Urban Computing Reveals the Hidden City

Walking around a metropolis will never be the same

We want our tools to sing of not just productivity but of our love of curiosity, the joy of wonderment, and the freshness of the unknown.

—Eric Paulos, “Manifesto of Open Disruption and Participation”

Illustration: Oliver Munday

In his essay “Walking in the City,” the French scholar Michel de Certeau talks about the “invisible identities of the visible.” He is talking specifically about the memories and personal narratives associated with a location. Until recently, this information was only accessible one-to-one—that is, by talking to people who had knowledge of a place.

But what if that data became one-to-many, or even many-to-many, and easily accessible via some sort of street-level interface that could be accessed manually, or wirelessly using a smartphone? This is essentially the idea behind urban computing, where the city itself becomes a kind of distributed computer. The pedestrian is the moving cursor; neighborhoods, buildings, and street objects become the interface; and the smartphone is used to “click” or “tap” that interface. In the same way that a computer, mouse, and interface are required to operate a Web browser to surf sites, the equivalent components of street computing create a reality browser that enables the city dweller to “surf” urban objects. On a broader level, the collection, storage, and distribution of the data related to a city and its objects is known as urban informatics (described by one technologist as “a city that talks back to you”).

Smartphone in hand, what can the modern-day flaneur expect to find in this newly digitized urban environment?

• First, thanks to the prevalence of GPS data, wayfinding is giving way (so to speak) to wayshowing, interfaces that provide specific directions from here to there, and to social navigation, getting around with the help of others (avoiding traffic, for example) and then checking in with your friends when you get there. 
• Similarly, our urban gadabout might take advantage of use-someplace technologies such as augmented reality, where physical space is overlaid with virtual data. A good example is Streetmuseum, a Museum of London app that can overlay an archive photo of a street scene onto the same scene as shown through your smartphone’s camera. Beyond augmented reality is amplified reality, where extra data is built into an object from the get-go. For example, the embedding of radio-frequency identification or near-field communication technologies in street objects enables the creation of locative media (also called location-based media). These situated technologies contain data about a specific location, which is then beamed to devices as they come within range, an exchange known as a situated interaction. An example is the sound garden, where designers assign sounds to public places, which users can then listen to using Wi-Fi–enabled devices.

There is, sadly, the ever-present danger that advertisers and hucksters will take advantage of these technologies to turn the city into a giant billboard. But to the technologists and social scientists at the forefront of urban computing, the goal is enhanced civic engagement. To that end, where once the ideal of pervasive computing was to create seamless, unnoticeable technology, today’s urban computing designers want to build seamful interfaces, whose visibility encourages users to interact directly with systems. Curatorial media allow for urban data curation, the careful collection of stories—histories as well as facts and figures—using technologies called urban annotation systems. Since data are both curated and disseminated in such systems, this is known as read/write urbanism.

Is the urban computer a good thing? Well, it’s certainly an inevitable thing, so I wouldn’t waste too much breath complaining about it. Think about a regular PC: You can turn it off, or you can use it for fun or for productivity. The urban computer is no different. You can ignore it (turning a city off is problematic), or you can use it to become a more attentive, engaged, and concerned citizen. It’s a tool. Make it sing.

Urban Computing, Part II

The Language of Smart Cities

As in all Utopias, the right to have plans of any significance belonged only to the planner in charge.

Jane Jacobs, The Death and Life of Great American Cities (1961)

Illustration: Oliver Munday

In a previous column, I ran through some words and phrases associated with urban computing, where

• the city is a computer, 
• the streetscape is the interface, 
• you are the cursor, and 
• your smartphone is the input device. 

This is the user-based, bottom-up version of the city-as-computer idea, but there’s also a top-down version, which is systems-based. It looks at urban systems such as transit, garbage, and water and wonders whether the city could be more efficient and better organized if these systems were “smart.” That is, if we applied principles of information technology and connectivity to the various processes that make up the urban infrastructure, we would end up with a smart city.

