AT&T and Intel Test drones’ Capabilities on LTE Beyond Line of Sight and at Higher Altitudes

As reported by Venture Beat: U.S. telecom giant AT&T is partnering with chip maker Intel to test and optimize how drones perform on LTE connections beyond line of sight, at higher altitudes, or when faced with external interference.

Intel is demoing an LTE-connected drone at Mobile World Congress (MWC) in Barcelona this week. The partnership is designed to show how a network that has primarily been designed to connect devices (such as smartphones) on the ground can be reappropriated for unmanned aerial vehicles (UAVs).

Above: Drone Controller

Many drones can be connected by smartphones, with onboard cameras giving the operator a real-time view of the UAV in flight. That, in conjunction with other sensors required to control the drone, means that a constant connection is required. And this is why Intel is teaming up with AT&T’s Internet of Things (IoT) team and its Foundry innovation center to see how drones can best work on an LTE network.

Drones have exploded in popularity in recent years, leading to increasing concerns over security and questions about how the vehicles could or should be regulated. And this is one of the areas the two companies are looking to address, including examining how signals between a smartphone and a drone may interfere with airplanes and other manned aircraft. They’ll also explore usability and functionality in “beyond line-of-sight” situations, a scenario the Federal Aviation Administration (FAA) is currently considering.

It’s worth noting here that the partnership is less about helping consumers navigate their toys around public thoroughfares than it is about exploring legitimate business scenarios. While the likes of Amazon are currently looking into “delivery by drone” initiatives, there are also many other use-cases across numerous industries that could see UAVs taken to the next level.

“AT&T and Intel will be testing how the network can enable the most exciting business use cases for drones,” said Chris Penrose, senior vice president of IoT Solutions at AT&T, in a press release. “Our LTE network is uniquely positioned to connect industries like delivery, agriculture, construction and insurance. We’re using the network to transfer important information, images and video quickly and efficiently — far beyond the boundaries of short-range connectivity.”

For AT&T, the move makes sense as the broader telecom industry increasingly embraces the so-called Internet of Things. As for Intel, it has been pushing heavily into the drone realm of late — recently acquiring Ascending Technologies, a drone maker that specializes in collision-avoidance technology.

“Intel believes UAVs have great potential, from inspections, precision agriculture to deliveries of consumer goods and providing emergency disaster relief,” added Anil Nanduri, vice president of the New Technology Group at Intel. “We want to grow this market through our collaborations and by integrating new technologies and compute to UAVs.”

Higher Accuracy GPS Could Boost Self-Driving Cars and Other Tech

As reported by Gizmag: Researchers have found a better way to crunch the data that GPS-enabled devices use to determine their location. The result could provide a level of accuracy down to the centimeter that's needed in things like autonomous vehicles and other precision tech.

We've seen other efforts to improve GPS location to centimeter-level accuracy using what's called "differential GPS," that makes use of ground-based reference points in addition to satellite GPS data. This latest effort from the University of California - Riverside (UCR) seems similar in that it's basically a software-based approach.

What's perhaps most revolutionary about the advance is not just the improved level of accuracy, but just how efficiently centimeter-accurate positioning is established.

"Achieving this level of accuracy with computational loads that are suitable for real-time applications on low-power processors will not only advance the capabilities of highly specialized navigation systems – like those used in driverless cars and precision agriculture – but it will also improve location services accessed through mobile phones and other personal devices, without increasing their cost," said UCR professor Jay Farrell, who led the research.

He claims that until now, achieving such accuracy has been computationally expensive, but the new approach returns a highly accurate position with several orders of magnitude fewer computations. That could make this level of GPS more practical in a number of emerging real world applications."To fulfill both the automation and safety needs of driverless cars, some applications need to know not only which lane a car is in, but also where it is in that lane – and need to know it continuously at high rates and high bandwidth for the duration of the trip," said Farrell.

Two members of the team that conducted the research have since moved on to work at Qualcomm and Google. The research was published recently in IEEE's Transactions on Control Systems Technology.

Is Tesla About To Unleash A Black Swan On The Energy Industry?

As reported by Forbes: Clients often ask me about what might be a “black swan” (an event that comes as a surprise to conventional wisdom, has a significant impact and is often rationalized after the fact) for the oil industry. Lately I’ve been thinking how a dramatic breakthrough in battery technology could be such an event. The implications for the petroleum industry might be broader than you think.

