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What's the Deal With the Black Box?

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I have spent my life on Mars, in a cave, with my fingers in my ears. What, pray tell, is a flight recorder?

Flight recorders are devices used in aircraft to record—you guessed it—flight information, which then may be used to aid any investigations into aircraft accidents or incidents.

There are two common types of flight recorders: flight data recorders (FDR) and cockpit voice recorders (CVR). FDRs record various aircraft performance parameters and operating conditions, such as time, altitude, airspeed, heading, aircraft attitude, flap position, control-column position, fuel flow and even whether the smoke alarms in the lavatory went off. The Federal Aviation Administration (FAA) requires that older commercial aircraft record a minimum of 11 to 29 parameters, depending on the size of the craft. Newer aircraft (built after 8-19-02) are required to record at least 88 parameters.

CVRs record the audio environment in an aircraft's cockpit, including conversations, ambient sounds and radio communications between the cockpit crew and others.

The FAA requires that the recording duration is a minimum of thirty minutes, and most magnetic-tape CVRs employ a continuous loop of tape that cycles every 30 minutes, recording new material over the old. Sometimes, the two recorders are combined into a single FDR/CVR unit.

Some aircraft also employ a quick access recorder (QAR), which records data on a removable storage device and can be accessed with a more-or-less regular desktop computer (FDRs and CVRs require special equipment to read the recording). QARs are usually scanned during the flight for deviations from normal operations and/or parameters so that problems can be detected and fixed before an accident even occurs.

If they're used to investigate crashes, they must be pretty tough, right?

If I had to rate the toughness of a flight recorder, I'd put it right up there with Bruce Willis in Die Hard and Clint Eastwood in Dirty Harry. Flight recorders are carefully engineered and constructed to withstand some less than comfortable conditions and usually have an impact tolerance of 3,400 Gs (one G is the g-force acting on a stationary object resting on Earth's surface. It is the force of Earth's gravity and equal to however much that object weighs. In an 3,400-G impact, the flight recorder hits something at a force equal to 3,400 times its own weight). They also have a fire resistance of 2012° F/30 minutes. They can withstand water pressure when submerged up to 20,000 feet underwater and usually have an underwater locator beacon with a six-year shelf life and 30-day operation capability.

The information the recorder gathers is stored within the device on a crash-survivable memory unit protected by aluminum housing, one inch of dry-silica material high-temperature insulation and a ¼-inch thick stainless-steel or titanium cast shell.

For high visibility in wreckage, the outside of flight recorders are coated in heat-resistant, reflective red, yellow or orange paint.

So, if it's painted red, yellow or orange, why is it called the black box?

There are a few theories about that.

The first explanation goes that after an early flight recorder for commercial flights—the "Red Egg"—was unveiled, a journalist pronounced it to be a "wonderful black box."

Another explanation says that when new electronic instruments were being added to Royal Air Force planes during World War II, they were covered in hand-made metal boxes and then painted black to prevent reflection. These electronics came to be collectively known as "black boxes" and the term then made its way into civil aviation and general usage post-war.

Still another explanation has it that the name is simply borrowed. In science and engineering, a "black box" is a device, system or object that can viewed solely in terms of input, output and transfer characteristics without any knowledge of its internal workings.

How do you read a black box and what do you do with the info?

In the United States, after a black box is located, it's usually brought to the computer labs of the National Transportation Safety Board (NTSB). Transporting the boxes there is done with the utmost care so no further damage is done to the memory unit. If the plane crashed into a body of water, the black box is usually transported in a cooler of water until it can be handled and disassembled properly.

At the NTSB labs, the black box data is downloaded onto computers equipped with readout systems and analysis software supplied by the black box manufacturers. Extracting the data from a relatively undamaged recorder only takes a few minutes. In the case of a badly dented or burned recorder, the box has to be disassembled and the memory units removed, cleaned and connected to a working recorder.