The need for more urban smarts seems obvious:
Cities have finite (and shrinking) budgets, and the resources that make a city run—including water, energy, clean air, and land—are precious. So the move from the current urban environment to the digital city includes upgrading components and retrofitting so-called smart technologies. For example, many urban homes have had their gas and electrical meters upgraded to smart meters that enable not only remote monitoring and reading but also smart pricing (or time-of-use pricing), where costs rise or fall depending on whether usage is on- or off-peak. On a larger scale, these newfangled meters are part of the smart grid, which uses real-time data and analytics to match energy production with demand, monitor equipment, and control supply.

Big data plays a big part in smart urbanism because city managers are starting to create a networked city that deploys digital sensors and other electronic infrastructure. These generate massive amounts of information not only on energy use but also on traffic, transit, and other civic data. The goal is the real-time city, which enables planners and administrators to make decisions and implement policies based on current data and trends. Call it city 2.0.

Eventually (so the blue-sky thinking of your average civic hacker goes), these sensors, monitoring devices, and other elements of urban technological infrastructure will cover almost every available public surface. The result will be the ubiquitous city (often shortened to u-city), where every urban system and resource will make its data available for monitoring, analysis, and control. This transphysical city will enable new services to be implemented seamlessly over the network or via the g-cloud (government cloud), a computing model sometimes called city-as-a-service.

The ultimate smart city is one that’s built from the ground up with civic tech goals in mind. The forerunner here is the Garden City model proposed in the late 19th century by Englishman Ebenezer Howard, which features parks, retail, residences, and industry organized in concentric circles. The modern equivalent of a built-from-scratch smart city is called a cyburg, and examples include:

• Songdo in South Korea, 
• Masdar City in the United Arab Emirates, and 
• the proposed, pedestrian-only Great City in China. 

These cities are planned for efficiency and are wired for data and services—cityware—all controlled by an urban operating system. Citizen access to these services is networked and ubiquitous, thanks to the implementation of civic tech.

The problem with these soft cities (or e-cities) is that, like Howard’s Garden City, the benefits accrue only if the whole thing remains under the strict control of an overarching authority that dictates things such as land use and density. But, as urban critics such as Lewis Mumford, Jane Jacobs, and more recently Richard Sennett have pointed out, a city is almost by definition an organic entity that constantly changes and evolves. To define this aspect of urbanism as a bug that must be fixed strikes at the soul of the city, because it sees commercial and individual freedom as the problem, not the solution. And if the increasing ubiquity of networked monitoring devices—particularly CCTV cameras—is combined with databases and software that enable easy searching and analysis, then the time of the superpanopticon is nigh. That kind of city doesn’t sound very smart to me.

This article originally appeared in print as “The City as System.”

ORIGINAL: IEEE Spectrum (Part I)

By Paul McFedries

27 Jan 2014

IEEE Spectrum (Part II)

By Paul McFedries

26 Mar 2014

Augmented reality turns drivers into a car mechanic

Augmented reality - technology which takes virtual objects and layers them on top of live camera images - is being used by the car industry to help design the next generation of cars.

Click's Dan Simmons visits Audi's research headquarters in Germany to find out how the company is using the technology and looks at some of the augmented reality apps which could help drivers fix problems without needing to consult a manual.

How augmented reality is aiding car design and helping drivers fix problems without a manual.
ORIGINAL: BBC

Smart Contact Lenses Will Give You Superhuman Vision

LAS VEGAS — Your future contact lenses could give you superhuman vision.

Just one year after eyewear startup Innovega announced a prototype of its high-tech iOptik lenses, the company is showing off the product at this year's International CES.

The Innovega eyewear system is made up of two parts: glasses and contact lenses. The contact lenses give you enhanced focusing abilities, so you can see near and far at levels beyond what the normal eye can see. For example, if you put a finger up to your eye while wearing the contacts, you can actually see the fine details of your fingerprint; whereas, the natural eye can't focus on an object so close up.

