Tag: smart cities

Who pays for smart cities?

This post was originally published by TDWI (The Data Warehousing Institute) as a Flashpoint feature on January 12, 2018.

One recent sunny morning there was a traffic jam on Cottage Street, a narrow street within view of my house, aptly named for its width. Commuters heading toward the nearby bridge over San Francisco Bay found themselves inching forward after their “smart” navigation devices had sent them on a shortcut.

The trouble with “smart” tech is that it starts out stupid. Users and neighborhoods suffer inconvenience to train developers’ algorithms—which is one part of to a common question about smart cities: “Who pays?” After all, most cities can’t afford the out-of-pocket expense for the fancy new technology. Instead, cities find other ways to get it and many of those involve compromise.

Financial capital does seem to be available. Smart Cities Financing Guide, published by the Smart Cities Council in 2015, lists 31 potential sources in three broad categories. Two of them put money under city control. Government-based funding includes, for example, general obligation bonds. These raise money from private bond buyers and are paid back mostly by taxes. A second category is called “development extractions,” which show up as tap fees, charged for new utility hookups, and other direct fees.

A third category—public-private partnerships—complicates the whole “who pays?” matter. In such arrangements, vendors provide technology in exchange for market presence (a fertile ground on which develop their technology) and often ownership of the data that results.

Navigating Competing Agendas

Naturally, the public and private sides of the bargaining table come with conflicting priorities. The private side has to satisfy regulatory and funding requirements and perhaps also a few broad mandates from top city leadership. One unspoken mandate is to keep the citizens happy. Citizen groups, at least the effective ones, persistently and perhaps dramatically advocate their various agendas. Better street lighting, better transit, and better protections for privacy and other causes exert steady pressure. Now and then, an ad hoc uprising may object to letting modern travel-direction apps clog horse-and-buggy-era streets.

On the other side of the table, technology vendors want a place to perfect technology, reap data, and build reputations. “[Technology vendors] believe that this will be a big market,” said Todd Walter, in Internet of Things marketing at Teradata, itself an interested vendor. “They all want to sell their stuff to the projects beyond the pilots and proofs of concept.” Vendors have already gone on their own to build or schedule such projects as “smart buildings” in which analytics finely tunes heating, cooling, and other basic functions; “smart” utility grids; integration of interagency emergency systems; data sharing among taxis and public transit; on-street video security; and video toll booths.

The two sides can seem farther apart than a mere table’s breadth. “When public and private sectors get together,” said Peeter Kivestu, Teradata director of travel industry solutions and marketing, “the public sector thinks they’re sitting across from a bunch of sophisticated hustlers who’re going to rip them off. The private sector thinks they have a bunch of public sector guys who can’t be trusted to achieve consistency because of the political and policy flows that go on.”

The Winding Road to Infrastructure ROI

Some vendors avoid any such involvements. Some telecommunication carriers, for example, are funding their own upgrades. So far, it looks like their networks will be the backbone of “smart.”

“[Smart systems] are very chatty,” said Dennis Duckworth, a product marketing and strategy consultant who’s recently worked with telecommunication carriers. “You take those maps and there are millions and millions and millions of [bits transmitted], and they’re taking up a lot of aggregate bandwidth.” During the long retrofit for beefier networks, there will be no shutting down. The rolling-upgrade will be expensive, and the carriers have to monetize the new, beefier networks somehow.

That payback, explained Duckworth, may well start not directly from the carriers but through appliance purchases by consumers. New, so-called “smart refrigerators” will signal to a mother ship, “Hey, my ice maker is faulty. Send a new one!” For that, the consumer will pay a little bit extra even when a “dumb” refrigerator might do just as well. Even the everyday water pipe will come with sensors built in, said Duckworth, whether you can use them or not.

Why do the carriers go to the trouble? They want the data, explains Duckworth. They’ve been watching Google and Facebook reap data that now flows over the telcos’ lines. The carriers want to play, too.

As any streetwise city dweller knows, those who pay call the shots. The only difference is that now the answer to “who pays” may also tell you who controls the technology and the data.

Smart cities / Cisco’s smart pipes plus Teradata’s scary-smart tech

Cisco’s smart plumbing will feed Teradata’s brains, says last week’s announcement. That sounds like a no-brainer except for what Teradata only hints at.

Start with this: Take Teradata’s new Customer Journey and skew the technology away from large commercial organizations and point it toward cities.

That extra-smart beast wouldn’t just swallow Cisco’s data and feed it back into pretty dashboards. It would ingest any data anyone could possibly feed it and, with machine-like intimacy, take care of anyone who opts in, person by person, moment by moment. Each individual’s likes, dislikes, cravings, emergencies, plans, and tribes might all be sensed and considered from the vast and disparate range of data. It would guide, suggest, nudge, and remind individuals in real time, not sorta real time, with texts, emails, or calls. But only for those who opt-in, I assume.

But opt in to exactly what? It’s still early, and for now I doubt if even the real dreamers among us can see the full possibilities. To glimpse where it could go in smart cities, consider what Customer Journey does in the commercial world. A bank, for example, sees a customer spend an hour on the mortgage calculator and then drop it. It may ask why. It offers help. It might offer calibrated incentives. Or imagine a telco that knows what each customer wants who calls the call center even before rep says hello. The beast watches, knows, predicts, and prompts.

