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An Air Traffic Controller(ATC) is a person responsible for the proper Take-Off and Landing of an Aircraft from the runway, and for relaying continuous vital information back and forth from Pilots. The proposed ATC will automate this entire process to reduce human-generated errors and save costs. The entire system will be made using Artificial Intelligence and will use Natural Language Processing and Artificial Neural Networks to create a human-like, but a better-prepared system. The model needed to create the ATC, can be trained on already available crucial flight data. The data must include flight take-off and landing time, along with altered time based on weather, climate and other physical factors. The back-end system of the ATC, can be then made to work on this trained model, and produce correct and calculated flight path and timings for the take-off and Landing.

Since 1986, the U.S. Army has been evaluating a digital data recording system known as a Portable Engine Analyzer Test Set (PEATS) for the detection, diagnosis and prognosis of faults on turbine engines installed in helicopters. On-board use of digital data systems makes test cell quality instrumentation available for testing installed engines. Electronic data recording and transfer of accurate performance information into a personal computer allows the use of Artificial Intelligence methods to form and interpret the significance of the data. The resulting information is being successfully used to provide previously unobtainable diagnostic capabilities for maintenance decisions. Standardized engine testing and formatting of data helps low experience technicians see the relative internal condition of a gas turbine engine at a glance.

In large scale industries attempts are continuously being made to automate assembly processes to not only increase productivity but also alleviate non-ergonomic tasks. However this is not always technologically possible due to specific joining challenges and the high number of special-purpose parts. For the riveting process, for example, semi-automated approaches represent an alternative to optimizing aircraft assembly and to reduce the exposure of workers to non-ergonomic conditions entailed by performing repetitive tasks. In [1], a semi-automated solution is proposed for the riveting process of assembling the section barrel of the aft section to its pressure bulkhead. The method introduced a dynamic task sharing strategy between human and robot that implements interaction possibilities to establish a communication between a human and a robot in Human-Robot-collaboration fashion.

DARPA will invest more than $2 billion in over 20 new and existing programs collectively called the “AI Next” campaign. Through AI Next, DARPA is exploring ways to advance the state-of-the-art in AI, pushing beyond second-wave machine learning techniques and toward “contextual reasoning and adaptation” capabilities. ...Through AI Next, DARPA is exploring ways to advance the state-of-the-art in AI, pushing beyond second-wave machine learning techniques and toward “contextual reasoning and adaptation” capabilities.

In a collaborative project between the CFMS and the NCC, both in Bristol, England, a closed loop manufacturing process has been demonstrated for the resin transfer molding (RTM) of high-quality composite components.

A new “AI Innovation Challenge” tasks United Kingdom and Canadian startups and researchers to pitch ideas for how AI could improve aircraft efficiency in extreme weather. ...A new “AI Innovation Challenge” tasks United Kingdom and Canadian startups and researchers to pitch ideas for how AI could improve aircraft efficiency in extreme weather.

With an initial focus on critical fight management systems, the committee will evaluate applications for AI usage in aviation and aerospace and will propose standards to support implementation and certification

The new Advanced Technology and Training Center (ATTC), which opened yesterday after a ribbon-cutting ceremony, will focus on breakthroughs in condition-based maintenance and the intersection of artificial intelligence (AI), robotics, and automation within that domain.

Software has transformed every operational asset of everything in life; artificial intelligence (AI) will have as big an impact on life, predicts Mark Roboff, vice president, aerospace and automotive at SparkCognition during the 2018 SAE Aerospace Standards Summit at LMI in McLean, Va.

By processing ultra-high-definition (UHD), 4K resolution camera images with state-of-the-art AI and machine learning systems at a new £2.5 million ($3.3 million) “digital tower laboratory,” NATS is investigating whether these technologies can improve Heathrow’s landing capacity during low-visibility periods and reduce flight delays.

The Swarm and Search AI Challenge: 2019 Fire Hack challenge will culminate in a March 2019 showdown and explore methods for planning complex UAS or “drone” swarm operations.

Airbus Aerial uses a unique combination of satellites, manned aircraft and rotorcraft, and unmanned aircraft systems (UAS) together with data analytics technology and an artificial intelligence (AI), or machine learning, platform to help organizations supporting recovery efforts better understand and react to the storm as it rolled across the southeastern U.S. into the Gulf of Mexico.

