The Federal Aviation Administration is celebrating the success of initial trials of drone delivery programs, with tests including ice cream delivery and feral hog traps. The trials were part of the FAA’s UAS Integration Pilot Program and carried out this month by t10 companies selected to collaborate with the FAA and local governments to prove applications. Results will inform the development of new rules and standards for safe drone operations. Separate trials were conducted in North Carolina, Virginia, Kansas and Oklahoma. WakeMed Health and Hospitals successfully flew a Matternet drone in Raleigh, N.C. to demonstrate the viability of drones delivering medical supplies to rural areas. Matternet has already proven successful operations in Europe, supporting deliveries of medical supplies to remote locations in Switzerland and running drone operations to support Mercedes-Benz Vans delivery services. The company got the attention of Boeing Horizon X which contributed to $16 million in Series A funding for Matternet this June, along with Swiss Post, Sony Innovation Fund and Levitate Capital. Other tests went further afield. Virginia Tech Mid-Atlantic Aviation Partnership and the FAA successfully completed the country’s first and sweetest long-distance drone delivery test when an ice-cream cone was delivered to a child. The Kansas Department of Transportation and the FAA also tested drone flights beyond visual sight, which would help advance drone technology for precision agriculture and infrastructure inspections. And, in Oklahoma, the Choctaw Nation and the FAA used drones to bait feral hog traps. The FAA hopes the UAS Integration Pilot Program will help launch drone applications including commerce, aerial photography, emergency management and rescue operations, agricultural support and infrastructure inspections. “Our country is on the verge of the most significant new development in aviation since the beginning of the jet age—the emergence of unmanned aircraft systems, or drones. The rules and regulations governing our national airspace never anticipated drones. This technology is developing so rapidly, however, that our country has reached a tipping point,” U.S. Transportation Secretary Elaine L. Chao said when announcing the program selectees earlier this year. “As of May 4, 2018 there were 1.1 million registered drones in the U.S., and more than 90,000 registered drone operators. There must be a path forward for the safe integration of drones if our country is to remain a global aviation leader and reap the safety and economic benefits drones have to offer.” Some claim that the FAA is stifling innovation by establishing too many regulatory hurdles for the advancement of drone applications. Acting FAA Administrator Dan Elwell addressed such criticism in a speech at the International Aviation Club Luncheon this past May. “There’s a perception out there that government is where good ideas go to die. Too many bureaucrats. Nothing gets done. And that makes people not want to work with us. The pace of change is too fast. The scope of work is too big. The stakes are too high. We can’t afford to be alienating the pioneers… the trailblazers… the groundbreakers. They’re the foundation of our industry. And we need them at our table,” he said. “We’re building a bigger table – not just for traditional aviation stakeholders, but the newest Silicon Valley start-ups,” Elwell added. “We’re doing away with outdated processes that don’t work in today’s aviation system. And if people come into my office and say the reason we do something a certain way is because that’s the way it’s always been done? You better believe I’m sending them back to the drawing board. “At the very time when American innovators are leading the charge by doing things in a new way, government has to keep up. The FAA has to keep up. If there’s a way for us to improve a process, we’ve got to lead the way. That’s what makes us a world leader in aviation, in safety, in efficiency.” Powered by WPeMatico The post From Ice Cream To Wild Hogs: FAA Celebrates Successful Drone Trials appeared first on PCStoreNearMe. via Technology Latest News – PCStoreNearMe https://ift.tt/2MHcsWK
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By Samantha Masunaga / Los Angeles Times WASHINGTON — In a contest to build the first drone that will fly alongside Navy carrier fighters, the Boeing Co. has won a contract worth up to $805 million to build aerial refueling tankers, the Pentagon said Thursday. Most of the work on the tanker drones, known as the MQ-25A Stingray, will be done in St. Louis, though 1.5 percent will be completed in San Diego, according to the Defense Department’s contract listing. Boeing will receive $79 million of the total award amount to start. The MQ-25 will be launched via catapult from the decks of aircraft carriers. The initial contract is for four aircraft, but the Navy said it eventually plans to spend $9.5 billion to produce 72 tankers. The first four drones are set to become operational by 2024. Lockheed Martin Corp. and General Atomics were also competing for the contract. Both companies had been doing much work on their