In a recent Forbes blog, tech contributor Mark Rogowsky reported some interesting details of the new Tesla Model 3 scheduled to make its debut on March 31. The Model 3 will be about the same size as a BMW 3 Series, with a price point of $35,000 and a range of 200 miles.

To be viable in the mass market for vehicles, an alternative vehicle needs to be competitive with the internal combustion engine (ICE) in three ways. It must have:

1. a price point of about $25,000
2. a record of reliability, and
3. a driving range of at least 300 miles, typical of mid-size sedans.

So the Model 3 is getting closer, but it’s not quite there. Yet.

A useful rule-of-thumb for automobile makers in model selection and pricing strategy is a price point that is 1.25x personal income. If we use GDP per capita as a proxy for income, then Tesla’s current mass market (at a price of $35,000) would be countries with income levels of about $28,000 per year (on a purchasing power parity basis). The chart below shows a market size of about 675 million (age 15 – 64) in 2015. This market grows to over 700 million by 2025. The market in advanced economies is fairly flat, but the emerging world nearly quadruples from 15 million to almost 60 million in the next ten years. If over the next 10 years Tesla can compress the price of its Model 3 (or equivalent) to $25,000, its market potential expands to almost 750 million drivers.

Today, there are over one billion ICE passenger vehicles on the roads compared to just over one million electric. Electric vehicles sales have increased almost 80% per annum since 2010 and were about 400,000 (equivalent to two weeks of VW’s current sales) of the 85 million vehicles sold globally in 2015.

Driving range is important to compete with an ICE vehicle, which are fueled through a fully depreciated distribution system. For the alternative to be successful, it needs to avoid (or minimize) investments in a network of refueling infrastructure (e.g., charge stalls in store parking lots) to keep down the effective cost of operating the vehicle. Avoiding this infrastructure investment is critical for electric vehicles to compete in advanced economies.

The initial version of the Tesla Model 3 looks to fall short of these mass market parameters. However, it does not take much of a stretch of the imagination for Tesla to close these competitive gaps as it builds actual road and manufacturing experience and production of the Model 3 ramps up.

How long might it take for these vehicles to significantly penetrate the global fleet? Once the technology breakthroughs are made, it will quickly disperse to other automobile manufacturers (similar to the spread of hydraulic fracturing in tight oil).

Technological innovation in automobiles tend to follow the rule of “7 in 10”, shorthand for a technology (e.g., air bags, anti-lock brakes, seatbelts) deployed in 70% of new car sales within 10 years. So if next generation electric vehicles can make the technology leap, then by 2025 they could account for about 70 million car sales annually. Over that pivotal decade, electric vehicles would grow to about 7% of the global car fleet. That might seem small, but without such a technology leap the share would be closer to 2%.

So what is the black swan event? It is not only that such a mass market electric vehicle could threaten oil demand growth, but that the underlying technological innovations necessary to be competitive with ICEs threaten the entire hydrocarbon industry – not just oil, but natural gas and coal as well. My hypothesis is that if a battery is capable of storing enough energy to move a $25,000 mid-size sedan 300 miles, then it would be cheap and small enough to mount another battery in the garage. If the garage battery is charged by roof-mounted solar and/or wind, it removes the need for incremental electricity generation from central power plants fired by natural gas or coal.

A more cost-effective battery (increasingly likely as electric vehicles penetrate deeper into the vehicle fleet) opens the possibility of even greater battery capacity and of households removing themselves from a central power grid. Not depending on a central power grid would be important to consumers in emerging economies who are looking for power reliability in addition to personal mobility.

Former Saudi Oil Minister Zaki Yamani is credited with the quip, “The Stone Age didn’t end because the world ran out of stones – and the same will be true with oil.” I usually conclude these black swan discussions with clients by saying that I won’t see the end of the oil industry, my kids won’t see the end, but my grandkids just might. If Tesla can meet its Model 3 aspirations in the next few years, my observation might be realized much earlier than I used to think. There’s a new Tesla dealership near my house; I think I’ll take a look.

Antonin Scalia, The 'Tiny Constable,' And Why Cops Need Warrants For GPS Car Trackers

As reported by Jalopnik: Is a GPS tracking device the same thing as a police officer who hides in your car? That’s how polarizing U.S. Supreme Court justice Antonin Scalia, who died at 79 last Saturday, approached the question of whether the Police need warrants to put GPS trackers on cars.

