The Impact of Artificial Intelligence Applications on the Participation of Autonomous Maintenance and Assets Management Optimisation within Power Industry: A Review

Author(s):  
Abdulla Y. Alseiari ◽  
Peter Farrel ◽  
Yassin Osman
Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 185
Author(s):  
Anna Nowacka ◽  
Magdalena Rzemieniak

The article presents the scope of issues related to the impact of the VUCA (volatility, uncertainty, complexity, ambiguity) environment on digital competences of management staff in power companies. Each company has to deal with its own individual and personalized VUCA world typical for the power industry. Unfortunately, some organizations are not aware of its existence, and therefore they do not identify the signals coming from the external environment while still working according to the developed patterns. The VUCA approach requires changing the competency model in enterprises and focusing on its strengths. On this basis, the research problem regarding power enterprises was formulated. The problem discussed in the article below concerns the undefined and undefined influence of the VUCA environment on the emerging digital competences of managers. In connection with the identification of the research problem in this area, an attempt was made to define the aim of the study, which is to determine the impact of the connections of the VUCA world with digital competences of managers in the energy sector. To solve the research problem, quantitative research was carried out on a randomly selected sample of managers. It has been shown that leaders are more or less aware of the existence of the VUCA world. As key competences, they mention the ability to develop and adapt digital technologies to the needs of the organization or the ability to flexibly switch thinking between various problems. The novelty of the work is the identification of the connections between the VUCA world and competences and the provision also through the prism of artificial intelligence. The existence of links between the VUCA environment and digital competences was indicated, and the use of VUCA as a determinant of the impact on changing the perception of employees was analyzed.


2020 ◽  
Author(s):  
Christopher Welker ◽  
David France ◽  
Alice Henty ◽  
Thalia Wheatley

Advances in artificial intelligence (AI) enable the creation of videos in which a person appears to say or do things they did not. The impact of these so-called “deepfakes” hinges on their perceived realness. Here we tested different versions of deepfake faces for Welcome to Chechnya, a documentary that used face swaps to protect the privacy of Chechen torture survivors who were persecuted because of their sexual orientation. AI face swaps that replace an entire face with another were perceived as more human-like and less unsettling compared to partial face swaps that left the survivors’ original eyes unaltered. The full-face swap was deemed the least unsettling even in comparison to the original (unaltered) face. When rendered in full, AI face swaps can appear human and avoid aversive responses in the viewer associated with the uncanny valley.


2020 ◽  
Vol 28 ◽  
Author(s):  
Valeria Visco ◽  
Germano Junior Ferruzzi ◽  
Federico Nicastro ◽  
Nicola Virtuoso ◽  
Albino Carrizzo ◽  
...  

Background: In the real world, medical practice is changing hand in hand with the development of new Artificial Intelligence (AI) systems and problems from different areas have been successfully solved using AI algorithms. Specifically, the use of AI techniques in setting up or building precision medicine is significant in terms of the accuracy of disease discovery and tailored treatment. Moreover, with the use of technology, clinical personnel can deliver a very much efficient healthcare service. Objective: This article reviews AI state-of-the-art in cardiovascular disease management, focusing on diagnostic and therapeutic improvements. Methods: To that end, we conducted a detailed PubMed search on AI application from distinct areas of cardiology: heart failure, arterial hypertension, atrial fibrillation, syncope and cardiovascular rehabilitation. Particularly, to assess the impact of these technologies in clinical decision-making, this research considers technical and medical aspects. Results: On one hand, some devices in heart failure, atrial fibrillation and cardiac rehabilitation represent an inexpensive, not invasive or not very invasive approach to long-term surveillance and management in these areas. On the other hand, the availability of large datasets (big data) is a useful tool to predict the development and outcome of many cardiovascular diseases. In summary, with this new guided therapy, the physician can supply prompt, individualised, and tailored treatment and the patients feel safe as they are continuously monitored, with a significant psychological effect. Conclusion: Soon, tailored patient care via telemonitoring can improve the clinical practice because AI-based systems support cardiologists in daily medical activities, improving disease detection and treatment. However, the physician-patient relationship remains a pivotal step.


