Review of Artificial Intelligence and Machine Learning Technologies: Classification, Restrictions, Opportunities and Challenges

Abstract

Artificial intelligence (AI) is an evolving set of technologies used for solving a wide range of applied issues. The core of AI is machine learning (ML)—a complex of algorithms and methods that address the problems of classification, clustering, and forecasting. The practical application of AI&ML holds promising prospects. Therefore, the researches in this area are intensive. However, the industrial applications of AI and its more intensive use in society are not widespread at the present time. The challenges of widespread AI applications need to be considered from both the AI (internal problems) and the societal (external problems) perspective. This consideration will identify the priority steps for more intensive practical application of AI technologies, their introduction, and involvement in industry and society. The article presents the identification and discussion of the challenges of the employment of AI technologies in the economy and society of resource-based countries. The systematization of AI&ML technologies is implemented based on publications in these areas. This systematization allows for the specification of the organizational, personnel, social and technological limitations. This paper outlines the directions of studies in AI and ML, which will allow us to overcome some of the limitations and achieve expansion of the scope of AI&ML applications.

Digital Twins and Enabling Technologies in Museums and Cultural Heritage: An Overview

“…Sensors for measuring or recording owner’s data , detecting professional and leisure activities [ 2 , 22 ] and scanning the environment, e.g., city life [ 20 ], have found their way into many personal technical devices used in everyday life. Beacons for indoor positioning in an interactive IoT-based museum, use of sensors and actuators to minimize the invasive character of conservation actions or influences from outside (such as sunlight, moisture and water level), sensor networks for asset multipurpose measurement and location-based services are highlighted in [ 25 ].…”

“…from an aircraft or satellite [ 4 ] or from drones [ 10 , 15 , 43 ]. It measures emitted or reflected radiation (in agriculture [ 2 ]), realizes inertial localization [ 5 , 19 ] or generates point clouds [ 14 , 28 ]. For 3D reconstruction in content-centric DTs, objects or artwork are scanned in their surroundings using camera [ 1 ], CCD (charge-coupled device) [ 9 ], laser [ 8 , 29 , 42 ], photogrammetry, triangulation in point clouds or other methods [ 9 , 14 , 24 , 38 , 40 ].…”

“…This process requires redistributing tasks and further developing cultural techniques, which contribute considerably to the transformation of the living spaces and habits of humans and animals in all areas of daily life. Digital transformation and technological progress have benefitted the working world through the elimination of simple or physically demanding activities in favor of highly skilled ones and led to breakthrough advances in the sciences, medicine, social life and leisure activities [ 1 , 2 , 3 ].…”

“…Based on a reference corpus resulting from a search for scientific publications in books, journals and conference papers on the keywords virtual museums , digital twins , emerging technologies and sensor in leading science databases [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ], we classify DTs according to their application areas, relevant technologies and concepts depending on type, focus and features, sensor technology used and adaptation or innovation power throughout their life cycle. Design, realization, operation and evolution are guided by experts, engineers, customers, curators, software engineers and visitors, all of whom define adequate quality criteria (QC) and metrics (QM) for DTs and ViMs V&VA.…”

“…In this review paper, we examine prominent science databases for occurrences of the terms virtual, museum, digital, twin, emerging, technologies, and sensor in journals, book chapters, conference papers and ePublications. Recent searches in Scopus, IEEEXplore, and Google Scholar with the search string “virtual AND museum AND digital AND twin AND emerging AND technologies AND sensor” yield 43 relevant publications [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ] from the last 13 years, 34 of which were in Scopus, 3 of which were excluded because the keywords were used in other meanings, such as “Siamese twins” (cf. Figure 1 and Figure A1 in the Appendix A ).…”