Depending on how you view things, Scalia was either a strict constructionist champion of individual rights, or a powerful opponent of progressive social change. But Scalia’s unique lens on the law led to an opinion that’s had a lasting effect on how law enforcement agencies can track vehicles in criminal investigations.

Thanks to the Supreme Court’s decision in the 2011-2012 case United States v. Jones, which came with a majority opinion written by Scalia, law enforcement agencies are now required to get search warrants before affixing a GPS tracking device to someone’s car.

The case went like this: in 2004, police in Washington D.C. and the FBI were investing nightclub owner Antoine Jones for drug trafficking. They secured a warrant to get a GPS tracking device to affix to Jones’ Jeep (a car actually registered to his wife), but that warrant ordered the device to be placed within 10 days and only in the District of Columbia.

After a month of tracking the car with the device from a stash house to various customers in the D.C. area, the feds were eventually able to indict Jones on a wide variety of narcotics conspiracy charges. Jones was called a “drug kingpin” and a raid on his stash house netted almost 100 kilos of cocaine and nearly $1 million in cash, the Washington Post reported in 2007. Jones—by no means anyone’s definition of an upstanding citizen—was sentenced to life in prison.

But according to the Cornell University Law School’s summary of the case, officers screwed up the placement of the GPS device. They put the device on the car 11 days later, and in Maryland, not D.C. The device was, essentially, outside the bounds of the warrant. That led the D.C. Court of Appeals to overturn Jones’ conviction in 2010.

A year after that, the Supreme Court heard the case. Lawyers for the government argued that Jones had no reasonable expectation of privacy out on public roads, and therefore affixing a GPS tracking device to someone’s car is not a “search” at all—a search would trigger protections under the Fourth Amendment. That part is the key to this case, and the Atlantic sums up how that argument went:

Chief Justice Roberts asked Deputy Solicitor General Michael Dreeben the question on all nine of their minds: “You think there would ... not be a search if you put a GPS device on all of our cars, monitored our movements for a month?”

“The Justices of this Court?” Dreeben asked cautiously.

“Yes,” Roberts said.

Dreeben said “the Justices of this Court when driving on public roadways” have no reasonable expectation of privacy.

“So,” Roberts said, “your answer is yes, you could tomorrow decide that you put a GPS device on every one of our cars, follow us for a month; no problem under the Constitution?”

Dreeben said yes.

All questions of whether a guy like Jones deserved to be in prison or not aside, the implications of such an argument are deeply chilling. And the court recognized this: they voted 9-0 to uphold the reversal of Jones’ conviction.According to this ruling, if law enforcement doesn’t get a warrant to track your car, the evidence gained from that would be inadmissible in court. (The court largely sidestepped the issue of whether Jones had a “reasonable expectation of privacy” or not, whether police can track a citizen on any level without a warrant.)

Though the justices were united in the decision, they did so for different reasons. Scalia, who authored the court’s majority opinion, acted in a way that reflected his own strict interpretation of the constitution: in seeking to preserve the Framers’ supposed intent of the Fourth Amendment when it was created, Scalia wondered if the 18th century colonial equivalent of this case would be a “constable” hiding in a suspect’s vehicle. From the opinion:

But it is almost impossible to think of late- 18th-century situations that are analogous to what took place in this case. (Is it possible to imagine a case in which a constable secreted himself somewhere in a coach and remained there for a period of time in order to monitor the movements of the coach’s owner?)

Justice Samuel Alito seemingly scoffed at looking at this through an 18th century lens in a footnote, writing, “The Court suggests that something like this might have occurred in 1791, but this would have required either a gigantic coach, a very tiny constable, or both—not to mention a constable with incredible fortitude and patience.”

See? The Supreme Court does have a sense of humor. Sort of.

As for Antoine Jones, while the Supreme Court upheld the reversal of his conviction, prosecutors pressed on with their drug case—this time without using the GPS evidence. They still had a ton of additional evidence about his massive drug trafficking ring. Another trial ended in a hung jury, but then Jones accepted a plea deal in May 2013 for 15 years in federal prison.

Still, his case will have a lasting effect on law enforcement practices. Whether GPS tracker is the same as a tiny, tiny police officer hiding in your car or not, he needs a warrant to be there.

