scholarly journals A remote MQTT-based data monitoring system for energy efficiency in industrial environments

2021 ◽  
Vol 31 (2) ◽  
pp. 25-35
Author(s):  
Guilherme Balduino Lopes ◽  
Renato Ferreira Fernandes Junior.
Keyword(s):  
Energy Efficiency ◽  
Industry 4.0 ◽  
New Technologies ◽  
Electrical Network ◽  
Industrial Plant ◽  
Production Lines ◽  
Artificial Intelligence System ◽  
Intelligence System ◽  
High Yields ◽  
New Industry

The concept of the new industry seeks not only to improve production processes, but also to bring solutions to environmental problems, in addition to reducing resource consumption, while maintaining high yields. This constant search for process optimization has been the main agent in the development of new technologies aimed at improving the performance of industrial production lines. Thus, this article proposes to raise some important concepts of Industry 4.0, and present the development of a remote IoT-based system that, through MQTT and Modbus protocols, will be responsible for monitoring the entire electrical network of an industrial plant, sending its data to the cloud, where it can be monitored and analyzed by the industry management sector or even by an artificial intelligence system, in a simple and effective way, in real time and from anywhere, in order to assist in decision-making focused on energy efficiency.

“New Normal” Strategic Communication

2020 ◽  
pp. 71-92
Author(s):  
Slavica Cicvarić Kostić ◽  
Jelena Gavrilović Šarenac
Keyword(s):  
Industry 4.0 ◽  
Business Models ◽  
Industrial Revolution ◽  
New Technologies ◽  
Planning Process ◽  
Strategic Communication ◽  
New Normal ◽  
Business Functions ◽  
New Industry ◽  
Modern Technologies

The digital industrial revolution, also called Industry 4.0, is substantially changing all areas of business. The application of modern technologies is transforming not only products and processes in the industry, but also business models in all sectors, which further implies required adaptations of all business functions. This chapter addresses the new dynamics and implications for strategic communication brought on by digitalization. A planning process of strategic communication will be elaborated within a digital context, together with the specifics of communicating with younger generations. Communication activities mostly relevant for companies in the new industry will also be presented. The issue of ethics in strategic communication will be also addressed, together with major initiatives in regulating the standards of the profession. The purpose of this chapter is to describe the changes that new technologies have brought to the discipline.

scholarly journals Identification of Energy Efficiency Trends in the Context of the Development of Industry 4.0 Using the Polish Steel Sector as an Example

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2867 ◽  
Author(s):  
Radosław Wolniak ◽  
Sebastian Saniuk ◽  
Sandra Grabowska ◽  
Bożena Gajdzik
Keyword(s):  
Energy Efficiency ◽  
Industry 4.0 ◽  
Global Economy ◽  
New Technologies ◽  
Research Question ◽  
Steel Production ◽  
Investment Policies ◽  
Improve Energy Efficiency ◽  
Steel Sector ◽  
Steel Market

The steel sector is crucial for the national economy of Poland and the global economy. In response to the challenges of the global steel market and the need to increase the sector’s competitiveness, a number of actions have been taken to increase the energy efficiency of steel production. Based on the synthesis of the literature and our own research, we describe the issues related to energy efficiency and the Industry 4.0 concept. The main aim of this paper is to identify energy efficiency trends in enterprises, especially those that focus on increasing the energy efficiency of production processes, and to make recommendations for investment policy for the Polish steel sector in the era of Industry 4.0. To achieve our goals and answer the research question, we used data from 2000–2019 for the Polish steel industry. The calculations and models in this paper were made by using Gretl software. Using direct research, an econometric model was built that verified the hypothesis regarding the relationship between investment in new technologies and the energy efficiency of steel production. Future investment policies should take the implementation of Industry 4.0 tools in the steel sector into account, which, according to the authors, will measurably improve energy efficiency.

scholarly journals Application of Artificial Intelligence in the Banking Sector

2020 ◽  
Author(s):  
Marina Nikolaevna Iakovleva
Keyword(s):  
Artificial Intelligence ◽  
Banking Sector ◽  
New Technologies ◽  
Artificial Intelligence System ◽  
Intelligence System ◽  
The World ◽  
Relevant Topic

This article is devoted to the study of the role of artificial intelligence in the banking sector. Today, the introduction of new technologies in all spheres of life is a very relevant topic. The article reveals the concept of artificial intelligence as a factor in the development of the banking sector in particular and the economy as a whole. An overview of the use of the artificial intelligence system in banks in Russia and the world is presented.

