The U.S. mobile industry claims it's desperate for new spectrum.
But when the FCC opened it's first mobile broadband airwave
auction in a half a decade, not a single major carrier participated.
As reported by GigaOM: For the first time in half a decade, the Federal Communications
Commission on Wednesday opened up bidding on a new spectrum auction,
releasing new airwaves for 3G or 4G data services to potential buyers.
But you would hardly know it, judging from the lack of interest across
the mobile industry.
Not a single one of the four nationwide providers is participating in what is now known as Auction 96,
which is distributing 10 MHz of frequencies in the 1900 MHz PCS band
nationwide. That’s not exactly the kind of behavior you’d expect from an
industry that insists it faces a spectrum crisis of the direst order.
Granted 10 MHz isn’t much in the grand scheme of things. It’s enough
to add incremental 3G capacity or deploy an LTE network half the size of
what most major operators have in the field today. But bandwidth is
bandwidth. Yet the major carriers have decided to take a pass on these airwaves, looking ahead to the FCC’s big incentive auction next year. If done right, that auction could open large chunks of frequencies in the much more desirable 600 MHz band.
So who is participating in Auction 96?
Dish Network is probably the one name you’ll recognize, but a lot of
smaller carriers are also submitting bids in hopes to add to their
regional holdings. In three rounds, bids now total $221 million. As you
would expect, licenses in the big cities are attracting the most
interest. The New York City license alone has attracted one quarter of
all bids so far, followed by Los Angeles and Chicago.
The auction is just getting started, and it doesn’t run at quite the
fast pace as estate sale. The FCC holds three bidding rounds each day
until there are no more bids. This auction certainly won’t be the
two-month-long process we saw in 2008 for the highly contested 700 MHz
airwaves. We’ll probably see this auction conclude in a few weeks if not
less.
Lockheed Martin launched the GPS IIR/M satellites between 1997 and 2009, and the fleet accounts for more than half the 36 GPS birds on orbit with batteries, the “the primary life-limiting component when GPS IIR/IIR-M vehicles are past their design life,” SMC said.
Aerospace Corp., a federally funded research and development center with extensive GPS expertise, Lockheed and SMC determined that reducing the charge rates during solstice season would add an average of one to two years of life per space vehicle.
Last week, the 2nd Space Operations Squadron, Schriever Air Force Base, Colo., completed the battery charge modification, which will extend the life of each of the GPS IIR/IIM satellites by one to two years, more than 27 years of cumulative life across fleet, SMC said.
The changes represent a savings of hundreds of millions of dollars for the US government.
As reported by ReadWrite: Today’s new cars are loaded with sensors and powerful computer
processors. That’s the high-tech pathway to turning our vehicles into
super-efficient, semi-autonomous—or even self-driving—"transportation
devices."
Unfortunately, the roads these clever mobility machines drive on are
all too often, well, dumb. You experience the pain of this problem every
time you senselessly wait for an extra couple minutes at a red light,
when there are no other cars in sight from any direction.
Samah el-Tantawy, a recently minted PhD of Engineering from the University of Toronto, wants to change that.
Inspired by research from her advisor and director of the Toronto Intelligent Transportation Systems Centre, Professor Baher Abdulhai,
el-Tantawy devised a system that uses artificial intelligence and game
theory that, in a simulated environment, shaved 40% of the time off an
average wait at an intersection. She said that could mean 12.5 fewer
minutes stuck in your car, if you pass through about 30 intersections on
your commute.
Can We Talk?
According to el-Tantawy, many of today’s traffic lights at
intersections operate based on pre-programmed repeated cycles that run
with little or no input from fluctuations in traffic. Yes, there are
sensors in pavements along major arteries, but those inputs into
centralized systems might only be able to extend a green light for a few
seconds. Like other centralized disconnected top-down systems, there
are inherent limitations.