Navy Tests First ‘Reversible’ Clean Energy Fuel Cell Storage System

As reported by ComputerWorld: Boeing has announced that, after 16 months of development, it has delivered a "reversible" fuel cell for the U.S. Navy that stores energy from renewable sources and generates zero-emissions electricity.

The Solid Oxide Fuel Cell (SOFC) system, which can generate 50 kilowatts (KW) of power, is the largest of its kind and can use electricity from wind or solar power to generate hydrogen gas, which it then compresses and stores.

When power is required, the system operates as a solid oxide fuel cell, consuming the stored hydrogen to produce electricity.

The SOFC system can scale to provide up to 400KW of power. It is being tested as part of a micro power grid at the Navy's Engineering and Expeditionary Warfare Center (EXWC) at Port Hueneme, Calif., .

"This fuel cell solution is an exciting new technology providing our customers with a flexible, affordable and environmentally progressive option for energy storage and power generation," Lance Towers, director of Boeing's Advanced Technology Programs, said in a statement.

A fuel cell is a device that uses stored chemical energy (in this case, hydrogen) and converts it into electricity. The SOFC device uses solar power to strip seawater of its hydrogen molecules through electrolysis. The hydrogen gas can then be stored and later used in the fuel cell stack where it electrochemically reacts with oxygen in ambient air to produce electric current, heat and water.

Omar Saadeh, a senior grid analyst at GTM Research, said the military is an enormous energy consumer with a high demand for reliability with regard to mission critical systems; so it only makes sense that they'd invest in a combination of on-site power generation and microgrid technologies.

"At forward operating bases, for example, deploying renewables not only enhances energy efficiency, but more importantly, also reduces the logistical risk in transporting fuel over distant and often hostile territory," Saadah said in an email reply to Computerworld.

Microgrids are small-scale power infrastructures that operate autonomous from the centralized grid run by utilities. According to a 2015 microgrid study by GTM Research, the military made up 35% of U.S. operational microgrid capacity.

While solar power is often promoted as the resource of the future, natural gas-fired generation accounts for 67% of the military’s domestic microgrid energy generation, Saadah said.

"This is due to its rapid dispatchability and reliability as a larger-scale power source," he said. "That being said, remote bases, which are smaller by nature, are deploying renewable and storage combinations as economically viable solutions that to meet today’s energy needs."

The SOFC manufacturers include Boeing in Huntington Beach, Calif. and Sunfire in Dresden, Germany.

The technology is unique in being able to both store energy and produce electricity in a single system, making the technology "reversible," Boeing said.

"The SOFC is a most promising technology for both remote islands and expeditionary applications," Michael Cruz, EXWC project manager, said in a published report. "Combined with a solar photovoltaic array, a SOFC system generates electricity, potable water, and heat with only two inputs, sunshine and seawater."

In Boost to Self-Driving Vehicles, U.S. Tells Google Computers Can Qualify as Drivers

As reported by Reuters: U.S. vehicle safety regulators have said the artificial intelligence system piloting a self-driving Google car could be considered the driver under federal law, a major step toward ultimately winning approval for autonomous vehicles on the roads.

The National Highway Traffic Safety Administration told Google, a unit of Alphabet Inc, of its decision in a previously unreported Feb. 4 letter to the company posted on the agency's website this week.

Google's self-driving car unit on Nov. 12 submitted a proposed design for a self-driving car that has "no need for a human driver," the letter to Google from National Highway Traffic Safety Administration Chief Counsel Paul Hemmersbaugh said.

"NHTSA will interpret 'driver' in the context of Google's described motor vehicle design as referring to the (self-driving system), and not to any of the vehicle occupants," NHTSA's letter said.

"We agree with Google its (self-driving car) will not have a 'driver' in the traditional sense that vehicles have had drivers during the last more than one hundred years."

Major automakers and technology companies such as Google are racing to develop and sell vehicles that can drive themselves at least part of the time.

All participants in the autonomous driving race complain that state and federal safety rules are impeding testing and eventual deployment of such vehicles. California has proposed draft rules requiring steering wheels and a licensed driver in all self-driving cars.

Karl Brauer, senior analyst for the Kelley Blue Book automotive research firm, said there were still significant legal questions surrounding autonomous vehicles.

But if "NHTSA is prepared to name artificial intelligence as a viable alternative to human-controlled vehicles, it could substantially streamline the process of putting autonomous vehicles on the road," he said.