contending designs in Southern California, Lockheed Martin at its famed Skunk Works unit in Palmdale and General Atomics at its San Diego facilities. The aircraft that currently make up carrier air wings —the F/A-18 Super Hornet and F-35 Lightning II fighters —have relatively short ranges compared with the planes they replaced, making refueling a higher priority. Potential adversaries such as Russia and China have the ability to threaten carriers hundreds of miles out to sea. Concerns about wear and tear on Super Hornets and their crew —which currently handle refueling duties, along with fighter tasks —also prompted demand for unmanned replacements. Boeing’s MQ-25 drone will be powered by a Rolls-Royce engine, which is also used in the U.S. Air Force’s Global Hawk and and Navy’s Triton drones. Powered by WPeMatico The post Boeing wins contract to build 4 carrier-based drone tankers appeared first on PCStoreNearMe. via Technology Latest News – PCStoreNearMe https://ift.tt/2C1oNQu If you are fortunate enough to be bilingual, you’ll quickly understand the shortcomings of Android OS (others too) when it comes to speech. True, the options for most popular languages are there, however Android does very little to help to switch from one another like it does for the keyboard input. This is surprising considering the entire Google Translate API is available to us, mortals. I decided to take the advantage of that and improve one of my car profiles WhatsApp Voice Notifications. In that tutorial, I’d assign the spoken language to the contact name. Google’s text to speech system (TTS) would set the language based on the nationality of my contact. It worked well enough until some of my friends would send me lines in other than assigned, languages. Thanks to the Google Translate API I can not only change the language of the text-to-speak engine on the fly but also incorporate on-the-fly translations. The best thing about it is that the delay isn’t significant. The whole system works great and I can enjoy the spoken notifications in my car yet again. Google Translate API & WhatsApp Voice NotificationsTo determine the language and translate the text, you are going to need the API key for the Google Translate service. Log in to the Google Console, enable Google Translate API and generate an API key. You are going to need this to authenticate the HTTP calls. The basic use of Google Translate API is free, but do check the usage data, as excessive calls can lead to a bill issued to you by Google. WhatsApp Voice Notifications TypesI’m going to show you how to achieve this on WhatsApp, but the same can be applied to other messengers that store the text of the message in the Android notification. The Tasker profile will have 2 modes.
In the next write up, I will also show you, how to achieve this with Google Home. Querying language with TaskerTASKER TASK: WhatsApp Get Language A1: HTTP Post [ Server:Port:https://translation.googleapis.com/language/translate/v2/detect?key=%TranslateAPI Path: Data / File: q=%par1 Cookies: User Agent: Timeout:10 Content Type:application/x-www-form-urlencoded Output File:Download/lang.txt Trust Any Certificate:On ] A2: AutoTools Json Read [ Configuration:Input Format: Json Simple Mode: true Json: /storage/emulated/0/Download/lang.txt Fields: language Separator: , Timeout (Seconds):60 ] A3: Return [ Value:%language Stop:On ] To get the language info, we have to submit the test sample using Google Translate API and HTTP Post request. The URL has to be authorised with your API key, and contain the JSON object with the message sample. https://translation.googleapis.com/language/translate/v2/detect?key=YOUR_API The message sample is submitted under the “q” key and to do this in Tasker simply add: q=enter_text_to_sample in your data field. Once the request is submitted, you will receive a JSON (want to know more about JSON in Tasker – tutorial here)formatted object which looks like this:
{ "data": {"detections": [
[{ "confidence": 1,
"isReliable": false,
"language": "en"
}]
] }
}
Of course, we are interested in the language detection and the code that comes with it. You can look up all the ISO language codes here: ISO Language codes
To make our life complicated, the TTS engine codes for individual languages do not correspond with the ISO standard (why? dialects and localisations) so each TTS setting will have to come with defined IF condition. It’s ok, I’d rather do this that way as realistically speaking, you will only need 2-5 languages at best. If you want to create a full conversion table in Tasker, be my guest! TTS Language codes