Instead, el-Tantawy’s system—dubbed MARLIN for Multi-agent Reinforcement Learning for Integrated Network
(of Adaptive Traffic Signal Controllers)—uses video cameras, other
vehicle data inputs (if available), processing power, and routers to
analyze how many drivers are zipping through the intersection and how
many are simmering with road rage for wasting countless minutes at a red
light. With MARLIN, cameras are aimed at all four approaches, and the
system is distributed throughout a region rather than just on main
streets.
“Our approach is decentralized, where the intelligence or math to
assign the greens is done on the fly at each intersection,” she told
me. “The brain sits at each intersection, and calculates the best
timing to minimize the number of cars approaching and waiting, and it
coordinates those decisions with other lights at other intersections.”
The Shortest Wait Wins
El-Tantawy said no amount of math can perfectly model every
situation. There are too many variables. The solution? “Each
intersection is connected to the neighboring or adjacent intersection,
sending and receiving information about the waiting vehicles,” she
said. Then, “reinforcement learning” comes into play.
Like a
child learning to walk by making minute adjustments, each traffic
light—or “agent,” as el-Tantawy calls them—makes a decision every second
about the best way to keep motorists and pedestrians waiting for as
short a period as possible.
“The agents learn, until they converge, with each one getting the
best response action to achieve its goals, without negatively affecting
the others. We use multi-agent reinforcement learning,” she said. “And
it cascades throughout the system. The decisions by agents affect each
other, so it’s a game.”
The system has to be simulated in a test
environment before being placed in the street, where the learning can
continue in real-world conditions. So far, MARLIN has only been used in a
test environment—but with great results. That encouraged el-Tantawy and
Professor Abdulhai to recently form a start-up traffic tech company to
commercialize the system, and get it on as many streets as possible.
It's easy to see how this AI-powered traffic light system could be a
major boost to a region's productivity, justifying the anticipated cost
of about $20,000 to $40,000 per intersection.
el-Tantawy said her
start-up will soon sign up its first municipality to run a field test,
but wasn’t ready yet to disclose the location. I hope it’s in my
neighborhood.
What's the point of all that data, anyway? It's to make decisions.
As reported by MIT Technology Review: Back in 1956, an engineer and a mathematician, William Fair and Earl
Isaac, pooled $800 to start a company. Their idea: a score to handicap
whether a borrower would repay a loan.
It was all done with pen and paper. Income, gender, and occupation
produced numbers that amounted to a prediction about a person’s
behavior. By the 1980s the three-digit scores were calculated on
computers and instead took account of a person’s actual credit history.
Today, Fair Isaac Corp., or FICO, generates about 10 billion credit
scores annually, calculating 50 times a year for many Americans.
This machinery hums in the background of our financial lives, so it’s
easy to forget that the choice of whether to lend used to be made by a
bank manager who knew a man by his handshake. Fair and Isaac understood
that all this could change, and that their company didn’t merely sell
numbers. “We sell a radically different way of making decisions that
flies in the face of tradition,” Fair once said.
This anecdote suggests a way of understanding the era of “big
data”—terabytes of information from sensors or social networks, new
computer architectures, and clever software. But even supercharged data
needs a job to do, and that job is always about a decision.
In this business report, MIT Technology Review
explores a big question: how are data and the analytical tools to
manipulate it changing decision making today? On Nasdaq, trading bots
exchange a billion shares a day. Online, advertisers bid on hundreds of
thousands of keywords a minute, in deals greased by heuristic solutions
and optimization models rather than two-martini lunches. The number of
variables and the speed and volume of transactions are just too much for
human decision makers.
When there’s a person in the loop, technology takes a softer approach (see “Software That Augments Human Thinking”).
Think of recommendation engines on the Web that suggest products to buy
or friends to catch up with. This works because Internet companies
maintain statistical models of each of us, our likes and habits, and use
them to decide what we see. In this report, we check in with LinkedIn,
which maintains the world’s largest database of résumés—more than 200
million of them. One of its newest offerings is University Pages, which
crunches résumé data to offer students predictions about where they’ll
end up working depending on what college they go to (see “LinkedIn Offers College Choices by the Numbers”).
