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Avius Launches Gestures – Touchless Customer Feedback Technology

#artificialintelligence

Customers who wish to provide feedback at business no longer need to physically touch a survey screen. Avius, a leading tech company that provides real-time customer feedback solutions, launched Gestures, a touchless AI-powered thumbs up/thumbs down survey experience. The innovative technology has launched at Hartsfield-Jackson Atlanta International Airport (ATL), the busiest airport in the world, and at LEGOLAND Florida. The pandemic has quickly created a new operating environment for businesses who are now more than ever embracing touchless technology. Avius predicted early on during the pandemic that touchless would play an important role in society moving forward.


Facial recognition tech spreads to car rentals

Mashable

Why take out your wallet and photo ID if a camera and software program can scan your face, verify your identity, and send you on your way in 30 seconds? That's what Hertz rental cars is asking with its new partnership with Clear, the biometric face and fingerprint scanning company you've seen at airport security checkpoints. SEE ALSO: Microsoft wants regulation to keep the'facial recognition genie' in the bottle At the Hartsfield–Jackson Atlanta International Airport this month, you can check out and drive off in your rental car with just a scan of your face (or a fingerprint reading). The offer only applies, however, if you're a Gold Plus Rewards program member who's signed up for Clear. Instead of showing an ID, you just look up at the camera from the car window and after scanning your face it matches the images against the database where your info is already logged.


Teenager accidentally kills himself as friends watch on Instagram Live

The Independent - Tech

A 13-year-old boy has accidentally killed himself while live-streaming a video on Instagram. Malachi Hemphill had been posing with a gun on Instagram Live when he mistakenly pulled the trigger at his home in Forest Park, Georgia, in the US. His body was found by family members, who broke down his bedroom door after hearing a loud bang. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.


Propagation of Delays in the National Airspace System

arXiv.org Artificial Intelligence

The National Airspace System (NAS) is a large and complex system with thousands of interrelated components: administration, control centers, airports, airlines, aircraft, passengers, etc. The complexity of the NAS creates many difficulties in management and control. One of the most pressing problems is flight delay. Delay creates high cost to airlines, complaints from passengers, and difficulties for airport operations. As demand on the system increases, the delay problem becomes more and more prominent. For this reason, it is essential for the Federal Aviation Administration to understand the causes of delay and to find ways to reduce delay. Major contributing factors to delay are congestion at the origin airport, weather, increasing demand, and air traffic management (ATM) decisions such as the Ground Delay Programs (GDP). Delay is an inherently stochastic phenomenon. Even if all known causal factors could be accounted for, macro-level national airspace system (NAS) delays could not be predicted with certainty from micro-level aircraft information. This paper presents a stochastic model that uses Bayesian Networks (BNs) to model the relationships among different components of aircraft delay and the causal factors that affect delays. A case study on delays of departure flights from Chicago O'Hare international airport (ORD) to Hartsfield-Jackson Atlanta International Airport (ATL) reveals how local and system level environmental and human-caused factors combine to affect components of delay, and how these components contribute to the final arrival delay at the destination airport.