It’s not just the dreamers whose imaginations work on this, it’s those with nightmares, too. I’ve worked with some. These ever-vigilant citizen activists in every city will speak articulately in forums that matter. I know this class, having lived among them and having edited media published by environmental organizations they helped lead.

Here, they at least will have legitimate questions. Who will ensure that the the beast behaves? How can anyone be sanguine, especially with today’s threat to American democratic norms coming from the White House? What’s the cost to our culture of supplanting traditional methods with this stuff?

It’s a reason to use all public means to manage the technology, which won’t be stopped. After all, it’s just technology — no different from oil, electricity, or computer networking. Applied with transparency, the beast can can provide a catalyst for collaboration with which cities thrive.

“Smart” starts with context

Imagine two marketing people sitting across a table from a data analyst. Marketing wants “simple numbers,” they say, and the analyst understands. The three of them know all the past conversations, the questions that arose and were answered, the points that got made, the conclusions or unresolved questions that remained.

Easy enough. But now with the rise of so-called “smart cities,” where the data spigots open and everyone with any point of view at all takes part, things can get into a mess. There, the starkly disparate points of view, which in business get talked through in relative calm, really show teeth.

Imagine the scene: From the city might come staff analysts, department heads, even elected officials. From the public come experts from interest-groups, grassroots politicians eager to make a name for themselves, owners of mom’n’pop stores, or even the even the grandmother who’s mad as hell. Each side — there may be several sides, and even divisions within each one — may have never set eyes on the other before, though some may know each other from decades of work together. Everyone’s got a different idea of past conversations, or no idea at all.

If only they had a nice, simple tool — as simple as a book, notepad, or whiteboard but also available for fast searches before meetings or quick refreshers on a tablet held just out of view from everyone else. Something as simple as — to use a metaphor by Alation vice president of marketing Stephanie McReynolds — a bicycle. You could walk across town, but it’s a lot easier on a bike. It has no hidden parts. Like any good machine, it makes more of whatever effort you exert.

Past conversations — rich with context, observations, and ideas — can be preserved and studied. Then those who like “simple numbers” might really talk.

“Smart” starts with context. Real decisions, no matter what data anyone has, still takes place among people — every one of whom has to know the context of any decision they’re part of.

A fun, lively path to smarter cities

San Francisco-area designer Steve Pepple wondered whether data could help him explore neighborhoods — on the way to helping city planners build better, perhaps “smarter” cities.

He describes in a fun post on Medium, a genuine “data story,” how he set out to help people find “pockets of activity, vibrance, and new things.”

First, he joined a do-it-yourself project called Sense Your City. Sensors around the world reaped “hyper-local data about environmental conditions, such as noise, dust, light, and pollutants.” That data led to “pockets of activity, vibrance, and new things.” In San Francisco, he writes, “you could see when the fog rolls in.”

That sounds like fun, but could he find a key insights about mobility, housing, or neighborhood change? He had frustrating moments. “I had a bunch of data to work with,” he writes. His many sources included DataSF, San Francisco Planning, SPUR, and the City of Oakland. But he didn’t know what he was doing. Perhaps worse, “I was stymied by trying to find a significant, cumulative insight by cobbling together and analyzing all the data.”

He had been inspired by one man’s discovery who famously found such an insight in San Francisco rental data. Eric Fischer had pored over newspaper ads back to 1948 and surprised urbanists with his conclusion: the usual levers for regulating demand wouldn’t solve the city’s housing crisis.

Smaller experiments

With no big discoveries in sight, Pepple turned to shorter experiments. Apparently as part of a fellowship with Stamen Design and Gray Area Foundation for the Arts, he looked at Instagram photos to track street movement, such as some taken during the 2015 Pride Parade. Data from those photos showed events like parade formation and, in the afternoon, a drift into block parties.

His Medium post includes a short series of visualizations that are more fun and vibrant than you might think any “smart city” has a right to be. With “color quantization,” he created a “spatial database of color” that showed parks and murals in the Mission District. In another map, colors expressed “density of people and establishments,” with brighter and more colorful buildings showing the most active.

Tangible, street-level meaning came in large, street-level screens…that showed passersby how they could “interact with data about their neighborhood and arrive at their own discoveries.”


It was his work with the urban designers and architects Perkins + Will that his approach had what I find the most interesting and possibly the most meaningful clue. Pepple and team could see and hear neighborhoods with the most activity. Could that be found with data? Indeed, data tracked activity and what people said about the places where it occurred; social media helped characterize those places; mapping tools connected hotspots.

A look at the maps Pepple and team produced shows that transit, living space, restaurants, and other amenities fail to anchor social hotspots. Fine, but why? If the data can reveal this, perhaps it can go the rest of the way.

Keep your eye on Pepple. His playful and often fun analysis puts a bright, even inspiring face on urban data.

Thanks to Stephanie Langenfeld McReynolds, vice president of marketing at Alation, for alerting me to Pepple’s work.

improved urban decision making

…the smart city movement is less about technology and more about improving the way decisions are made in large urban areas, where the demand for services is increasing and the availability of resources is diminishing.”

Michael Flowers, as interpreted by Mike Barlow in a 2015 O’Reilly report, Smart Cities, Smarter Citizens. Flowers is now chief analytics officer at Enigma.io.