The data on a CVR is reviewed and interpreted by a team of experts, usually including a representative from the airline involved in the accident, a representative from the airplane manufacturer, an NTSB transportation safety specialist and an NTSB air safety investigator. Meanwhile, the data on an FDR is used by NTSB investigators to reconstruct the events and conditions of the flight (FDRs are also used to analyze aircraft engine performance, the condition of aircraft parts and instruments and air safety issues). These processes can take weeks or even months, but, ideally, provide the investigators with some insight into the final moments of the flight and what caused the accident.

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Google's AI Can Make Its Own AI Now
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iStock

Artificial intelligence is advanced enough to do some pretty complicated things: read lips, mimic sounds, analyze photographs of food, and even design beer. Unfortunately, even people who have plenty of coding knowledge might not know how to create the kind of algorithm that can perform these tasks. Google wants to bring the ability to harness artificial intelligence to more people, though, and according to WIRED, it's doing that by teaching machine-learning software to make more machine-learning software.

The project is called AutoML, and it's designed to come up with better machine-learning software than humans can. As algorithms become more important in scientific research, healthcare, and other fields outside the direct scope of robotics and math, the number of people who could benefit from using AI has outstripped the number of people who actually know how to set up a useful machine-learning program. Though computers can do a lot, according to Google, human experts are still needed to do things like preprocess the data, set parameters, and analyze the results. These are tasks that even developers may not have experience in.

The idea behind AutoML is that people who aren't hyper-specialists in the machine-learning field will be able to use AutoML to create their own machine-learning algorithms, without having to do as much legwork. It can also limit the amount of menial labor developers have to do, since the software can do the work of training the resulting neural networks, which often involves a lot of trial and error, as WIRED writes.

Aside from giving robots the ability to turn around and make new robots—somewhere, a novelist is plotting out a dystopian sci-fi story around that idea—it could make machine learning more accessible for people who don't work at Google, too. Companies and academic researchers are already trying to deploy AI to calculate calories based on food photos, find the best way to teach kids, and identify health risks in medical patients. Making it easier to create sophisticated machine-learning programs could lead to even more uses.

[h/t WIRED]

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Courtesy Umbrellium
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These LED Crosswalks Adapt to Whoever Is Crossing
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Courtesy Umbrellium

Crosswalks are an often-neglected part of urban design; they’re usually just white stripes on dark asphalt. But recently, they’re getting more exciting—and safer—makeovers. In the Netherlands, there is a glow-in-the-dark crosswalk. In western India, there is a 3D crosswalk. And now, in London, there’s an interactive LED crosswalk that changes its configuration based on the situation, as Fast Company reports.

Created by the London-based design studio Umbrellium, the Starling Crossing (short for the much more tongue-twisting STigmergic Adaptive Responsive LearnING Crossing) changes its layout, size, configuration, and other design factors based on who’s waiting to cross and where they’re going.

“The Starling Crossing is a pedestrian crossing, built on today’s technology, that puts people first, enabling them to cross safely the way they want to cross, rather than one that tells them they can only cross in one place or a fixed way,” the company writes. That means that the system—which relies on cameras and artificial intelligence to monitor both pedestrian and vehicle traffic—adapts based on road conditions and where it thinks a pedestrian is going to go.

Starling Crossing - overview from Umbrellium on Vimeo.

If a bike is coming down the street, for example, it will project a place for the cyclist to wait for the light in the crosswalk. If the person is veering left like they’re going to cross diagonally, it will move the light-up crosswalk that way. During rush hour, when there are more pedestrians trying to get across the street, it will widen to accommodate them. It can also detect wet or dark conditions, making the crosswalk path wider to give pedestrians more of a buffer zone. Though the neural network can calculate people’s trajectories and velocity, it can also trigger a pattern of warning lights to alert people that they’re about to walk right into an oncoming bike or other unexpected hazard.

All this is to say that the system adapts to the reality of the road and traffic patterns, rather than forcing pedestrians to stay within the confines of a crosswalk system that was designed for car traffic.

The prototype is currently installed on a TV studio set in London, not a real road, and it still has plenty of safety testing to go through before it will appear on a road near you. But hopefully this is the kind of road infrastructure we’ll soon be able to see out in the real world.

[h/t Fast Company]

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