scholarly journals The Use of Artificial Intelligence in Industry 4.0

2020 ◽  
Vol 73 ◽  
Author(s):  
Maksim Sharabov ◽  
Georgi Tsochev
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Industry 4.0 ◽  
New Technologies ◽  
Web Of Science ◽  
Predictive Analytics ◽  
Use Case ◽  
Industrial Robotics ◽  
The Past ◽  
New Generation

This article presents a brief overview of the effect of new technologies, how they are changing the manufacturing process, and how the machines are starting to get a lot smarter thanks to the artificial intelligence. The focus is over the examination of Industry 4.0 and how it revolutionized the whole manufacturing segment and what promise of a better, more efficient future it brings. This analysis focuses primarily on how artificial intelligence is integrated, what benefits it brings, and how big of an improvement it is over basic programming. Part of the research is based on 771 publications tracked over the past three to five years. Publications are within some of the well-known databases Scopus, Web of Science, and IEEE. We will examine the basic use case scenarios where AI is crucially needed and how a new generation of the factory can look and feel like a living human being. Keywords: Industry 4.0, artificial intelligence, predictive analytics, predictive maintenance, industrial robotics, computer vision.

The Future of the Planetary Trust in a Kaleidoscopic World

2021 ◽  
pp. 1-8
Author(s):  
Edith Brown Weiss
Keyword(s):  
Artificial Intelligence ◽  
Natural Resource ◽  
Human Activities ◽  
New Technologies ◽  
Future Generations ◽  
Nuclear War ◽  
Human Environment ◽  
The Past ◽  
Resource Degradation ◽  
Shared Goal

Today, it is evident that we are part of a planetary trust. Conserving our planet represents a public good, global as well as local. The threats to future generations resulting from human activities make applying the normative framework of a planetary trust even more urgent than in the past decades. Initially, the planetary trust focused primarily on threats to the natural system of our human environment such as pollution and natural resource degradation, and on threats to cultural heritage. Now, we face a higher threat of nuclear war, cyber wars, and threats from gene drivers that can cause inheritable changes to genes, potential threats from other new technologies such as artificial intelligence, and possible pandemics. In this context, it is proposed that in the kaleidoscopic world, we must engage all the actors to cooperate with the shared goal of caring for and maintaining planet Earth in trust for present and future generations.

Conceptual Model of a Digital Platform for Cyber-Physical Management of a Modern Enterprises Part 1. Digital Platform and Digital Ecosystem

2019 ◽  
Vol 20 (6) ◽  
pp. 323-332 ◽  
Author(s):  
V. I. Gorodetsky ◽  
V. B. Laryukhin ◽  
P. O. Skobelev
Keyword(s):  
Artificial Intelligence ◽  
Conceptual Model ◽  
Industry 4.0 ◽  
Autonomous Agents ◽  
Complex Adaptive System ◽  
Predictive Analytics ◽  
Smart Services ◽  
Digital Platforms ◽  
Digital Platform ◽  
Digital Ecosystem

The paper proposes conceptual model of a digital platform for cyber-physical management of modern enterprises in the upcoming era of Industry 5.0. Unlike Industry 4.0, which focuses on automation of physical processes, Industry 5.0 is oriented on digitization of knowledge and automation of reasoning processes for creating artificial intelligence that is able to manage enterprises. This still emerging era will be characterized by the vision of any business, including industrial production or logistics, as a complex adaptive system built on fundamental principles of self-organization and evolution, as well as interaction of artificial intelligence systems and humans. The paper shows that implementation of such production and logistics management systems will require development of new models and decision-making methods based on knowledge and semantic information processing, integration of computational and communication components, accumulation of big data and its processing for predictive analytics, blockchain technologies for fixing mutual obligations of systems components in the for m of smar t contracts, as well as human-machine and software inter faces. Existing approaches to creation of digital platforms within the digital economy of Industry 4.0 and their limitations are analyzed. The concept of digital ecosystem is developed as an open, distributed, self-organized "system of systems" of smart services capable of coming up with solutions and automatically resolving conflicts through negotiations and concessions. The concept of the digital platform within Industry 5.0 is described, which will be able to support functioning of the digital ecosystem of "smart services" of cyberphysical management of both individual objects and enterprises of humans and robots, and in the future, industries of such enterprises — implemented using self-organizing autonomous agents at all levels.

scholarly journals A Look at the Past, Present and Future Research Trends of Artificial Intelligence in Agriculture

Agronomy ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1839
Author(s):  
José Luis Ruiz-Real ◽  
Juan Uribe-Toril ◽  
José Antonio Torres Arriaza ◽  
Jaime de Pablo Valenciano
Keyword(s):  
Artificial Intelligence ◽  
Web Of Science ◽  
Scientific Literature ◽  
Green Economy ◽  
Future Research ◽  
Agriculture Sector ◽  
The Past ◽  
Use Of Resources ◽  
Research Organizations ◽  
Prolific Authors