When you put on the accompanying glasses, which include flat-panels or micro-projectors that can display apps and media, they create a Google Glass-like experience. Putting on the contact lenses under the glasses will further enhance your vision.

So why didn't Innovega blend the contacts and glasses technology into one solution? "A lot of companies are trying to do that right now with hardware, and there are limitations: It creates a tiny field of view," an iOptik spokesperson told Mashable. "Google Glass is the equivalent of having your smartphone about 24 inches in front of you. The iOptik system is six times the resolution and 20 times the area. It's like looking at a big TV projection, and you can see so much more."

Smart eyewear such as Google Glass would look more like goggles if the near- and far-vision technology were placed within the device, according to the spokesperson. By pairing the contacts with the iOptik glasses, it still looks like you're wearing regular glasses. You also have the option of filling the contact lenses with a prescription.

"We're hoping technology like this will eventually replace your smartphone," the spokesperson said.

Homepage image: Leon Neal/Getty Images; other images: Mashable 

Topics: Google Glass, Google Glass, Mobile, Tech, wearables

ORIGINAL: Mashable

By Samantha Murphy Kelly

Key MS engineer leaving the company to join Google

Blaise Agüera y Arcas, now a former engineer at MS has left the company to join Google for his future work. He has quite the name at MS and will surely be missed. Blaise Agüera y Arcas originally joined MS in 2006 when his startup company Seadragon was bought.

Blaise Agüera y Arcas helped develop several key things at MS such as Bing Maps service and newly launched image-stitching Photosynth software. According to a report from New York Times, the former-MS engineer will continue his career at Google and will help the search giant on machine learning. This is another area that MS has been focusing heavily in recent months. Losing a key engineer at this time is unfortunate for MS, however, Google can rejoice as it has won over a very important individual.

In Blaise Agüera y Arcas’s blog post, he says that “it’s painful to leave behind so many won­der­ful ongo­ing projects, and even more so to leave behind such a great team.“ He continues on to say that leaving MS was “the hard­est deci­sion of my life.“ This isn’t a surprise seeing as he has spend quite a number of years at MS. After all, if you work at a place for many year, you tend to develop a bond not only with the coworkers, but also with the company.

Employee poaching is very common amongst big companies. There have been agreements made between companies such as Google, MS and Apple, however at times, the agreement is broken. Perhaps this is one of those times. Nonetheless, Google has gained a key engineer that help with its future successes.

Want to see the new Photosynth in action? Click on this image of St. Bonaventure Church to give it a road test.

ORIGINAL: Tech Savvy

by Hamza K
Dec 16, 2013

Think Google Glass is cool? These specs can see through your skin

We’ve all been there: Sitting awkwardly on a doctor’s table, as a nurse stabs you repeatedly, trying to find a vein to draw some blood. It’s painful – and it could soon become a thing of the past, thanks to a nifty pair of x-ray glasses from Silicon Valley-based imaging firm Evena Medical.

Evena’s Eyes-On Glasses enable nurses (or any other user) to clearly see the veins beneath your skin, and choose the “best” vein for whatever reason a nurse might need to stick you with a needle. Eyes-On is similar to other medical devices made by Evena – but those are big, and need to be carted from room to room. Eyes-On can be worn like a pair of Google Glass, presumably making the process all that much easier.

“Studies have shown that up to 40 percent of IV starts require multiple attempts to locate and access a vein, which not only wastes valuable nursing time but also delays therapy and causes patient discomfort and dissatisfaction,” said Frank Ball, Evena Medical President and CEO, in a statement. “With Evena’s Eyes-On Glasses, nurses can quickly and easily locate and access the best veins for each patient – even in challenging clinical environments such as pediatric or neonatal units.”