Author(s):  
Nagla Rizk

This chapter looks at the challenges, opportunities, and tensions facing the equitable development of artificial intelligence (AI) in the MENA region in the aftermath of the Arab Spring. While diverse in their natural and human resource endowments, countries of the region share a commonality in the predominance of a youthful population amid complex political and economic contexts. Rampant unemployment—especially among a growing young population—together with informality, gender, and digital inequalities, will likely shape the impact of AI technologies, especially in the region’s labor-abundant resource-poor countries. The chapter then analyzes issues related to data, legislative environment, infrastructure, and human resources as key inputs to AI technologies which in their current state may exacerbate existing inequalities. Ultimately, the promise for AI technologies for inclusion and helping mitigate inequalities lies in harnessing grounds-up youth entrepreneurship and innovation initiatives driven by data and AI, with a few hopeful signs coming from national policies.


2021 ◽  
Vol 13 (3) ◽  
pp. 1426
Author(s):  
Delu Wang ◽  
Xun Xue ◽  
Yadong Wang

The comprehensive and accurate monitoring of coal power overcapacity is the key link and an important foundation for the prevention and control of overcapacity. The previous research fails to fully consider the impact of the industry correlation effect; making it difficult to reflect the state of overcapacity accurately. In this paper; we comprehensively consider the fundamentals; supply; demand; economic and environmental performance of the coal power industry and its upstream; downstream; competitive; and complementary industries to construct an index system for assessing coal power overcapacity risk. Besides; a new evaluation model based on a correlation-based feature selection-association rules-data envelopment analysis (CFS-ARs-DEA) integrated algorithm is proposed by using a data-driven model. The results show that from 2008 to 2017; the risk of coal power overcapacity in China presented a cyclical feature of “decline-rise-decline”, and the risk level has remained high in recent years. In addition to the impact of supply and demand; the environmental benefits and fundamentals of related industries also have a significant impact on coal power overcapacity. Therefore; it is necessary to monitor and govern coal power overcapacity from the overall perspective of the industrial network, and coordinate the advancement of environmental protection and overcapacity control.


2021 ◽  
pp. 115076
Author(s):  
Covadonga Díez-Sanmartín ◽  
Antonio Sarasa-Cabezuelo ◽  
Amado Andrés Belmonte

Work ◽  
2020 ◽  
Vol 67 (3) ◽  
pp. 557-572
Author(s):  
Said Tkatek ◽  
Amine Belmzoukia ◽  
Said Nafai ◽  
Jaafar Abouchabaka ◽  
Youssef Ibnou-ratib

BACKGROUND: To combat COVID-19, curb the pandemic, and manage containment, governments around the world are turning to data collection and population monitoring for analysis and prediction. The massive data generated through the use of big data and artificial intelligence can play an important role in addressing this unprecedented global health and economic crisis. OBJECTIVES: The objective of this work is to develop an expert system that combines several solutions to combat COVID-19. The main solution is based on a new developed software called General Guide (GG) application. This expert system allows us to explore, monitor, forecast, and optimize the data collected in order to take an efficient decision to ensure the safety of citizens, forecast, and slow down the spread’s rate of COVID-19. It will also facilitate countries’ interventions and optimize resources. Moreover, other solutions can be integrated into this expert system, such as the automatic vehicle and passenger sanitizing system equipped with a thermal and smart High Definition (HD) cameras and multi-purpose drones which offer many services. All of these solutions will facilitate lifting COVID-19 restrictions and minimize the impact of this pandemic. METHODS: The methods used in this expert system will assist in designing and analyzing the model based on big data and artificial intelligence (machine learning). This can enhance countries’ abilities and tools in monitoring, combating, and predicting the spread of COVID-19. RESULTS: The results obtained by this prediction process and the use of the above mentioned solutions will help monitor, predict, generate indicators, and make operational decisions to stop the spread of COVID-19. CONCLUSIONS: This developed expert system can assist in stopping the spread of COVID-19 globally and putting the world back to work.


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