Technification in agriculture has resulted in the inclusion of more efficient companies that have evolved into a more complex sector focused on production and quality. Artificial intelligence, one of the relevant areas of technology, is transforming the agriculture sector by reducing the consumption and use of resources. This research uses a bibliometric methodology and a fractional counting method of clustering to analyze the scientific literature on the topic, reviewing 2629 related documents recorded on the Web of Science and Scopus databases. The study found significant results regarding the most relevant and prolific authors (Hoogenboom), supporting research organizations (National Natural Science Foundation of China) and countries (U.S., China, India, or Iran). The identification of leaders in this field gives researchers new possibilities for new lines of research based on previous studies. An in-depth examination of authors’ keywords identified different clusters and trends linking Artificial Intelligence and green economy, sustainable development, climate change, and the environment.

scholarly journals It’s Time to Talk About HPC Storage: Perspectives on the Past and Future

2021 ◽  
Author(s):  
Bradley Settlemyer ◽  
George Amvrosiadis ◽  
Philip Carns ◽  
Robert Ross
Keyword(s):  
Artificial Intelligence ◽  
High Performance ◽  
New Technologies ◽  
Storage Systems ◽  
Storage System ◽  
Status Quo ◽  
Future Research ◽  
The Past ◽  
Experimental Data Analysis ◽  
Performance Computing

High-performance computing (HPC) storage systems are a key component of the success of HPC to date. Recently, we have seen major developments in storage-related technologies, as well as changes to how HPC platforms are used, especially in relation to artificial intelligence and experimental data analysis workloads. These developments merit a revisit of HPC storage system architectural designs. In this paper we discuss the drivers, identify key challenges to status quo posed by these developments, and discuss directions future research might take to unlock the potential of new technologies for the breadth of HPC applications.

scholarly journals Digital twins: artificial intelligence and the IoT cyber-physical systems in Industry 4.0

2021 ◽  
Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Razvan Nicolescu ◽  
Michael Huth ◽  
Omar Santos
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Industry 4.0 ◽  
New Technologies ◽  
Physical Object ◽  
Coupled Systems ◽  
Human Computer Interactions ◽  
New Approach ◽  
Industrial Systems ◽  
Digital Twins

AbstractThis paper presents a summary of mechanisms for the evolution of artificial intelligence in ‘internet of things’ networks. Firstly, the paper investigates how the use of new technologies in industrial systems improves organisational resilience supporting both a technical and human level. Secondly, the paper reports empirical results that correlate academic literature with Industry 4.0 interdependencies between edge components to both external and internal services and systems. The novelty of the paper is a new approach for creating a virtual representation operating as a real-time digital counterpart of a physical object or process (i.e., digital twin) outlined in a conceptual diagram. The methodology applied in this paper resembled a grounded theory analysis of complex interconnected and coupled systems. By connecting the human–computer interactions in different information knowledge management systems, this paper presents a summary of mechanisms for the evolution of artificial intelligence in internet of things networks.

scholarly journals Literature Review on Artificial Intelligence in Journalism: A Bibliometric Analysis of Publications Indexed in the Web of Science and Scopus

2021 ◽  
Vol 10 (4) ◽  
pp. 734-744
Author(s):  
Violetta Zorina ◽  
Elizaveta Osipovskaya
Keyword(s):  
Artificial Intelligence ◽  
Quantitative Research ◽  
Web Of Science ◽  
Empirical Studies ◽  
Academic Literature ◽  
The Past ◽  
Research Areas ◽  
Current State ◽  
Number Of Publications ◽  
The Web

This article reviews the past-to-present academic literature on artificial intelligence (AI) in journalism. Over the past years, these technologies have attracted the sufficient attention of researchers from various fields of scientific study producing a large number of publications. We have reviewed academic articles published between 2015 and 2021 to provide understanding of the current state of the research on AI in various research areas including journalism. The corpus was gathered by searching publications in two international databases, Scopus and the Web of Science (WoS). 70 empirical studies were selected on the basis of applying AI to journalism. Each article was categorized according to the type of database, period of time, the country of publication, the field of study and the frequency of citations. The applied method of quantitative research allows tracking the development of research within six years in the field of automated journalism. Finally, we put forward several proposals for further research in this field.

scholarly journals Positive Effect of Industry 4.0 on Quality and Operations Management

