Sustainable Smart Cities: Networked Digital Technologies, Cognitive Big Data Analytics, and Information Technology-driven Economy

doi:10.22381/ghir11220196

Cited by 18 publications

(7 citation statements)

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“…Cyber-physical smart manufacturing systems function in an automated, robust, and flexible manner. The integration of Internet of Things smart devices, cognitive decision-making algorithms, industrial artificial intelligence, and digitized mass production [169][170][171][172][173][174][175][176][177][178][179][180] furthers the design of cutting-edge monitoring strategies across Industry 4.0 wireless networks.…”

Section: Discussionmentioning

confidence: 99%

Sustainable, Smart, and Sensing Technologies for Cyber-Physical Manufacturing Systems: A Systematic Literature Review

et al. 2021

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With growing evidence of the operational performance of cyber-physical manufacturing systems, there is a pivotal need for comprehending sustainable, smart, and sensing technologies underpinning data-driven decision-making processes. In this research, previous findings were cumulated showing that cyber-physical production networks operate automatically and smoothly with artificial intelligence-based decision-making algorithms in a sustainable manner and contribute to the literature by indicating that sustainable Internet of Things-based manufacturing systems function in an automated, robust, and flexible manner. Throughout October 2020 and April 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “Internet of Things-based real-time production logistics”, “sustainable smart manufacturing”, “cyber-physical production system”, “industrial big data”, “sustainable organizational performance”, “cyber-physical smart manufacturing system”, and “sustainable Internet of Things-based manufacturing system”. As research published between 2018 and 2021 was inspected, and only 426 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 174 mainly empirical sources. Further developments should entail how cyber-physical production networks and Internet of Things-based real-time production logistics, by use of cognitive decision-making algorithms, enable the advancement of data-driven sustainable smart manufacturing.

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Section: Discussionmentioning

confidence: 99%

Sustainable, Smart, and Sensing Technologies for Cyber-Physical Manufacturing Systems: A Systematic Literature Review

et al. 2021

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“…The nature and scale of the problems studied, connects the study with the works of Russian scientists and practitioners [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Modern challenges of the digital ecosystem of transport and logistics

Panyushkina

2023

E3S Web Conf.

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The modern stage in the development of the transport industry is characterized by changes in the traditional economic models of interaction between multiple participants in the provision of transport and logistics services. These changes are caused by digital technologies that form a new digital outline of the business models of the transport industry. The digital ecosystem of transport and logistics is the basis for the breakthrough development of the Russian economy and increasing its competitiveness. However, the digital update format does not offer ready-made solutions, its deployment is constrained by the lack of the necessary number of competent personnel, the high cost of implementing and maintaining digital tools, ensuring high reliability, data preservation and security. All this requires additional resources to overcome the emerging barriers with minimal losses. In this regard, the study of the stated topic is demanded and relevant. Therefore, the purpose of the current study is to systematize the main challenges that create imbalances in the pace and scale of modification of the digital circuit of the transport and logistics ecosystem of the Russian Federation. The need to systematize the challenges in creating the digital contour of the transport and logistics ecosystem is justified by the presence of multiple economic interests in this area, including socially significant ones. However, their multidirectional and contradictory nature hinders the rate of formation of a single trend of development of the transport complex and logistics activities of all participants providing services, as well as the creation of a single digital platform that accumulates the potential for effective interaction of transport complex operators. The study was conducted using general scientific methods of knowledge, such as: generalization and systematization of scientific and statistical data on the risks of the barrier environment in the digital transformation of the Russian transport industry, forming the main challenges of the digital ecosystem of transport and logistics, their comparative analysis, synthesis, application of systemic and functional approaches.

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“…The purpose of our systematic review was to inspect the recently published research on IoRT and harmonize the assimilations it articulates on ambient intelligence and context awareness tools [85][86][87][88], blockchain technologies [89][90][91][92], and path planning and computer vision algorithms [93][94][95][96]. Data gathered continuously by perception devices [97][98][99][100] across industrial robot systems and cloud computing infrastructure [101][102][103][104] diagnose and handle faults by use of visual perception and environment mapping algorithms.…”

Section: Introductionmentioning

confidence: 99%

Remote Big Data Management Tools, Sensing and Computing Technologies, and Visual Perception and Environment Mapping Algorithms in the Internet of Robotic Things

et al. 2022

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The purpose of our systematic review was to inspect the recently published research on Internet of Robotic Things (IoRT) and harmonize the assimilations it articulates on remote big data management tools, sensing and computing technologies, and visual perception and environment mapping algorithms. The research problems were whether robotic manufacturing processes and industrial wireless sensor networks shape IoRT and lead to improved product quality by use of remote big data management tools, whether IoRT devices communicate autonomously regarding event modeling and forecasting by leveraging machine learning and clustering algorithms, sensing and computing technologies, and image processing tools, and whether smart connected objects, situational awareness algorithms, and edge computing technologies configure IoRT systems and cloud robotics in relation to distributed task coordination through visual perception and environment mapping algorithms. A Shiny app was harnessed for Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines to configure the flow diagram integrating evidence-based gathered and processed data (the search outcomes and screening procedures). A quantitative literature review of ProQuest, Scopus, and the Web of Science databases was carried out throughout June and October 2022, with search terms including “Internet of Robotic Things” + “remote big data management tools”, “sensing and computing technologies”, and “visual perception and environment mapping algorithms”. Artificial intelligence and intelligent workflows by use of AMSTAR (Assessing the Methodological Quality of Systematic Reviews), Dedoose, DistillerSR, and SRDR (Systematic Review Data Repository) have been deployed as data extraction tools for literature collection, screening, and evaluation, for document flow monitoring, for inspecting qualitative and mixed methods research, and for establishing robust outcomes and correlations. For bibliometric mapping by use of data visualization, Dimensions AI was leveraged and with regards to layout algorithms, VOSviewer was harnessed.

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Sustainable Smart Cities: Networked Digital Technologies, Cognitive Big Data Analytics, and Information Technology-driven Economy

Cited by 18 publications

References 0 publications

Sustainable, Smart, and Sensing Technologies for Cyber-Physical Manufacturing Systems: A Systematic Literature Review

Sustainable, Smart, and Sensing Technologies for Cyber-Physical Manufacturing Systems: A Systematic Literature Review

Modern challenges of the digital ecosystem of transport and logistics

Remote Big Data Management Tools, Sensing and Computing Technologies, and Visual Perception and Environment Mapping Algorithms in the Internet of Robotic Things

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