If the car's computer is the driver for legal purposes, then it clears the way for Google or automakers to design vehicle systems that communicate directly with the vehicle's artificial pilot.

In its response to Google, the federal agency offered its most comprehensive map yet of the legal obstacles to putting fully autonomous vehicles on the road. It noted existing regulations requiring some auto safety equipment can not be waived immediately, including requirements for braking systems activated by foot control.

"The next question is whether and how Google could certify that the (self-driving system) meets a standard developed and designed to apply to a vehicle with a human driver," NHTSA said.

Google is "still evaluating" NHTSA's lengthy response, a company spokesperson said on Tuesday. Google executives have said they would likely partner with established automakers to build self-driving cars.

WORRIES ABOUT PEOPLE UNDERMINING SAFETY

Google told NHTSA that the real danger is having auto safety features that could tempt humans to try to take control.

Google "expresses concern that providing human occupants of the vehicle with mechanisms to control things like steering, acceleration, braking... could be detrimental to safety because the human occupants could attempt to override the (self-driving system's) decisions," the NHTSA letter stated.

NHTSA's Hemmersbaugh said federal regulations requiring equipment like steering wheels and brake pedals would have to be formally rewritten before Google could offer cars without those features.

For example, current federal rules require alerts on dashboards if tire pressure runs low. NHTSA said a test would need to be created that shows the vehicle computer is informed of the problem. NHTSA raised the question of whether humans in the vehicles should also be made aware.

In January, NHTSA said it may waive some vehicle safety rules to allow more driverless cars to operate on U.S. roads as part of a broader effort to speed up development of self-driving vehicles.

NHTSA said then it would write guidelines for self-driving cars within six months. Transportation Secretary Anthony Foxx said the administration may seek new legal authority to allow deployment of autonomous vehicles "in large numbers," when they are deemed safe, the department said.

The process of rewriting federal regulations governing the design, placement and operation of vehicle controls could take months or years. The NHTSA counsel said Google could consider applying for exemptions for certain regulations, providing NHTSA with supporting documents.

(Reporting by Paul Lienert in Detroit and David Shepardson in Washington; Editing byCynthia Osterman)

A Google self-driving car is seen inside a lobby at the Google headquarters in Mountain View, California November 13, 2015.

MIT Shows Off Power Efficient Chip Designed for Artificial Intelligence

A team of US researchers has built an energy-friendly chip that can perform powerful artificial intelligence (AI) tasks, enabling future mobile devices to implement “neural networks” modeled on the human brain.

As reported by Hindustan Times: The team from Massachusetts Institute of Technology (MIT) developed a new chip designed specifically to implement neural networks.

It is 10 times as efficient as a mobile GPU (Graphics Processing Unit) so it could enable mobile devices to run powerful AI algorithms locally rather than uploading data to the Internet for processing.

The GPU is a specialized circuit designed to accelerate the image output in a frame buffer intended for output to a display.

Modern smartphones are equipped with advanced embedded chip-sets that can do many different tasks depending on their programming.

GPUs are an essential part of those chip-sets and as mobile games are pushing the boundaries of their capabilities, the GPU performance is becoming increasingly important.

Neural nets were widely studied in the early days of artificial intelligence research, but by the 1970s, they had fallen out of favor. In the past decade, however, they have come back under the name “deep learning.”

“Deep learning is useful for many applications such as object recognition, speech and face detection,” said Vivienne Sze, assistant professor in MIT’s department of electrical engineering and computer science, in a MIT statement.

The new chip, which the researchers dubbed “Eyeriss,” can also help usher in the “Internet of things” – the idea that vehicles, appliances, civil-engineering structures, manufacturing equipment, and even livestock would have sensors that report information directly to networked servers, aiding with maintenance and task coordination.

With powerful AI algorithms on board, networked devices could make important decisions locally, entrusting only their conclusions, rather than raw personal data, to the Internet.

The team presented their findings at the “International Solid State Circuits Conference” in San Francisco recently.

At the conference, the MIT researchers used “Eyeriss” to implement a neural network that performs an image-recognition task. It was for the first time that a state-of-the-art neural network has been demonstrated on a custom chip.

“This work is very important, showing how embedded processors for deep learning can provide power and performance optimizations that will bring these complex computations from the cloud to mobile devices,” explained Mike Polley, senior vice president at Samsung’s mobile processor innovations lab.