These smart systems, and their impact, are prosaic next to what’s
planned. Take IBM. The company is pouring $1 billion into its Watson
computer system, the one that answered questions correctly on the game
show Jeopardy! IBM now imagines computers that can carry on
intelligent phone calls with customers, or provide expert
recommendations after digesting doctors’ notes. IBM wants to provide
“cognitive services”—computers that think, or seem to (see “Facing Doubters, IBM Expands Plans for Watson”).
Andrew Jennings, chief analytics officer for FICO, says automating
human decisions is only half the story.
Credit scores had another major
impact. They gave lenders a new way to measure the state of their
portfolios—and to adjust them by balancing riskier loan recipients with
safer ones. Now, as other industries get exposed to predictive data,
their approach to business strategy is changing, too. In this report, we
look at one technique that’s spreading on the Web, called A/B testing.
It’s a simple tactic—put up two versions of a Web page and see which one
performs better (see “Seeking Edge, Websites Turn to Experiments” and “Startups Embrace a Way to Fail Fast”).
Until recently, such optimization was practiced only by the largest
Internet companies. Now, nearly any website can do it. Jennings calls
this phenomenon “systematic experimentation” and says it will be a
feature of the smartest companies. They will have teams constantly
probing the world, trying to learn its shifting rules and deciding on
strategies to adapt. “Winners and losers in analytic battles will not be
determined simply by which organization has access to more data or
which organization has more money,” Jennings has said.
Of course, there’s danger in letting the data decide too much. In
this report, Duncan Watts, a Microsoft researcher specializing in social
networks, outlines an approach to decision making that avoids the
dangers of gut instinct as well as the pitfalls of slavishly obeying
data. In short, Watts argues, businesses need to adopt the scientific
method (see “Scientific Thinking in Business”).
To do that, they have been hiring a highly trained breed of business
skeptics called data scientists. These are the people who create the
databases, build the models, reveal the trends, and, increasingly,
author the products. And their influence is growing in business. This
could be why data science has been called “the sexiest job of the 21st
century.” It’s not because mathematics or spreadsheets are particularly
attractive. It’s because making decisions is powerful.
As reported by Wired: Thirteen suspects have been indicted in New York on a gas station skimming scheme that netted them more than $2 million, according to court documents.
The skimming devices, placed on card readers at gas station pumps throughout the southern U.S., recorded credit and debit card data, as well as PINs, which the thieves then used to withdraw more than $2 million from ATMs. They then tried to launder the money through at least 70 different bank accounts, according to the district attorney’s office in New York County.
Some of the skimming devices were placed on pumps at Raceway and Racetrac gas stations throughout Texas, Georgia, and South Carolina. The devices were Bluetooth enabled, so the thieves could simply download the stolen data from the skimming device without having to remove it.
Between March 2012 to March 2013, they used forged cards embossed with the stolen account data to withdraw cash at ATMs in Manhattan, then deposited the money into bank accounts in New York. Co-conspirators in California and Nevada then withdrew the money from ATMs in those states. During that year, the defendants allegedly laundered about $2.1 million.
Garegin Spartalyan, 40, Aram Martirosian, 34, Hayk Dzhandzhapanyan, 40, and Davit Kudugulyan, 42 are the lead defendants in the 426-count indictment charging them with, among other things, money laundering, possession of stolen property, and possession of a forgery device.
The other defendants are each charged with two counts of money laundering.
As reported by Live Mint: At the Consumer Electronics Show (CES) in Las Vegas
earlier this month, the roulette wheel of innovation landed on something
rather old-fashioned and unexpected: the automobile.
In recent decades,
cars have been undergoing a gradual transformation from the kinds of
mechanical systems Henry Ford
might have imagined into computers on wheels. And that transformation
is bringing with it a new wave of digital advances—above all, autonomous
driving.
The first autonomous (or self-driving) cars date back to the late
twentieth century. But recent increases in sophistication and reductions
in cost—reflected, for example, in cheap LIDAR systems, which can “see”
a street in 3D in a way similar to that of the human eye—are now
bringing driverless cars closer to the market.
