Industrial IoT in 5G environment towards smart manufacturing

Cheng, Jiangfeng; Chen, Weihai; Tao, Fei; Lin, Chun-Liang

doi:10.1016/j.jii.2018.04.001

Cited by 321 publications

(193 citation statements)

References 44 publications

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“…The Tactile Internet increases the capacity to human-tomachine communication by empowering tactile and haptic sensations, and improves the interactions of machines. Tactile internet is a holistic network or grid of networks for remotely getting to, seeing, manipulating, and controlling genuine or virtual objects [22]. This is a sure way for students to have an interactive and haptic feel of Augmented and Virtual reality contents respectively.…”

Section: E Tactile Internet Over 5gmentioning

confidence: 99%

5G Enabled Technologies for Smart Education

Dake¹,

Adjei²

2019

IJACSA

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5G technology use cases depicts the prospects of 5G network model to revolutionize Industry and Education is not an exception. The 5G model in general is made up of three main blocks: Enhanced Mobile Broadband, Massive Machine Type Communication and Ultra Reliable and Low Latency Communication. Within these blocks are the services 5G offers to users. In this paper, we focus on Educational users as beneficiaries of 5G technologies. The modern day Educational Institutions can benefit from the deployment of 5G-enabled services adapted to this sector. We proposed frameworks relating 5G and its disruptive technologies in advancing tools that will propel the idea of a Smart Educational System. This paper hence provides a comprehensive discussion on 5G technologies that will facilitate new teaching and learning trends in Educational environment.

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Section: E Tactile Internet Over 5gmentioning

confidence: 99%

5G Enabled Technologies for Smart Education

Dake¹,

Adjei²

2019

IJACSA

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“…In a similar context, Cheng, et al, (2018) have investigated the emerging application of realtime monitoring and smart communication technology based on 3G, 4G, and 5G communication networks with the massive amount of data generated in the manufacturing process. Researchers further acknowledge the positive impact of these technologies in raising the application of smart manufacturing based on cyber-physical manufacturing system as the dominant development ran across the globe.…”

Section: Current Applications Of Disruptive Technologies In Global Mamentioning

confidence: 99%

Disruption in Manufacturing Industry - The Future of Global Workforce

Bambe¹

2019

ASSRJ

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The aim of this research was to evaluate the future of the global workforce aligned with the disruptive technologies in the manufacturing industry. The impacts of 5G, robotics, artificial intelligence, and machine learning were focused on current research. The purpose was to identify the possible safety net, which could be used by the governments and regulatory authorities to deal with the negative effects of technologies on the workers' displacement in the next 5 to 10 years. Through the implementation of the inductive research methodology based on structured survey questionnaire administered with the sample of 100 employees working in the manufacturing sector, effects of disruptive technologies on the employment situation, production activity and overall organisation performance were addressed. Findings of the investigation have confirmed that new technologies have positive impacts on the production activity and overall organisational performance. New technologies are contributing vitally to increasing the production output, production quality, improving the cost of delays, increasing efficient waste management, reliable and consistent growth and enhanced profitability for the manufacturing companies. In contrary, these technologies are also having negative effects on the employment situation such as reduced recruitment, training, compensation, and increased unrest. Lastly, the set of recommendations directing towards introducing governmental regulations and policies for mandatory training, balanced compensation and increased hiring, are expected to have a significant positive contribution for tackling the issue of displacements.

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“…Recently, the industrial Internet of Things (IIoT) has been widely adopted by various companies, as it provides connectivity and analysis capabilities, which are the key technologies for advanced manufacturing [1][2][3][4]. In IIoT, a large number of sensors are used to periodically detect changes in machine health, manufacturing process, industrial environment, etc.…”

Section: Introductionmentioning

confidence: 99%

Failure Prediction Model Using Iterative Feature Selection for Industrial Internet of Things

Kwon

Kim

2020

Symmetry

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This paper presents a failure prediction model using iterative feature selection, which aims to accurately predict the failure occurrences in industrial Internet of Things (IIoT) environments. In general, vast amounts of data are collected from various sensors in an IIoT environment, and they are analyzed to prevent failures by predicting their occurrence. However, the collected data may include data irrelevant to failures and thereby decrease the prediction accuracy. To address this problem, we propose a failure prediction model using iterative feature selection. To build the model, the relevancy between each feature (i.e., each sensor) and the failure was analyzed using the random forest algorithm, to obtain the importance of the features. Then, feature selection and model building were conducted iteratively. In each iteration, a new feature was selected considering the importance and added to the selected feature set. The failure prediction model was built for each iteration via the support vector machine (SVM). Finally, the failure prediction model having the highest prediction accuracy was selected. The experimental implementation was conducted using open-source R. The results showed that the proposed failure prediction model achieved high prediction accuracy.

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Industrial IoT in 5G environment towards smart manufacturing

Cited by 321 publications

References 44 publications

5G Enabled Technologies for Smart Education

5G Enabled Technologies for Smart Education

Disruption in Manufacturing Industry - The Future of Global Workforce

Failure Prediction Model Using Iterative Feature Selection for Industrial Internet of Things

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