Drone Company Allegedly Brings Bomb on Plane, Fires Whistleblower Employee

A legal complaint from a former security officer says the company brought an explosive-laden drone on a flight with 230 other passenger and fired him for reporting it.
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By Avery Thompson    
May 18, 2018
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Getty Imagesfhm    

It is very bad for there to ever be a bomb on an airliner. There are actually several people at any given airport whose entire job is to prevent you from bringing a bomb (and plenty of things that are not bombs) onto an airplane! Despite this, one employee of a drone company allegedly brought a bomb onto a plane anyway somehow, according to Bloomberg, and a coworker who reported it to the DoD was then fired.

Drone manufacturer AeroVironment mostly builds UAVs and is a supplier of small drones to the U.S. military. An open question, however, is what they were doing with an explosive-strapped drone on a commercial flight that also housed over 200 other.

Security officer Mark Anderson became aware of the event about a month later, and alerted the DoD and higher-ups at the company to the situation. In retaliation, Anderson says AeroVironment limited his duties and eventually fired him. In response, Anderson filed a wrongful termination lawsuit.

AeroVironment released this statement on the lawsuit:

    AeroVironment believes the complaint contains baseless legal claims that are without merit. The Company will defend itself vigorously once it is served with the complaint, consistent with its ongoing commitment to conducting its business with the highest standards of ethics, safety and integrity.

There are still plenty of details we'd need to understand the full scope of this story, and they may come out in the future. In the meantime, well, hopefully none of this is a lesson you need to learn.

First Steps Toward Drone Traffic Management

NASA recently successfully demonstrated rural operations of its unmanned aircraft systems (UAS) traffic management (UTM) concept, integrating operator platforms, vehicle performance and ground infrastructure. The next steps involve further validation through Federal Aviation Administration (FAA) test sites.

“UTM is designed to enable safe low-altitude civilian UAS operations by providing pilots information needed to maintain separation from other aircraft by reserving areas for specific routes, with consideration of restricted airspace and adverse weather conditions,” said Parimal Kopardekar, manager of NASA’s Safe Autonomous Systems Operations project and lead of NASA’s UTM efforts.

Engineers at NASA’s Ames Research Center in Moffett Field, California, are developing UTM cloud-based software tools in four segments of progressively more capable levels. They design each “technical capability level” for a different operational environment that requires development of proposed uses, software, procedures and policies to enable safe operation, with Technical Capability Level One focusing on a rural environment. With continued development, the Technical Capability Level One system would enable UAS operators to file flight plans reserving airspace for their operations and provide situational awareness about other operations planned in the area.

The majority of flight testing occurred at Crows Landing, a remote, closed, private-use airfield, 18 miles southwest of Modesto, California. Prior to flight test, the team deployed a 100-foot weather tower, small weather stations, microphone, Automatic Dependent Surveillance-Broadcast (ADS-B) in a ground relay station for air traffic feeds, and a radar station for flight test monitoring and data collection.

The day of the test the team arrived at dawn for preflight vehicle checks, and to test communication, radio, weather and other equipment prior to the preflight briefing, which covered test objectives, abort procedures, and geofence and autopilot boundaries. “Geofencing” is when the global positioning system or a radio frequency is used to define a geographical boundary -- a virtual barrier. Marcus Johnson, UTM flight test director, initiated the first test at 8:30 a.m. local time. Pilots then submitted operation plans and their positions into the UTM system, which checked airspace for conflicts, approved or disapproved flight plans and started tracking the drones through the UTM system’s ground control station.

UTM system scheduling and tracking onscreen displays
UTM system scheduling and tracking displays On the left is an aerial view of the operational area. The pink solid line indicates the flight plan that was requested from the UAS operator. The dotted line outlines the area where the drone is allowed to fly. This area is always larger than the requested flight plan to account for drone deviation due to wind or navigation uncertainty. On the right is a schedule view of the approved flight plan and upcoming operations in the UTM system. This view shows a single operation, but the system is capable of showing multiple simultaneous operations, each with their own start and end time, and general information about the flight, such as who is flying, altitude and air speed. It also has an area where the UTM manager can message a UAS operator.
Credits: NASA Ames

As the pilots flew their drones within the approved geofence, the team monitored each drone’s ability to maintain flight plans in windy conditions with radar, cellular signals, ADS-B and GPS provided by the UAS ground control station to the UTM system. This data provides insight into the reliability, accuracy and delay associated with UAS position reports, and helps researchers further develop the UTM system’s navigational performance. In addition to collecting data about air traffic for UTM development, collaborator Gryphon Sensors made traffic calls to alert the drone operators of non-transponding aircraft approaching the test range.

The team monitored temperature, wind and weather conditions with weather balloons, and a radio frequency band for safety purposes. The team collected the meteorological data to validate low-altitude weather forecasting models developed in partnership with the National Oceanic and Atmospheric Administration and Massachusetts Institute of Technology Lincoln Labs. Researchers took measurements from each aircraft to evaluate potential noise impact to people and wildlife.

Over eight days the UTM team flew 108 flights with 10 different aircraft. Flights averaged 11 minutes, but some flew as long as 38 minutes.

Eleven collaborators participated in the initial testing that focused on vehicle trajectory, the virtual constraints known as geofencing and tracking aspects, including:

  • UAS multi-rotor and fixed wing vehicles;
  • ADS-B transponders providing GPS altitude, airspeed and location information;
  • ADS-B ground stations and air traffic surveillance displays;
  • vehicle tracking over the cellular network; 
  • vehicle tracking using low-altitude radar system; and
  • weather measurement equipment.