As we saw last week, several manufacturers are working
toward integrating such systems into their fleets, and expect to start
selling premium cars with different degrees of autonomy as early as
2016. According to a just-released IHS report, “sometime after 2050”
virtually all vehicles on the road might be self-driving.
At the CES, journalists were busy snapping pictures of
driverless vehicles zooming through the streets of Vegas. But, had they
turned their cameras around, they might have captured something far more
interesting: the stage upon which the drama of self-driving will take
place—the street itself.
Self-driving vehicles promise to have a dramatic impact
on urban life, because they will blur the distinction between private
and public modes of transportation. “Your” car could give you a lift to
work in the morning and then, rather than sitting idle in a parking lot,
give a lift to someone else in your family – or, for that matter, to
anyone else in your neighbourhood, social-media community, or city.
A recent paper by the Massachusetts Institute of
Technology’s SMART Future Mobility team shows that the mobility demand
of a city like Singapore—potentially host to the world’s first
publicly-accessible feet of self-driving cars—could be met with 30% of
its existing vehicles. Furthermore, other researchers in the same group
suggest that this number could be cut by another 40% if passengers
travelling similar routes at the same time were willing to share a
vehicle—an estimate supported by an analysis of New York City Taxis
shareability networks. This implies a city in which everyone can travel
on demand with just one-fifth of the number of cars in use today.
Such reductions in car numbers would dramatically lower
the cost of our mobility infrastructure and the embodied energy
associated with building and maintaining it. Fewer cars may also mean
shorter travel times, less congestion, and a smaller environmental
impact.
The deployment of more intelligent transportation systems
promises to deliver similar benefits. Real-time data planning and smart
routing are already a reality. Tomorrow’s autonomous vehicles will
prompt another wave of innovation, from optimization of road capacity to
intersection management. Imagine a world without traffic lights, where
vehicular flows “magically” pass through one another and avoid
collision.
But, while the world’s mobility challenges will
increasingly be met with silicon rather than asphalt, encouraging
widespread adoption requires guaranteeing that our streets are as
safe—or safer—than they are today. That means that various redundancies
must be introduced to ensure that if one component fails, another
seamlessly takes over.
Traffic accidents, though rarer, would still be a
possibility; in fact, they might be one of the main impediments to
implementation of autonomous systems, demanding a restructuring of
insurance and liability that could sustain armies of lawyers for years
to come.
Finally, there is the fresh issue of digital security. We
are all familiar with viruses crashing our computers. But what if the
same virus crashes our cars?
All of these issues are urgent, but none of them is
insurmountable. They will be resolved in the coming years as autonomy
redefines mobility and sparks the next generation of innovations in the
field. At that point, the smart money might favor something even more
old-fashioned than cars: the city itself.
As reported by Computerworld: As the amount of information being fed into
in-car telematics systems grows through mobile connectivity, vehicles
will expand their ability to capture and share not only internal systems
status and location data, but also changes in surroundings in real
time.
Cars will be able to communicate with other vehicles, or even traffic
lights, and predict how conditions will affect a commute, adjusting
in-vehicle navigation or even taking over control from the driver, if so
desired.
"Cars will become the first robot most of us experience in our lifetime," said Gartner analyst Thilo Koslowski.
Koslowski, who was speaking at the Consumer Telematics Show in Las
Vegas today, said a major theme this year will be service providers,
such as ISPs and mobile carriers, expanding their ecosystems into the
auto telematics supply chain - providing the connectivity and apps
required for a full-mobile user experience.
Like OS and app upgrades on mobile devices today, software upgrades
to infotainment systems will happen automatically and wirelessly, he
said. Vehicles will be connected to the cloud, enabling users to upload
data from wearable devices as well as access personal data stored at
home or through cloud services.
Ultimately, your car will become just another part of your mobile data plan.
"AT&T has already said they will have that in GM vehicles going
forward," Koslowski said. "Cars will be the predominant platform for the
Internet of Things. It may even be mandated that your car have
connectivity, instead of it being a luxury."
