sealed the hatch.

“A little rain never hurt anyone, First Analyst,” one of the workers said, Wolfe knew him as Mr. Herl. “Well be in and out before you know it.”

He patted a case in his lap. Inside was a section of pipe, fresh from the Industrial Works Department, 3D printed to specifications stored in the Paradigm Database. This work detail had been dispatched because the sensors in that section of pipe had shown increased pressure loads and higher stress. Combined with other sensor measurements and historical data from pumps and pipes downstream showed an increased probability of failure and soon.

Combe argued this would be an excellent time for Wolfe to show his salt to the city that appointed him to the position that would oversee the analysis of data from those sensors and, as luck would have it, sign off on work details exactly like this one.

“If I’m asking you folks to brave wind or rain or dark of night to keep this city running,” Wolfe said. “I suppose I too can handle a little rain.”

Even as the gondola carried him off into the storm, Steven Wolfe stood tall watching the gloom knowing that the cameras too were watching him.

— Excerpt from The City of Paradigm, novel by Kyt Dotson, © 2014

The City of Paradigm, California may not be a real place–but smart buildings, smart houses, and sensors as part of infrastructure may not be that far off into the future. The Internet of Things suggests that a lot of little things, each playing their part can coalesce into an understandable whole. Roads outfitted with sensors could map traffic patterns, measure wear and tear, even warn a city government before a bridge’s superstructure was going to give way (or perhaps even identify when potholes were most likely to start forming).

The big data analysis and real-time opportunity is already with us from companies such as Splunk who can give a lot of context to sensor data and information from critical city infrastructure. However, before that data can reach the database, it has to be collected, buffered, and sent over the wires or wireless and that means the software that runs the hardware eyes and ears of the Internet of Things has a technological niche to fill.

“The Internet of Things is a game-changing technological evolution, but it started many years ago,” says John Carbone. VP of Marketing, Express Logic–developers of the ThreadX embedded OS. “The Internet has always connected things, but over the years, those things have gotten smaller, lighter, less expensive, and smarter. So now, we see all sorts of things being networked, and the future will bring even more such connections.”

In the story, Stephen Wolfe finds himself elected to the position of Director of Big Data and Urban Information Analysis—a government position making him the head of the City of Paradigm Bureau of Urban Information Analysis and also why one of the repair workers jokingly calls him “First Analyst.” As more cities automate information infrastructure and connect systems that weren’t well connected before we may one day see the rise of such a position.

Big (and small) cities put a lot of people together with civil infrastructure. As a result, lots of money is spent on development and upkeep of that infrastructure and keeping the people safe—this comes out not just in means of people power, for construction crews, repair crews, and dispatchers; but also energy spent planning and directing those people.

To get a better picture of this, I spoke with urban anthropologist and Chief Technology Officer, IBM Smarter Cities, Dr. Katharine Frase, about how IBM has been part of using the Internet of Things and big data analysis as tools to assist governments and urban centers better handle their infrastructure. This all fits in very well with the IBM Smarter Cities initiative that involves using these technologies to provide better insight and automation.

As with any technology, Dr. Frase stressed that much of how we incorporate big data analysis and sensors into infrastructure should work to compel a better human experience, not to replace something that already works, but to augment it.

“The goal of a lot of computing technology has been to automate the routine and free up humans to do higher level things and the municipal use of Internet of Things is exactly a solution to this,” says Dr. Frase.

A smarter utilities example

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In the story: it’s raining. The reason for the outage that calls Director Wolfe out on repairs is presumably storm-related and many cities already face a great deal of issues in both electrical and water when storms cause damage to infrastructure. Dr. Frase talked about how IBM has been working with DTE Energy on outage prediction.

Storms already wreak havoc on electrical infrastructure—downed lines, exploded transformers, neighborhoods and houses going dark. Dr. Frase explained that the usual system is for calls to come in from customers (in the dark), dispatch receives complaints and sends out a truck to scout the region to make sure something is wrong, then after that repair crews need to be dispatched. All of this takes a while and means residents spend time in the dark during the entire process.

However, one thing that we’ve learned from Big Data is that history can help predict the future. What regions of the city suffered the most in the past year contextualized with information from the weather service about where the storm would hit the hardest can lead to insights into where to optimally position repair crews. Utilities lose some $14B in total annual service due to storms in the U.S. alone.

Utilities end-points that can “call home” when something is starting to go wrong can get a truck out to the region before the power grid goes down to take a look at what’s going on. Upstream transformers communicating back that voltage suddenly spiked could tell the utility that a tree might have just taken out a power line. All the while giving ready-information minutes before customers start scrambling for cell phones in the dark.

Smarter cities examples

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Miami-Dade County, Florida; Boston, Massachusetts; City of Dubuque, Iowa; and Desert Mountain, Arizona have all adopted smaller and more modern-world versions of what was used as a setting for City of Paradigm and are working with IBM to better manage infrastructure.

In Miami-Dade the county is facing budget cutbacks that directly effect infrastructure and utilities and the government is using IBM to help them better streamline communication. These initiatives are: Water management, transportation, intelligent policing, government transparency. The water project alone is expected to save the county $1 million per year. The initiative seeks to help agencies share information among the 35 municipalities within the county by using cloud, big data, and predictive analysis to drive better decisions.

Boston is using IBM software to closely monitor streetlights and other city infrastructure. “The software combines data from maintenance visits and inspections, enabling officials to access one consolidated view of city repair needs and make informed decisions on future repairs.” In another perfect example of using big data’s historical context to deliver predictive analysis combined with real-time data flowing in from sensors.

Arizona may be two-thirds forest, but the one-third that is a desert has Phoenix and several other major cities. This means that Arizonans have a different-than-typical understanding of drought and water usage. IBM’s work with Desert Mountain (in Scottsdale, Phoenix metro) involves six golf courses and 4,500 residents in an attempt to give them a better handle on water supply. The work hopes to reduce water use by as much as 10 percent and provide an additional 10 percent energy savings related to water pumping and distribution.

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