This document discusses guidelines for the development of Aircraft Systems leveraging AI capabilities, taking into account the overall aircraft operating environment and functions. This includes validation of requirements and verification of the design implementation for certification and product assurance and guidelines with the assessment of safety.

This document reviews current aerospace software, hardware, and system development standards used in the certification/approval process of safety-critical airborne and ground-based systems, and assesses whether these standards are compatible with a typical Artificial Intelligence (AI) and Machine Learning (ML) development approach. The document then outlines what is required to produce a standard that provides the necessary accommodation to support integration of ML-enabled sub-systems into safety-critical airborne and ground-based systems, and details next steps in the production of such a standard.

Almost exactly seven months after Unites Technologies Corporation (UTC) completed its acquisition of Rockwell Collins (now Collins Aerospace), the aerospace conglomerate announced its merger with the Raytheon Company.

Unfortunately, the same is not true for simulations used to train and test artificial intelligence (AI) that enables autonomous vehicles to fly and drive without humans. Research has shown that simulation “fidelity” is the most influential factor affecting training yield, but psychological fidelity is a widely accepted definition that does not apply to AI because it describes how well simulations engage various cognitive functions of human operators. ...Research has shown that simulation “fidelity” is the most influential factor affecting training yield, but psychological fidelity is a widely accepted definition that does not apply to AI because it describes how well simulations engage various cognitive functions of human operators. ...Therefore, this investigation reviewed the literature that was published between January 2010 and May 2022 on the topic of simulation fidelity to understand how researchers are defining and measuring simulation fidelity as applied to training AI. The results reported herein illustrate that researchers are generally using agreed-upon terms such as physical fidelity, but there is an emerging definition of functional fidelity that is being adopted to replace the concept of psychological fidelity for training AI instead of humans.

This paper illustrates a framework for educating students on systems approaches and systems thinking in a near “live” scenario through a case of safety critical control system embedded with Artificial Intelligence (AI). With the recent advances in AI and increasing demands on embedding AI in complex aerospace systems, certification of such systems poses many hurdles and challenges. ...Though AI has been used in aerospace industry for optimization problems for quite some time, challenges in certification of safety critical aerospace control systems embedded with AI are actively being explored in the industry. ...Though AI has been used in aerospace industry for optimization problems for quite some time, challenges in certification of safety critical aerospace control systems embedded with AI are actively being explored in the industry. Experiments on such system are required to clearly understand the verification and safety aspects of deploying such systems.

The major Implementation study area of AI in this paper include implementing in Cargo load planning to reduce the human dependency and error, ground handling with the help of autopiloting vehicle which can operate in any weather condition, sequence of loading Unit Load Devices (ULD’s) based on priority, operating control unit to move ULD in the Cargo deck , fixing ULD’s when it is stuck during operation and implementation of AI based predictive maintenance for the Cargo electrical and mechanical components and AI based design decision making in cargo LRU’s. ...This paper focuses on Artificial Intelligence (AI) implementation can reduce the inefficiency and inconsistency due to the manual intervention in cargo operation in different areas. ...The major Implementation study area of AI in this paper include implementing in Cargo load planning to reduce the human dependency and error, ground handling with the help of autopiloting vehicle which can operate in any weather condition, sequence of loading Unit Load Devices (ULD’s) based on priority, operating control unit to move ULD in the Cargo deck , fixing ULD’s when it is stuck during operation and implementation of AI based predictive maintenance for the Cargo electrical and mechanical components and AI based design decision making in cargo LRU’s.

The intent of this paper is to describe different AI modules and services in this AI platform towards enabling Smart Factory and Industry 4.0....The paper describes an AI based IR platform which caters to the aforesaid scenarios in a scalable manner and integrates seamlessly with similar problems across different domains.

The applications of Artificial Intelligence (AI) in the product design software, and the advancements in the Direct Digital Manufacturing (DDM) such as Additive Manufacturing have been leading the aerospace and automobile industries into the next level. ...The applications of Artificial Intelligence (AI) in the product design software, and the advancements in the Direct Digital Manufacturing (DDM) such as Additive Manufacturing have been leading the aerospace and automobile industries into the next level. AI assisted generative design helps the designers to reduce the weight of the structures without compensating the strength of the structures.