There could even come a day when cars will be discounted -- or free
-- depending on how long consumers are willing to commit to a data plan,
Kowlowski said. "Maybe you'll get a car for free if you sign up for
lifetime data contract," he said. "If you change this to something a
little less dramatic, and talk about a discounted vehicle purchase with
an eight-year contract..., how many people would be interested in this?
"I was surprised to see quite a few [of those surveyed] were
interested in this - 38%," he continued.
"Obviously, you're not going to
get a Ferrari or Porsche or Audi heavily discounted because you sign up
for a data contract, but a smaller vehicle, absolutely."
Kevin Link, general manager of Verizon's Telematics division, said
telematics systems have developed from a first iteration of on-board help
services, such as GM's OnStar system, to vehicle diagnostics that
provide manufacturers with data about mechanical performance.
The next generation of connected cars, or "telematics 3.0," will
expand the value chain beyond the obvious, offering traffic condition
info to the car as well as emissions data to the driver.
Telematics 3.0 will also offer service providers a great deal of
information they can use for marketing purposes. For example, the
systems will be able to tell streaming media services what you're
listening to, and point of interest (POI) services in on-board GPS
systems will tell companies when a driver has searched for them, and
whether the driver stopped in.
A driver who visits a particular coffee shop or a golf course might
be targeted for marketing and advertising via mobile apps available
through the car's telematics system.
"Why is Google getting into the auto space? If you think about what
Google has and what they don't have, location is one of the missing
elements of the Google model," Link said. "They know everything else,
except where we transact."
Car manufacturers falling behind
In the meantime, vehicle manufacturers risk falling behind or even
being left out of the mobile telematics equation. "I'm a little worried
these big Internet companies may dominate this space and leave very
little for automotive companies," Koslowski added.
He pointed to Google's announcement Monday of an Open Automotive
Alliance, aimed at bringing Android OS to the telematics systems of
several vehicle manufacturers. Google announced plans to bring Android to cars by the end of this year.
Audi, General Motors (GM), Honda, Hyundai and chip maker Nvidia were all part of the launch of the Open Automotive Alliance.
"Having your own secure cloud of information connected to your
vehicle, that's what Google's...announcement was all about," Koslowski
said.
For example, the owner of a car would be able to connect his or her
Android smartphone and any cloud services enabled through that. At the
same time, if another family member wanted to borrow the car, they, too,
could use Android by simply connecting their smartphone to the car's
telematics system.
Tech companies such as Google are expected to have increasing
influence in the mobile options vehicle makers can offer - and consumers
want it that way.
According to a Gartner survey released today, 57% of vehicle owners
said they want technology vendors to influence decisions about their
car's mobile capabilities in the years ahead. Forty-three percent want
automakers to be the main influencer of mobile tech.
The survey also revealed that 47% of respondents want to use mobile
apps while driving. At the same time, 89% said they're concerned that
access to in-vehicle mobile apps will be a driving distraction.
Jaguar, Land Rover add mobile apps to telematics
Peter Vrik, head of connected technologies and apps for Jaguar, said
his company will now be offering iOS and Android mobile apps natively on
its infotainment systems through a partnership with Bosch SoftTec and
its mySPIN app integration software.
Jaguar's InControl Apps mobile application platform connects a car's
telematics and infotainment system to a mobile phone or tablet through
the use of a standard USB cord. Once connected, apps that have been
enabled through Bosh SoftTec's in-vehicle integration software
automatically show up for use on the infotainment system.
For example, iHeart Radio streaming music service, parking location
assist Parkopedia and real-time traffic navigation system INRIX will all
be available in upcoming vehicles, Vrik said. Vrik listed 11 apps that
are currently available, but said that list will continue to expand.
"By 2010, we target to have 20 million smartphones connected via
mySPIN," said Dietmar Meister, director smartphone and cloud solutions
at Bosch
"Customers want the latest apps and updates in their car. They want
to use the apps that are already there," Vrik said. "Users want to make
sure the app has the DNA of the original app. Don't try to make them
look different."