NASA collaborators for Technical Capability Level One flight tests included Precision Hawk, Raleigh, North Carolina; Verizon, Bedminster, New Jersey; Gryphon Sensors, Syracuse, New York; Airware, San Francisco; University of Nevada-Reno/Flirty, Reno, Nevada; SkySpecs, Ann Arbor, Michigan; ne3rd, Navarre, Florida; Harris/Exelis, San Francisco; Unmanned Experts, Denver; San Jose State University; and Lone Star UAS Center, Corpus Christi, Texas.

The cloud-based system of UTM is described in four technical capability levels.

  • Technical Capability Level One involves field-testing of rural UAS operations for agriculture, firefighting and infrastructure monitoring.
  • Technical Capability Level Two will be demonstrated in October 2016 for applications that operate beyond visual line of sight of the operator in sparsely populated areas. The system will provide flight procedures and traffic rules for longer-range applications.
  • Technical Capability Level Three will include cooperative and uncooperative UAS tracking capabilities to ensure collective safety of manned and unmanned operations over moderately populated areas and is planned for January 2018.
  • Technical Capability Level Four will involve higher-density urban areas for autonomous vehicles used for newsgathering and package delivery, and will offer large-scale contingency mitigation. Build Four will be demonstrated in 2019.

As a result of the Level One field test, NASA created implementation and integration guidelines and lessons learned for the UTM system in a rural, remote or over-water environments.

“UTM Level One tests demonstrated awareness of all airspace constraints, and shows promise for vehicle tracking to support initial low-density operations,” said Kopardekar. 

The final test of Level One concluded on November 18 with a test at Moffett Field. During this test the team flew a live drone on the runway while a nearby lab simulated virtual drones with simulated trajectory conflicts.  The UTM system recognized the live and virtual drones and responded by sending messages and alerts to all vehicles. Further tests with additional vehicles, trajectory configurations and multiple users will be conducted at FAA designated test sites in an initial safe UAS integration campaign in spring 2016.

To learn more about NASA aeronautics, visit:

http://www.nasa.gov/aero

In recent years there have been plenty of headlines highlighting the use of drones to smuggle drugs and other contraband into prisons.

And that’s fair enough. It’s a new, interesting challenge for authorities to deal with. And fear gets clicks.

Last year in the UK, for example, police monitored and apprehended an organized crime gang responsible for using drones to smuggle £1.2m worth of drugs, weapons and mobile phones into prisons across the country.

As of December 2017, 17 people had been found guilty of using drones to get contraband into prisons in the UK. Last week, 5 more were convicted.

And many such cases have been reported in the US, Canada, and Australia – to name a few.

So yes, the problem is a real one. It’s also one that is difficult to stop without having expensive, sophisticated systems in place. Not to mention the staff capable of using them.

We’ve seen plenty of exciting applications of drone technology in Africa. Unsurprisingly, most of them are driven by necessity, far removed from the relatively frivolous notion of an Amazon prime delivery service or some kind of milkshake on-demand courier.

US startup Zipline has long been established on the continent, providing vital infrastructure for medical deliveries in Rwanda and, more recently, Tanzania. Drones have also been deployed in the fight against Malaria in Malawi and used to combat illegal poaching across the continent.
Drones prevent illegal fishing in Seychelles

Previously the use of drones to prevent poaching has occurred on land. But one north-African startup is taking the technology to the ocean: ATLAN Space.

The company’s FishGuard program was recently awarded $150,000 by the National Geographic Society in its Competition to Combat Illegal Fishing, a search for innovative solutions and technologies that protect and sustain fisheries in coastal communities.
FishGuard is a partnership between ATLAN Space, Grid-Arendal and Trygg Mat Tracking. The aim is to use drones to identify and reduce illegal fishing in the Republic of Seychelles.
Together they are monitoring huge swathes of the ocean with fully autonomous drones guided by computer vision and AI.

    To fight IUU ((illegal, unreported, unregulated) fishing and protect the sustainability of our oceans, we have created FishGuard, a fully scalable and adaptable solution that allows institutions to monitor millions of km2 while hugely decreasing the patrolling costs and greatly increasing the efficiency. FishGuard is a unique combination of autonomous drones guided by Artificial Intelligence, with field experience and capacity building.” – Badr Idrissi, ATLAN Space

Investigating threats from above

Currently, authorities have to use light aircraft or coast guard vessels to keep tabs on boats’ activities.
So how will FishGuard work? Starting in October, the pilot program will use drones that have been pre-programmed with GPS data outlining hotspots for illegal fishing activities.
Once above the location, the drone’s AI will register the type of ships that are present on the water, from cruising boats, to tankers to fishing vessels. The drone will then establish whether the boat is an authorized fishing vessel.
If the system comes back negative, the drone will register the boat’s location, identification number and relay the data back to the authorities via satellite.
“With artificial intelligence, we are able to replace the pilot, the data analyst, transmission equipment, and with that we can reduce the cost,” says Idrissi.
Atlan Space has confirmed that their technology could be integrated with any type of drone. Presumably, fixed-wing models will offer longer flight times and be able to cover more distance. A small drone with a combustion engine could offer an operational range of up to 800 kilometers, suggested Idrissi.