The tech that gives Eyes-On Glasses their x-ray superpowers comes from Epson (yes, the same Epson that makes printers). The company’s Moverio smartglasses technology gives users a taste of augmented reality thanks to its transparent display that “projects overlays of digital content onto the real-world in the center of the wearer’s field of view … enabling a seamless blend of the physical and digital worlds,” according to Evena.

The Eyes-On Glasses also packs on-board storage for saving images of patients’ vein patters, and “telemedicine” capabilities (probably Wi-Fi) that let nurses easily share the images with doctors straight from the device.

Evena expects to start shipping Eyes-On Glasses in the first quarter of 2014, so don’t be surprised when your nurses walk in looking like they just came off the set of an 80s sci-fi movie.

Check out a (slightly disturbing) video of Eyes-On in action below:

Evena Eyes-On™ Glasses The newest addition to the Evena family of products is the one-of-a-kind point-of-care wearable Eyes-On™ Glasses system. Evena Eyes-On Glasses provide all the same imaging technology advantages as other Evena products, but in a cost-effective, cart-free, wearable form. The Evena Glasses system is appropriate for pre-hospital, physician offices, clinics or hospitals. The Glasses unit is battery powered and offers the ultimate in portability and ease of use.
Unique Eyes-on Glasses features include:

• Multi-Spectral Imaging - a breakthrough patented technology developed by Evena for the deepest penetration with the most detailed and sharpest image is effective for almost all physiologies.
• Real-time anatomically accurate images – no other system provides such exceptionally clear, accurate images.
• EMR/PACS interface enables automated, improved and more precise documentation of appropriate care, including verification of vein patency.
• Hands-free, cart-free, wearable technology allows medical staff to maneuver anywhere anytime with the complete vasculature image right before their eyes.
• See-through, Eyes-On technology allows the user to have full situational awareness, to keep eye contact with the patient plus a clear view of the patient’s area of interest, enabling quick and easy location and access to the best vein.

Evena Sparrow is not available in the U.S., EU and many other developed nations

ORIGINAL: Digital Trends; Evena

By Andrew Couts 

November 20, 2013

Meet Genesis Angels, A New $100M Fund For AI And Robotics, Co-Founded By Investor Kenges Rakishev And Chaired By Israel’s Ex-PM

ORIGINAL: TechCrunch
Ingrid Lunden
Friday, April 19th, 2013

 

For those startups in newer areas like robotics, artificial intelligence and augmented reality who complain that VCs are too focused on consumer internet companies, help is at hand: Genesis Angels is a new VC that has raised a fund of around $100 million, with a large chunk coming from co-founder and serial investor and Kazakh petrochemical mogul Kenges Rakishev, which it plans to use for early stage investments in emerging areas like these and others. Based in Israel, but looking for startups worldwide, Genesis launched just this week, naming ex-Israeli prime minister Ehud Olmert as its chairman.

Moshe Hogeg, the other co-founder behind Genesis Angels (and founder and CEO of mobile video/photo startup Mobli, pictured here with Rakishev, left, and Olmert, center), says that the idea for Genesis came out of his and Rakishev’s observation that while the market for consumer internet services is saturated with a lot of me-too companies, there is a flourishing world of R&D in areas like robots and artificial intelligence that is not getting enough attention. It’s mostly giant tech companies like Google and Microsoft and academic institutions that are putting money into the very cutting edge of technology.

(Indeed, it was just yesterday, during Google’s earnings call, that CEO Larry Page talked about the “big bets” that Google wants to make on new technology. Google is not afraid to make big investments, he said, because the fear is that if it doesn’t it may miss out on the next big thing.)

The problem with this is that it leaves little room for startups. And although more recent developments like Kickstarter and Indigogo are creating a new groundswell of interest and financial support for some of these projets, there are yet others that will not want that kind of public profile for what they’re working on.

Hogeg describes Genesis’ role as something between the concept stage and when a VC may typically become interested in a company working on cutting-edge technology. “You can send the most brilliant scientist to a VC, but often it might take that scientist and his startup five years to create their products,” he explained in an interview. “VCs will say, ‘No problem, come back in four years.’ Genesis will invest in those companies in the meantime.” Typical investments will be in the range of $200,000 and $2 million.

