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We show also other applications, where AI can be an excellent tool to evaluate vehicle acoustics. We emphasize the relation of AI to Speech Intelligibility and make considerations concerning other factors influencing Intelligibility. ...The paper presents the concepts and applications regarding Articulation Index (AI) that is widely used in the automotive industry as a powerful parameter to qualify/quantify the middle and high frequency spectra associated to the internal noise of vehicles. ...Finally we discuss the results presented and identify the position of AI in the general context/vision of the parameters that are available in vehicle acoustics.

Artificial intelligence (AI) is the branch of computer science committed to attaining and exceeding the intelligence of the human brain, primarily by innovative software technology. ...The objective of this paper is to provide an overview of AI applications, tools and techniques and to assist and encourage renewed initiative in research, development and applications of AI enhanced expert systems and robotics for the benefit of our industry. ...The objective of this paper is to provide an overview of AI applications, tools and techniques and to assist and encourage renewed initiative in research, development and applications of AI enhanced expert systems and robotics for the benefit of our industry.

Good driving practices, encompassing actions like maintaining smooth acceleration, sustaining a consistent speed, and avoiding aggressive maneuvers, can yield several benefits. These practices enhance energy efficiency, reduce accident risks, and significantly lower maintenance costs. Consequently, the presence of a system capable of providing actionable insights to promote such driving behavior is crucial. Addressing this need, the Drive-GPT model is introduced, representing an AI-based generative pre-trained transformer. Within this study, the transformative potential of deep learning networks, specifically based on transformers, is showcased in capturing the typical driving patterns exhibited by individuals in diverse road, traffic, weather, and vehicle health scenarios.

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.

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.

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.

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.

Here, we develop an automatic judgement system for motor current waveform by establishing an AI model trained by knowledge of experts and CAE technology.

These areas include diagnostics, training, planning and scheduling, process monitoring, control and simulation. AI has been used extensively within Texas Instruments to improve manufacturing productivity and quality. ...Some examples of these internal applications, as well as external customer programs, are used to illustrate AI's potential for the factory of the future.

Artificial intelligence (AI) has witnessed significant attention from both research and industry in recent years. AI is not a new area of research, and research in this field has been reported over decades since 1950 on a continuous basis. ...The buildup of research in the area of AI over the past 60 years and the general viability of application of the past and ongoing research especially in the area of automotive are the motivation behind this work.

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.

Self-supervised learning is a technique where the AI model learns the features from the training data, without tags or labels and tags the data by itself. ...This tagged/labelled data can be further used to train other AI models. This saves the cost of tagging the data. Tagging or labeling is a time-consuming activity, which also needs human effort to do the job.

Among all AI (Artificial Intelligence) areas, Expert System has shown to be one of the most practical applications. ...Despite its great use in several areas, the application of AI techniques is almost unknown in the fluid power domain. Perhaps this is due to the fact that to develop an expert system, the knowledge engineer, namely the system developer, has to convince the domain experts of the system technical feasibility, as well as of its financial return.

The paper outlines a novel approach for applying artificial intelligence (AI) to the training of a mechanical design system model, assimilates the definition of meta-data for design containers (binders) to that of labels for books in a library, and represents customers, requirements, components and assemblies in the form of database objects with hierarchical structure. ...A simple example, one involving idea generation for conceptual design, is presented, in order to provide insight into the significant utility that may be derived from the proposed AI design framework.

This paper combines the findings from the TEACHING project, which delves into the foundations of humanistic AI concepts, with insights derived from an expert workshop in the field of dependability engineering. ...On the other hand, the positive outcome of this dialogue about the dependability of AI in embedded systems is that experts foster a shared understanding across diverse domains of expertise.

It was only a vision at the time, but the introduction of Artificial Intelligence (AI) in manufacturing has since enabled it to become attainable. Since most mature manufacturing organizations have merged traditional quality philosophies and techniques, their processes generate only a few Defects Per Million of Opportunities (DPMO). ...Process Monitoring for Quality (PMQ) is an AI and big data-driven quality philosophy aimed at defect detection and empirical knowledge discovery.

A “toolbox” approach to systematizing the application of AI tools is described. A recommended overall approach for successful application development is suggested.

Trucks with intuition Perceptive Automata partners with Volvo Trucks to demonstrate AI technology that can determine when pedestrians will cross the road. Change is afoot Cummins and its CTO help focus the 2019 SAE COMVEC on the fast-shifting technology landscape that faces both on- and off-highway sectors. ...Editorial AI, ADAS & AVs-oh my! Holistic hydraulic designs add more sensors, controls DSD helps 'balance the books' for buying electric truck technology JCB prepared to meet EU Stage V emissions Protecting a cyber-physical remote diagnostic communication system against cyberattacks SKF employs digital tools to enhance bearing design, performance New Mercedes-Benz Actros loaded with ADAS, active safety tech Q&A Peloton CEO Josh Switkes explains Level 4 'automated following' platooning

However, this requires models based on the physics of the system to be built into the digital twin, links to data from sensors on the real live system, and sophisticated algorithms incorporating artificial intelligence (AI) and machine learning (ML). All of this can be used for integrated vehicle health management (IVHM) decisions, such as determining future failure, root cause analysis, and optimized energy performance. ...The Adoption of Digital Twins in Integrated Vehicle Health Management, however, still has a range of unsettled topics that cover technological reliability, data security and ownership, user presentation and interfaces, as well as certification of the digital twin’s system mechanics (i.e., AI, ML) for use in safety-critical applications. Click here to access the full SAE EDGETM Research Report portfolio.