Since response comes as a JSON, I’m going to use AutoTools JSON Read action to extract the value and identify the language. At this stage all I need is to set the variable %language, which will determine the TTS engine later on using IF statements. The correct Say Tasker action is selected, and the sample text is spoken with the properly picked TTS engine. Translating a message with TaskerTASKER TASK: WhatsApp Translate A1: HTTP Post [ Server:Port:https://translation.googleapis.com/language/translate/v2/?key=%TranslateAPI Path: Data / File: q=%par1 target=en Cookies: User Agent: Timeout:10 Content Type:application/x-www-form-urlencoded Output File:Download/translated.txt Trust Any Certificate:On ] A2: [X] HTTP Post [ Server:Port:https://translation.googleapis.com/language/translate/v2/?key=%TranslateAPI Path: Data / File: q=%par1 target=zh-CN Cookies: User Agent: Timeout:10 Content Type:application/x-www-form-urlencoded Output File:Download/translated.txt Trust Any Certificate:On ] A3: [X] HTTP Post [ Server:Port:https://translation.googleapis.com/language/translate/v2/?key=%TranslateAPI Path: Data / File: q=%par1 target=pl Cookies: User Agent: Timeout:10 Content Type:application/x-www-form-urlencoded Output File:Download/translated.txt Trust Any Certificate:On ] A4: AutoTools Json Read [ Configuration:Input Format: Json Simple Mode: true Json: /storage/emulated/0/Download/translated.txt Fields: translatedText Separator: , Timeout (Seconds):60 ] A5: Return [ Value:%translatedtext Stop:On ] The second option assumes that we are going to translate every message to a default language. For the sake of this tutorial I will use English, but feel free to pick your own native language instead. To submit the data to Google Translate API, once again, I’m going to send an HTTP Post to the authenticated URL: https://translation.googleapis.com/language/translate/v2?key=YOUR_API This time the data has to contain the sample text and the language we are going to translate the text to. q=your_sample_message target=language (ISO language code) The return message is a JSON response which looks like this:
{
"data":{
"translations":[
{
"translatedText":"This is just a test",
"detectedSourceLanguage":"pl"
}
]
}
}
In the same manner, AutoTools JON Read action will extract the value translatedtext and set it in %translatedtext for a later use. International WhatsApp Voice NotificationsTASKER PROFILE: WhatsApp Translations Profile: WhatsApp Translations Event: AutoNotification Intercept [ Configuration:Event Behaviour: true Notification Type: Only Created Notifications Has Reply Action: true Notification Apps: WhatsApp Notification App: WhatsApp Package Name: com.whatsapp ] Enter: WhatsApp Spoken International A1: If [ %WhatsAppMode eq 0 ] A2: Perform Task [ Name:WhatsApp Get Language Priority:%priority Parameter 1 (%par1):%antext Parameter 2 (%par2): Return Value Variable:%sayit Stop:Off ] A3: Say [ Text:%antext Engine:Voice:default:default Stream:3 Pitch:5 Speed:5 Respect Audio Focus:On Network:Off Continue Task Immediately:Off ] If [ %sayit ~ en ] A4: Say [ Text:%antext Engine:Voice:com.google.android.tts:pol-pol Stream:3 Pitch:5 Speed:5 Respect Audio Focus:On Network:Off Continue Task Immediately:Off ] If [ %sayit ~ pl ] A5: Say [ Text:%antext Engine:Voice:com.google.android.tts:zho-chn Stream:3 Pitch:5 Speed:5 Respect Audio Focus:On Network:Off Continue Task Immediately:Off ] If [ %sayit ~ zh-CN ] A6: End If A7: If [ %WhatsAppMode eq 1 ] A8: Perform Task [ Name:WhatsApp Translate Priority:%priority Parameter 1 (%par1):%antext Parameter 2 (%par2): Return Value Variable:%sayit Stop:Off ] A9: Say [ Text:%sayit Engine:Voice:com.google.android.tts:eng-gbr Stream:3 Pitch:5 Speed:5 Respect Audio Focus:On Network:Off Continue Task Immediately:Off ] A10: [X] Say [ Text:%sayit Engine:Voice:com.google.android.tts:pol-pol Stream:3 Pitch:5 Speed:5 Respect Audio Focus:On Network:Off Continue Task Immediately:Off ] A11: [X] Say [ Text:%sayit Engine:Voice:com.google.android.tts:zho-chn Stream:3 Pitch:5 Speed:5 Respect Audio Focus:On Network:Off Continue Task Immediately:Off ] A12: End If We have the full know-how to create the on-the-fly adjustments. The profile is very simple actually. I’m going to capture WhatsApp notifications using AutoNotification (intercept Whatsapp notifications with a “reply”), and then use Say action after the language or translation has been determined. To get the language or translation, I will use the Perform Task action and send the %antext as %par1. The language detection task will return the %language code and the translate task will return the %translatedtext to the main task. [appbox googleplay com.joaomgcd.autonotification] The returned value will be passed over to the Say action with a specified TTS either by the IF condition (%sayit) or predefined language setting for your translations. TASKER TASK: WhatsApp Mode A1: Profile Status [ Name:WhatsApp Translations Set:On ] A2: Variable Add [ Name:%WhatsAppMode Value:1 Wrap Around:2 ] A3: Flash [ Text:Native language mode enabled Long:On ] If [ %WhatsAppMode eq 0 ] A4: Flash [ Text:Translating to another language Long:On ] If [ %WhatsAppMode eq 1 ] If you want to hardcode your option into the task (and you don’t need another one) – feel free to do so. I’m going to wrap both actions in an additional IF condition which will determine what behaviour I want from my profile. A variable %WhatsAppMode becomes 1 or 0 thanks to the Variable Add action with a wrap around 2. A toggle will set a global variable and flash the confirmation of the selected behaviour. And with that done, you can decide for yourself how you want to enable it. You can trigger the profile from a home shortcut, voice command or the notification