Advanced Flight Technologies (Essay Sample)

Advanced Flight Technologies Author Institution Course Date Advanced Flight Technologies Artificial Intelligence (AI) and machine learning are one of the most recent advanced technologies that have diverse applications in aviation and many other industries. This technology has been established as one of the most effective techniques in helping to enhance jet fuel efficiency, reduce flight delays, and improve safety (Aeroclass.org., 2021). Leading airlines such as Airbus have adopted AI and machine learning applications to improve operational performance and customer satisfaction. This paper explores the impacts of AI and machine learning on current aviation technologies and safety methods at Airbus. Impacts of AI and machine learning on current aviation technologies at Airbus Artificial intelligence in aviation is per se, a multivariate topic since this technology does not only find its application in supporting air transport but also supports and enhances the efficiency of other aviation technologies to realize the best outcome. Until recently, Airbus was using air traffic control (ATC) and air traffic management (ATM) almost entirely based on human experience and work (Takialddin, 2020). This was because of the indispensable nature of human intervention in the ever-changing airlines to maintain varying traffic and weather conditions. However, Airbus and other aviation companies globally realized that the introduction of artificial intelligence in the industry brings significant impacts. Since the introduction of this technology, Airbus has witnessed substantial improvements in flow management, flight planning, and safety assessment (Aeroclass.org, 2021). This is due to the automation of different aviation technologies with the help of AI. AI has also facilitated the automatic prediction and handling of a vast majority of situations and scenarios in the sky using big data in the aviation industry. AI has enabled Airbus and other airlines such as Boeing to train their machine-learning algorithms to take various data sources and variables into account (Chen & Chang, 2021). This enables “intelligent” air traffic management applications to take air traffic and weather conditions into account before “making suitable” decisions using these vital data sources. Additionally, artificial intelligence has facilitated the automation of ATC and ATM, which has in return, improved their efficiency and predictability (Aeroclass.org, 2021). Consequently, Airbus uses the ATC and ATM applications to calculate and effectively predict the most ideal routes for their air transportation and airlines to ply to save fuel and time. Thirdly, AI significantly impacts the Internet of Things (IoT) in aviation for predictive maintenance. Predictive intelligence is one of the most fascinating feats that the AI industry has achieved in the aviation industry. Airbus is using these intelligent solutions to predict potential complications, flight delays, and in maintenance and repair procedures (Chen & Chang, 2021). Al enables the creation of an aircraft’s digital twin with the help of IoT. Digital twins enable engineers at Airbus to duplicate an exact physical state of hardware or object on their computers. This gives them the necessary insight into every plane and machine and establishes when targeted maintenance and repairs will be ideal depending on the condition the plane is in. the incorporation of AI and IoT generates an incredible way of saving money, optimizing work, and marinating an excellent state and shape of planes (Takialddin, 2020). Besides, AI enables IoT and predictive applications in Airbus and other companies that conduct repairs and manage planes to have requisite insights into each plane and machine by predicting potential glitches and failures with the highest degree of precision before they happen. This attribute impacts the airline company in question because it helps to save money and time. Artificial Intelligence has also found its application in aviation, especially in modern drones. Drones have increasingly become popular in recent years. Notably, drones are becoming even more intelligent and autonomous than they were first invented (Ganesh et al., 2018). However, the autonomy of these crewless vehicles is a function of AI which underwrites this ability in fully autonomous UAVs and drones. Some drones use the current technology, hence are usually controlled by pilots stationed within tens or hundreds kilometer radius. However, thanks to the positive impacts of artificial intelligence and machine learning, the aviation industry now has fully automated aircraft and drones operating on vast amounts of data and working without the need for any human intervention. Airbus uses AI to automate air travel. The company applies this technology to Wayfinder applications, disruptive cockpit (DISCO), and ATTOL technologies. Firstly, Wayfinder is an automated system that uses AI technology to power automatic aircraft applications (Njolomole & Kalimuthu, 2021). The technology helps to scale up small aircraft and aerial vehicles to commercial planes. On the other hand, disruptive cockpits are AI-enhanced cockpit programs built to facilitate the operations of single pilots in new aircraft. Lastly, Airbus applies The Autonomous Taxi, Take-off, and Landing (ATTOL) technology integrated with AI technology, through computer-aided visions to allow commercial planes to detect and navigate obstacles (Ganesh et al., 2018). This integration helps to reduce or minimize potential accidents or avoid impassible routes during tax take-offs, approaches, and landings. The impacts of AI and machine learning on safety methods at Airbus Artificial intelligence and machine learning play a pivotal role in ensuring that the enhanced avionics system (EASy) avionic suite safety method provides optimum safety to aircraft. Airbus’ planned adoption of the latest EASy avionics with integrated AI technologies will incorporate operator’s feedback, situational awareness, and efficiency would ultimately enhance safety (Waddell, 2021). The EASy precept is primarily designed and built through experience and military heritage to deliver a performance-enhancing and highly intuitive flight environment. This AI-enabled technology fosters safety by giving unprecedented usability for pilots in varying circumstances. Secondly, event detection applications were conventionally used to monitor and track tasks or processes to determine occurrences. Recently, people in the avia...