Emerging Industrial Revolution: Symbiosis of Industry 4.0 and Circular Economy: The Role of Universities

2020 ◽  
Vol 25 (3) ◽  
pp. 505-525 ◽  
Author(s):  
Seeram Ramakrishna ◽  
Alfred Ngowi ◽  
Henk De Jager ◽  
Bankole O. Awuzie
Keyword(s):  
Economic Growth ◽  
Circular Economy ◽  
Industry 4.0 ◽  
Business Models ◽  
Industrial Revolution ◽  
New Technologies ◽  
Production Systems ◽  
Fourth Industrial Revolution ◽  
New Jobs

Growing consumerism and population worldwide raises concerns about society’s sustainability aspirations. This has led to calls for concerted efforts to shift from the linear economy to a circular economy (CE), which are gaining momentum globally. CE approaches lead to a zero-waste scenario of economic growth and sustainable development. These approaches are based on semi-scientific and empirical concepts with technologies enabling 3Rs (reduce, reuse, recycle) and 6Rs (reuse, recycle, redesign, remanufacture, reduce, recover). Studies estimate that the transition to a CE would save the world in excess of a trillion dollars annually while creating new jobs, business opportunities and economic growth. The emerging industrial revolution will enhance the symbiotic pursuit of new technologies and CE to transform extant production systems and business models for sustainability. This article examines the trends, availability and readiness of fourth industrial revolution (4IR or industry 4.0) technologies (for example, Internet of Things [IoT], artificial intelligence [AI] and nanotechnology) to support and promote CE transitions within the higher education institutional context. Furthermore, it elucidates the role of universities as living laboratories for experimenting the utility of industry 4.0 technologies in driving the shift towards CE futures. The article concludes that universities should play a pivotal role in engendering CE transitions.

scholarly journals The vulnerability of securing IoT production lines and their network components in the Industry 4.0 concept

2020 ◽  
Vol 53 (2) ◽  
pp. 11237-11242
Author(s):  
Tibor Horak ◽  
Zuzana Cervenanska ◽  
Ladislav Huraj ◽  
Pavel Vazan ◽  
Jan Janosik ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Production Lines

scholarly journals Clinically applicable artificial intelligence system for dental diagnosis with CBCT

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Matvey Ezhov ◽  
Maxim Gusarev ◽  
Maria Golitsyna ◽  
Julian M. Yates ◽  
Evgeny Kushnerev ◽  
...  
Keyword(s):  
State Of The Art ◽  
Model Development ◽  
Clinical Effectiveness ◽  
Anatomical Landmarks ◽  
Periapical Lesion ◽  
Artificial Intelligence System ◽  
Intelligence System ◽  
Significant Difference ◽  
Diagnostic Capabilities ◽  
Lesion Localization

AbstractIn this study, a novel AI system based on deep learning methods was evaluated to determine its real-time performance of CBCT imaging diagnosis of anatomical landmarks, pathologies, clinical effectiveness, and safety when used by dentists in a clinical setting. The system consists of 5 modules: ROI-localization-module (segmentation of teeth and jaws), tooth-localization and numeration-module, periodontitis-module, caries-localization-module, and periapical-lesion-localization-module. These modules use CNN based on state-of-the-art architectures. In total, 1346 CBCT scans were used to train the modules. After annotation and model development, the AI system was tested for diagnostic capabilities of the Diagnocat AI system. 24 dentists participated in the clinical evaluation of the system. 30 CBCT scans were examined by two groups of dentists, where one group was aided by Diagnocat and the other was unaided. The results for the overall sensitivity and specificity for aided and unaided groups were calculated as an aggregate of all conditions. The sensitivity values for aided and unaided groups were 0.8537 and 0.7672 while specificity was 0.9672 and 0.9616 respectively. There was a statistically significant difference between the groups (p = 0.032). This study showed that the proposed AI system significantly improved the diagnostic capabilities of dentists.

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