2021 ◽  
Vol 17 (09) ◽  
pp. 133
Author(s):  
Hanane Rifqi ◽  
Abdellah Zamma ◽  
Souad Ben Souda ◽  
Mohamed Hansali
Keyword(s):  
Artificial Intelligence ◽  
Operations Management ◽  
Six Sigma ◽  
Industry 4.0 ◽  
New Technologies ◽  
Lean Six Sigma ◽  
Quality Practices ◽  
Technological Advances ◽  
Potential Gain ◽  
Positive Effect

the last decade has witnessed the birth of technological advances such as the IoT, artificial intelligence, machine learning and augmented reality. These technologies have driven the transition to Industry 4.0 where they have enabled the digitization of manufacturing with potential gain. Also Industry 4.0 has given birth to several new hybrid concepts as well as several management operations to take advantage and become more efficient by using IoT and these new technologies. In our paper, we discuss the effect of Industry 4.0 on management and quality practices by answering the following questions based on the literature review: What is the positive effect of Industry 4.0 on quality improvement and operations management? How does Industry 4.0 integrate concepts (Lean, Six Sigma, Supply Chain ...) to create new paradigms?

scholarly journals Generative Adversarial Networks–Enabled Human–Artificial Intelligence Collaborative Applications for Creative and Design Industries: A Systematic Review of Current Approaches and Trends

2021 ◽  
Vol 4 ◽  
Author(s):  
Rowan T. Hughes ◽  
Liming Zhu ◽  
Tomasz Bednarz
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Web Of Science ◽  
Generative Adversarial Networks ◽  
Image Generation ◽  
The Past ◽  
Research Fields ◽  
Adversarial Networks ◽  
Prisma Statement ◽  
Active Research

The future of work and workplace is very much in flux. A vast amount has been written about artificial intelligence (AI) and its impact on work, with much of it focused on automation and its impact in terms of potential job losses. This review will address one area where AI is being added to creative and design practitioners’ toolbox to enhance their creativity, productivity, and design horizons. A designer’s primary purpose is to create, or generate, the most optimal artifact or prototype, given a set of constraints. We have seen AI encroaching into this space with the advent of generative networks and generative adversarial networks (GANs) in particular. This area has become one of the most active research fields in machine learning over the past number of years, and a number of these techniques, particularly those around plausible image generation, have garnered considerable media attention. We will look beyond automatic techniques and solutions and see how GANs are being incorporated into user pipelines for design practitioners. A systematic review of publications indexed on ScienceDirect, SpringerLink, Web of Science, Scopus, IEEExplore, and ACM DigitalLibrary was conducted from 2015 to 2020. Results are reported according to PRISMA statement. From 317 search results, 34 studies (including two snowball sampled) are reviewed, highlighting key trends in this area. The studies’ limitations are presented, particularly a lack of user studies and the prevalence of toy-examples or implementations that are unlikely to scale. Areas for future study are also identified.

scholarly journals MAKEMESEE –UMA SOLUÇÃO PARA O AUXÍLIO DE DEFICIENTES VISUAIS

2021 ◽  
Vol 13 (2) ◽  
pp. 57-66
Author(s):  
Henrique Ramos Ricci ◽  
Francisco Assis da Silva ◽  
Mário Augusto Pazoti
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Visual Impairment ◽  
Financial Market ◽  
New Technologies ◽  
Medical Images ◽  
Disabled People ◽  
Autonomous Cars ◽  
Computer Power

Solutions involving artificial intelligence has become increasingly common in the last years because the increase of computer power and emergence of new technologies. These works include many humansneeds, like autonomous cars, segmentation of medical images or financial market predictions. Since accessibility is a very important area and the techniques like artificial intelligence and computer vision can make solutions to help disabled people, this paper is showing an aid that can detect, calculate and narrate obstacles to help visual impairment people. With a hardware compound by two webcams, responsible by to get different images from a scene, and a software that can processing the images, classifying, and detecting the obstacles, the system can informthe user what are ahead.

A REVIEW OF FACE RECOGNITION METHODS

2013 ◽  
Vol 27 (04) ◽  
pp. 1356005 ◽  
Author(s):  
M. PARISA BEHAM ◽  
S. MOHAMED MANSOOR ROOMI
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Pattern Recognition ◽  
Face Recognition ◽  
Soft Computing ◽  
Recognition Accuracy ◽  
Previous Survey ◽  
The Past ◽  
Potential Applications ◽  
Feature Based

Face recognition has become more significant and relevant in recent years owing to it potential applications. Since the faces are highly dynamic and pose more issues and challenges to solve, researchers in the domain of pattern recognition, computer vision and artificial intelligence have proposed many solutions to reduce such difficulties so as to improve the robustness and recognition accuracy. As many approaches have been proposed, efforts are also put in to provide an extensive survey of the methods developed over the years. The objective of this paper is to provide a survey of face recognition papers that appeared in the literature over the past decade under all severe conditions that were not discussed in the previous survey and to categorize them into meaningful approaches, viz. appearance based, feature based and soft computing based. A comparative study of merits and demerits of these approaches have been presented.

Sign in / Sign up

Export Citation Format

Share Document