LAS VEGAS – Most baseball fans won't forget the controversial call in Game 6 of the 2019 World Series between the Houston Astros and the Washington Nationals when runner Trea Turner was ruled out because of interference. Umpire accuracy is a frustration for fans and players in nearly every game. This season, MLB has launched so-called "robot umpires" in 11 Pacific Coast League Triple-A teams, putting it one step away from reaching the major leagues, to improve accuracy and reduce delays. The automated balls and strikes system (ABS) debuted in a Las Vegas Aviators' game earlier this month. As cool and bizarre as it would be to see "Jetsons"-style robots on the field, most fans won't notice the actual device -- eight surveillance-looking cameras at the top of the bleachers.

A multitude of factors can contribute to a flight being delayed, but Air France, who partnered with a handful of other companies, is testing the world's first self-driving luggage tug in hopes of streamlining airport operations and improving the speed of getting luggage to and from an aircraft. The vehicle, known as the AT135 baggage tractor, began official testing at France's Toulouse-Blagnac airport last month on November 15. To the untrained eye it looks like the myriad of vehicles you already see scurrying around the airport tarmac while waiting for a flight, including a cab with a seat, steering wheel, and all the controls needed for a human driver. But look closer and you'll be able to spot some of the telltale hardware upgrades of an autonomous vehicle, including laser scanning LIDAR sensors on the roof and bumper that complement less visible sensors like GPS and front and rear cameras providing a 360-degree view around the tug. Climb inside the tug and you'll also find a big switch allowing it to be switched between manual and autonomous modes, as well as an oversized touchscreen showing a map of the airport and all the gates the vehicle is designed to service.

British Airways (BA) has introduced artificial intelligence (AI) technology to parts of its "airside operation" at Heathrow Airport. In an announcement Monday, the airline said that AI would be used to tackle challenges faced when an aircraft is being prepared for departure after passengers from its previous flight have disembarked. It's during this time that staff on the ground undertake manual checks related to 18 different things, making records of what they are doing, British Airways said. These checks have to be done before the plane takes to the air again and are, among other things, related to refueling, the unloading and reloading of luggage, and cleaning of the aircraft's inside. BA said that if one of these tasks encounters an issue, it could potentially disrupt the whole process, resulting in a delayed departure.

New technology could curb delays. The world's second busiest airport by international travelers (and Europe's busiest), London's Heathrow airport handled a record 80.1 million passengers last year. The logistical scale of such an operation is orchestral, requiring meticulous air traffic control 24 hours a day, seven days a week. When that process is subject to even the smallest disruption, the effect can be collateral and events can quickly grind to a halt, leaving tens of thousands of passengers grounded. Owed to a combination of the dreary British climate and the height of its control tower which, at 87 meters high, is often consumed by low cloud, the weather is perhaps one of the most common causes of delays at Heathrow.

Researchers have created an artificial intelligence (AI) system they claim can spot abnormalities in chest X-rays and speed up the processing of screenings. The software uses computer vision to recognise radiological abnormalities in X-rays and then suggest how quickly these should be reported by a radiologist. The research from the University of Warwick claims the system could help cut the average delay in receiving an expert opinion from 11 days to less than three. The study, carried out by Warwick Manufacturing Group (WMG), an academic department of the university, also involved an algorithm that was capable of reading radiological reports, understand the findings and the priority level of the exam. The research, which was carried out through work with Guy's and St Thomas' NHS Foundation Trust in London, has been published in the journal Radiology.