If you visit Genesis Angels’ site, you will see that it already lists a number of companies in its portfolio, including Hogeg’s. These are listed, he says, because they are some of the investments Rakishev himself has made. Genesis, he notes, is still raising money for its first fund, with the total in play currently close to $100 million. Among those contributing to the fund are merchant bank Forbes & Manhattan, as well as private individuals who are well-known in the space of angel investments specifically around areas like hardware and new technology. The first three investments that are being made out of the new fund, Hogeg says, will be coming out shortly.

Ehud Olmert’s appointment as chairman is about laying the groundwork for the kind of assistance that Genesis Angels will be able to offer its portfolio companies, Hogeg says.

“He is a big believer in technology. Irasel invested the most in this area when he was still prime minister,” he notes. The relatively small country currently has some 3,000 tech companies, according to this report from the AP on the launch of the new VC.

Olmert took office in 2006 but left in 2009 under a corruption scandal cloud that he is still fighting. But that, apparently, has not affected his wider influence. “Mr Olmert is a very powerful man and he can use his contacts to help us and our companies, for example in partnering and joint ventures. He can open any door in the world.”

There have been other VC funds focused on these emerging areas. Dmitry Grishin, for example, the CEO of Mail.ru and founder of Grishin Robotics, last year started a $25 million fund dedicated to investing in other robotics companies (examples of his investments here, here and here).

It may be that Genesis teams up with people like this to cooperate on investments. “He shares a vision with us about this space,” says Hogeg.

Modeling the human brain: Are we more than the sum of our parts?

ORIGINAL: Research At Google

How does the human brain work? What is happening when the brain generates cognitions? One way to think of the brain is as a series of connected systems, with brain function emerging from the various “network” connections that exist between neurons. During the last several decades, there has been an explosion of methods one can use to measure and quantify network operations in the human brain, and yet how the brain and its structure uniquely allows an individual to sleep, generate emotions, and create innovative ideas, remains an open area of research with many unanswered questions.

Recently, University of Toronto Psychology Professor Rotman Research Institute (http://goo.gl/UtX6QF) Director Randy McIntosh (http://goo.gl/oW2rnB) spoke at Google about The Virtual Brain (TVB, http://goo.gl/ghluhB),

an international project that uses real neuroimaging data to construct a simulation of the human brain, with the goal of regenerating via simulation the data that is measured when an actual human being is thinking. By doing so, TVB aims to provide a means to merge available neurophysical data with the goal of understanding what it is about the “function-structure confluence” in a brain that forms the basis of cognitive architectures.

Watch a brief synopsis of TVB below as well as the longer talk given at Google at http://goo.gl/DyohPh, which includes a peak at a side project called My Virtual Dream, in which small groups of people interact with TVB through wireless EEG headsets, modifying an immersive audiovisual environment that mimics a dream and augmenting the group experience.

Artificial Intelligence Is the Most Important Technology of the Future

ORIGINAL: Maria Konovalenko Blog
Maria Konovalenko
July 30, 2013 · 16:36

Artificial Intelligence is a set of tools that are driving forward key parts of the futurist agenda, sometimes at a rapid clip. The last few years have seen a slew of surprising advances: 

• the IBM supercomputer Watson, which beat two champions of Jeopardy!; 
• self-driving cars that have logged over 300,000 accident-free miles and are officially legal in three states; and 
• statistical learning techniques are conducting pattern recognition on complex data sets from consumer interests to trillions of images. 

In this post, I’ll bring you up to speed on what is happening in AI today, and talk about potential future applications. Any brief overview of AI will be necessarily incomplete, but I’ll be describing a few of the most exciting items.