bar tiles. ConclusionThis is a much-improved version of my previous voice notification profile. WhatsApp Voice Notifications are not perfect, as foreign words in a single message won’t get the same treatment, but as long as your contact sticks to a single language per sentence – everything should be fine. The translated data can be also used in custom notifications which would have the translated messages. This is something I’m not going to cover in this tutorial. Be aware I have not included any exceptions for URL handling. If your friend sends you a link, this profile will read it out! Lastly, I will be looking into adding this to my Google Home Notifications too. This way messages received to your phone can be passed over, translated and spoken by the smart speaker. You can download the ready file here and if you wish you can buy me a coffee or support me via Patreon. Share this:Powered by WPeMatico The post Get WhatsApp voice notifications & translations in native languages with Tasker appeared first on PCStoreNearMe. via Technology Latest News – PCStoreNearMe https://ift.tt/2ooZrCu
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It’s a brilliant idea. Put solar panels on a drone and it doesn’t even need a battery. That’s exactly what students made at the National University of Singapore. Without a battery, you could fly a drone like this as long as the sun keeps shining. It’s awesome (assuming your motives are pure). But if you watch the video, you’ll notice immediately that the drone is as thin as a sheet. The real question, then, is what size and mass could this drone be and still run completely on solar power? I’m going to answer this and give you a solar-powered quadcopter calculator. But first, let’s look at the important physics ideas that go into this calculation. Solar PowerPower is defined as the time rate of energy usage (change in energy divided by change in time) and is measured in units of Watts. Ideally, you want all the power from the solar panels to go into the power required to fly. This means there is no need for a battery to temporarily store energy—which is fine, since that would add mass to the vehicle. But how much power can you get from a solar panel? That is the real question. The power output from a solar panel depends on the following values (with some initial estimates from me):
With that, I get the power output as the following equation. That’s it for the solar power. Hovering PowerThe power needed for a hovering quadcopter is a little bit more complicated. Let me give you the short version. Really, this works for any flying vehicle that hovers by pushing air down. Let’s start with the nature of forces and motion. If you take an object that is at rest and increase its speed, this requires a force. The magnitude of this pushing force depends on the mass of the object, the change in speed and the time over which the speed changes. Now replace this object with air—because that’s what these flying vehicles use to fly. You can get a greater thrust force by using more mass of air using a larger rotor area. You can also get more thrust by increasing the speed of the air. There is some more math involved here, but I am going to skip it (but you could indeed look over this if you want). But wait! We don’t care about the thrust force, we want the power. If you increase the speed of air (with mass), this increases its kinetic energy. The faster you increase the kinetic energy, the more power it takes. This means that you could have a hovering craft with small rotors that pushes the air down really fast OR a large rotor that pushes the air down at a slower speed. But the power isn’t the same for these two options. Since the kinetic energy is proportional to the square of the velocity, the smaller rotor with faster air requires MUCH more power to hover. Incidentally, this is why a human-powered helicopter (a real thing) has to be so large to get the power down to human levels. Calculating Hovering PowerNow for all the details. How big is this quadcopter? How large are the rotors? What about the size of the solar panels? What if someone invents a more efficient solar panel? Instead of calculating all possible variations, I am just going to make a calculator of a sort. Really, this is just a python program that calculates the the rotor size needed to hover for a given set of parameters. Also note that this is just one more reason that python is a better calculator than your standard scientific calculator (plus python is free). Here is the code—right here in this page. Feel free to edit the values and rerun the calculation. Don’t worry, you can’t break anything. It’s unbreakable code. Just click the “play” to run and the “pencil” to edit.
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With my default estimations, I get a rotor diameter of almost 5.9 centimeters. That seems fairly reasonable? But what if you increase the mass? What about the size of the solar panels? Yes, now you can change these things with just a few edits of the code. You are all set to make your own solar-powered drone. More Great WIRED Stories
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