Using artificial intelligence approach to design the product creative on 6G industrial internet of things

2021 ◽  
Author(s):  
Yifang Gao
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Intelligence Approach ◽  
Artificial Intelligence Approach

scholarly journals Artificial intelligence in cyber physical systems

2020 ◽  
Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Max Van Kleek ◽  
Omar Santos ◽  
Uchenna Ani
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Literature Review ◽  
Conceptual Framework ◽  
Cyber Physical Systems ◽  
Industrial Internet Of Things ◽  
Physical Systems ◽  
Industrial Internet ◽  
Selection Decisions ◽  
Future Challenges

Abstract This article conducts a literature review of current and future challenges in the use of artificial intelligence (AI) in cyber physical systems. The literature review is focused on identifying a conceptual framework for increasing resilience with AI through automation supporting both, a technical and human level. The methodology applied resembled a literature review and taxonomic analysis of complex internet of things (IoT) interconnected and coupled cyber physical systems. There is an increased attention on propositions on models, infrastructures and frameworks of IoT in both academic and technical papers. These reports and publications frequently represent a juxtaposition of other related systems and technologies (e.g. Industrial Internet of Things, Cyber Physical Systems, Industry 4.0 etc). We review academic and industry papers published between 2010 and 2020. The results determine a new hierarchical cascading conceptual framework for analysing the evolution of AI decision-making in cyber physical systems. We argue that such evolution is inevitable and autonomous because of the increased integration of connected devices (IoT) in cyber physical systems. To support this argument, taxonomic methodology is adapted and applied for transparency and justifications of concepts selection decisions through building summary maps that are applied for designing the hierarchical cascading conceptual framework.

scholarly journals Smart Helmet 5.0 for Industrial Internet of Things Using Artificial Intelligence

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6241
Author(s):  
Israel Campero-Jurado ◽  
Sergio Márquez-Sánchez ◽  
Juan Quintanar-Gómez ◽  
Sara Rodríguez ◽  
Juan M. Corchado
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Internet Of Things ◽  
Information And Communication Technologies ◽  
Health And Safety ◽  
Working Environment ◽  
Training Dataset ◽  
Support Vector ◽  
Industrial Internet Of Things ◽  
Industrial Internet

Information and communication technologies (ICTs) have contributed to advances in Occupational Health and Safety, improving the security of workers. The use of Personal Protective Equipment (PPE) based on ICTs reduces the risk of accidents in the workplace, thanks to the capacity of the equipment to make decisions on the basis of environmental factors. Paradigms such as the Industrial Internet of Things (IIoT) and Artificial Intelligence (AI) make it possible to generate PPE models feasibly and create devices with more advanced characteristics such as monitoring, sensing the environment and risk detection between others. The working environment is monitored continuously by these models and they notify the employees and their supervisors of any anomalies and threats. This paper presents a smart helmet prototype that monitors the conditions in the workers’ environment and performs a near real-time evaluation of risks. The data collected by sensors is sent to an AI-driven platform for analysis. The training dataset consisted of 11,755 samples and 12 different scenarios. As part of this research, a comparative study of the state-of-the-art models of supervised learning is carried out. Moreover, the use of a Deep Convolutional Neural Network (ConvNet/CNN) is proposed for the detection of possible occupational risks. The data are processed to make them suitable for the CNN and the results are compared against a Static Neural Network (NN), Naive Bayes Classifier (NB) and Support Vector Machine (SVM), where the CNN had an accuracy of 92.05% in cross-validation.

Design of industrial internet of things system based on machine learning and artificial intelligence technology

2020 ◽  
pp. 1-11
Author(s):  
Xu Kun ◽  
Zhiliang Wang ◽  
Ziang Zhou ◽  
Wang Qi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Internet Of Things ◽  
Monitoring System ◽  
Remote Monitoring ◽  
Industrial Equipment ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Test Platform ◽  
Artificial Intelligence Technology

For industrial production, the traditional manual on-site monitoring method is far from meeting production needs, so it is imperative to establish a remote monitoring system for equipment. Based on machine learning algorithms, this paper combines artificial intelligence technology and Internet of Things technology to build an efficient, fast, and accurate industrial equipment monitoring system. Moreover, in view of the characteristics of the diverse types of equipment, scattered layout, and many parameters in the manufacturing equipment as well as the complexity of the high temperature, high pressure, and chemical environment in which the equipment is located, this study designs and implements a remote monitoring and data analysis system for industrial equipment based on the Internet of Things. In addition, based on the application scenarios of the actual aeronautical weather floating platform test platform, this study combines the platform prototype system to design and implement a set of strong real-time communication test platform based on the Windows operating system. The test results show that the industrial Internet of Things system based on machine learning and artificial intelligence technology constructed in this paper has certain practicality.

scholarly journals Emerging Technologies in Manufacturing

2020 ◽  
Vol 1 (2) ◽  
Keyword(s):  
Artificial Intelligence ◽  
Economic Development ◽  
Internet Of Things ◽  
Manufacturing Industry ◽  
Emerging Technologies ◽  
Smart Manufacturing ◽  
Industrial Internet Of Things ◽  
Profound Impact ◽  
The Core ◽  
Industrial Internet

Manufacturing is the way of transforming resources into products or goods which are required to cater to the needs of the society. It constitutes the foundation of any nation’s economic development. This paper reviews emerging technologies in manufacturing. These technologies include artificial intelligence, smart manufacturing, robotics, automation, 3D printing, nanotechnology, industrial Internet of things, and augmented reality. The use of these technologies will have a profound impact on the manufacturing industry. They have the potential to transform manufacturing as we know it. They should be at the core of any manufacturing upgrading effort.

scholarly journals Industrial Internet of Things (IIoT) of Forensic and Vulnerabilities

2020 ◽  
Vol 8 (5) ◽  
pp. 257-260
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
New Technologies ◽  
Smart Devices ◽  
Digital Information ◽  
Forensic Investigation ◽  
Industrial Internet Of Things ◽  
Future Technology ◽  
Industrial Internet ◽  
Investigation Process

The Industrial Internet-of-Things (IIoT) have changed the present world and future technology-based Industry 4.0, however the understanding of Industrial Internet of things (IIoT) has turned out to be big challenge as far as security concern. The main purpose of adopting and going with new technologies will bring new challenges with cybersecurity and will have more expose uncertain vulnerabilities in terms of AI and BI applications and usage with forensic investigation and accuracy of information sharing between smart devices. This paper composed on the utilization of Artificial Intelligence in securing required evidence for forensic investigation process. The legal methods are different as per region and industry, but the back-frame work and case-based thinking are similar. This framework is made from Intelligence systems such as AI and BI too dependent on the digital information from cloud server. The information from Business Intelligence (BI) and Artificial Intelligence (AI) intersects with data on cloud-based server requires more secure network process and firewall to prevent cyber intruders. This paper has discovered a few gaps on security issues and vulnerabilities where as it will cater proper IIoT based procedure for the Digital Forensic Investigation process.

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