The key applications of Artificial Intelligence are in any area that involves more data than humans can handle on our own, but which involves decisions simple enough that an AI can get somewhere with it. Big data, lots of little rote operations that add up to something useful. An example is image recognition; by doing rigorous, repetitive, low-level calculations on image features, we now have services like Google Goggles, where you take an image of something, say a landmark, and Google tries to recognize what it is. Services like these are the first stirrings of Augmented Reality (AR).

It’s easy to see how this kind of image recognition can be applied to repetitive tasks in biological research. One such difficult task is in brain mapping, an area that underlies dozens of transhumanist goals. The leader in this area is Sebastian Seung at MIT, who develops software to automatically determine the shape of neurons and locate synapses. Seung developed a fundamentally new kind of computer vision for automating work towards building connectomes, which detail the connections between all neurons. These are a key step to building computers that simulate the human brain.

As an example of how difficult it is to build a connectome without AI, consider the case of the flatworm, C. elegans, the only completed connectome to date. Although electron microscopy was used to exhaustively map the brain of this flatworm in the 1970s and 80s, it took more than a decade of work to piece this data into a full map of the flatworm’s brain. This is despite that brain containing just 7000 connections between 300 neurons. By comparison, the human brain contains 100 trillion connections between 100 billion neurons. Without sophisticated AI, mapping it will be hopeless.

There’s another closely related area that depends on AI to make progress; cognitive prostheses. These are brain implants that can perform the role of a part of the brain that has been damaged. Imagine a prosthesis that restores crucial memories to Alzheimer’s patients. The feasibility of a prosthesis of the hippocampus, part of the brain responsible for memory, was proven recently by Theodore Berger at the University of Southern California. A rat with its hippocampus chemically disabled was able to form new memories with the aid of an implant.

The way these implants are built is by carefully recording the neural signals of the brain and making a device that mimics the way they work. The device itself uses an artificial neural network, which Berger calls a High-density Hippocampal Neuron Network Processor. Painstaking observation of the brain region in question is needed to build a model detailed enough to stand in for the original. Without neural network techniques (a subcategory of AI) and abundant computing power, this approach would never work.

Bringing the overview back to more everyday tech, consider all the AI that will be required to make the vision of Augmented Reality mature. AR, as exemplified by Google Glass, uses computer glasses to overlay graphics on the real world. For the tech to work, it needs to quickly analyze what the viewer is seeing and generate graphics that provide useful information. To be useful, the glasses have to be able to identify complex objects from any direction, under any lighting conditions, no matter the weather. To be useful to a driver, for instance, the glasses would need to identify roads and landmarks faster and more effectively than is enabled by any current technology. AR is not there yet, but probably will be within the next ten years. All of this falls into the category of advances in computer vision, part of AI.

Finally, let’s consider some of the recent advances in building AI scientists. In 2009, “Adam” became the first robot to discover new scientific knowledge, having to do with the genetics of yeast. The robot, which consists of a small room filled with experimental equipment connected to a computer, came up with its’ own hypothesis and tested it. Though the context and the experiment were simple, this milestone points to a new world of robotic possibilities. This is where the intersection between AI and other transhumanist areas, such as life extension research, could become profound.

Many experiments in life science and biochemistry require a great deal of trial and error. Certain experiments are already automated with robotics, but what about computers that formulate and test their own hypotheses? Making this feasible would require the computer to understand a great deal of common sense knowledge, as well as specialized knowledge about the subject area. Consider a robot scientist like Adam with the object-level knowledge of the Jeopardy!-winning Watson supercomputer. This could be built today in theory, but it will probably be a few years before anything like it is built in practice. Once it is, it’s difficult to say what the scientific returns could be, but they could be substantial. We’ll just have to build it and find out.

That concludes this brief overview. There are many other interesting trends in AI, but machine vision, cognitive prostheses, and robotic scientists are among the most interesting, and relevant to futurist goals.

I would like to thank Michael Anissimov, a fellow transhumanist and author of the Accelerating Future blog, for contributing this piece.