Advancing Food Manufacturing: Leveraging Robotic Solutions for Enhanced Quality Assurance and Traceability Across Global Supply Networks DOI
Jacob Tizhe Liberty, Ernest Habanabakize,

Paul Inuwa Adamu

et al.

Trends in Food Science & Technology, Journal Year: 2024, Volume and Issue: 153, P. 104705 - 104705

Published: Sept. 10, 2024

Language: Английский

Artificial intelligence-based decision-making algorithms, Internet of Things sensing networks, and sustainable cyber-physical management systems in big data-driven cognitive manufacturing DOI Creative Commons
George Lăzăroiu, Armenia Androniceanu, Iulia Grecu

et al.

Oeconomia Copernicana, Journal Year: 2022, Volume and Issue: 13(4), P. 1047 - 1080

Published: Dec. 30, 2022

Research background: With increasing evidence of cognitive technologies progressively integrating themselves at all levels the manufacturing enterprises, there is an instrumental need for comprehending how systems can provide increased value and precision in complex operational processes. Purpose article: In this research, prior findings were cumulated proving that integrates artificial intelligence-based decision-making algorithms, real-time big data analytics, sustainable industrial creation, digitized mass production. Methods: Throughout April June 2022, by employing Preferred Reporting Items Systematic Reviews Meta-analysis (PRISMA) guidelines, a quantitative literature review ProQuest, Scopus, Web Science databases was performed, with search terms including ?cognitive Industrial Internet Things?, automation?, systems?, ?cognitively-enhanced machine?, technology-driven computing technologies,? technologies.? The Review Data Repository (SRDR) leveraged, software program collecting, processing, analysis our research. quality selected scholarly sources evaluated harnessing Mixed Method Appraisal Tool (MMAT). AMSTAR (Assessing Methodological Quality Reviews) deployed intelligence intelligent workflows, Dedoose used mixed methods VOSviewer layout algorithms Dimensions bibliometric mapping served as visualization tools. Findings & added: Cognitive developed on product lifecycle management, Things-based production logistics, deep learning-assisted smart process planning, optimizing creation capabilities algorithms. Subsequent interest should be oriented to predictive maintenance assist use

Language: Английский

Citations

89

Big Data Management Algorithms, Deep Learning-Based Object Detection Technologies, and Geospatial Simulation and Sensor Fusion Tools in the Internet of Robotic Things DOI Creative Commons
Mihai Andronie, George Lăzăroiu, Mariana Iatagan

et al.

ISPRS International Journal of Geo-Information, Journal Year: 2023, Volume and Issue: 12(2), P. 35 - 35

Published: Jan. 21, 2023

The objective of this systematic review was to analyze the recently published literature on Internet Robotic Things (IoRT) and integrate insights it articulates big data management algorithms, deep learning-based object detection technologies, geospatial simulation sensor fusion tools. research problems were whether computer vision techniques, mining, simulation-based digital twins, real-time monitoring technology optimize remote sensing robots. Preferred Reporting Items for Systematic Reviews Meta-analysis (PRISMA) guidelines leveraged by a Shiny app obtain flow diagram comprising evidence-based collected managed (the search results screening procedures). Throughout January July 2022, quantitative ProQuest, Scopus, Web Science databases performed, with terms “Internet Things” + “big algorithms”, “deep technologies”, “geospatial tools”. As analyzed between 2017 only 379 sources fulfilled eligibility standards. A total 105, chiefly empirical, have been selected after removing full-text papers that out scope, did not sufficient details, or had limited rigor For quality evaluation so as attain sound outcomes correlations, we deployed AMSTAR (Assessing Methodological Quality Reviews), AXIS (Appraisal tool Cross-Sectional Studies), MMAT (Mixed Methods Appraisal Tool), ROBIS (to assess bias risk in reviews). Dimensions regards initial bibliometric mapping (data visualization) VOSviewer harnessed layout algorithms.

Language: Английский

Citations

70

Machine Intelligence and Autonomous Robotic Technologies in the Corporate Context of SMEs: Deep Learning and Virtual Simulation Algorithms, Cyber-Physical Production Networks, and Industry 4.0-Based Manufacturing Systems DOI Creative Commons
Marek Nagy, George Lăzăroiu, Katarína Valašková

et al.

Applied Sciences, Journal Year: 2023, Volume and Issue: 13(3), P. 1681 - 1681

Published: Jan. 28, 2023

This study examines Industry 4.0-based technologies, focusing on the barriers to their implementation in European small- and medium-sized enterprises (SMEs). The purpose of this research was determine most significant obstacles that prevent SMEs from implementing smart manufacturing, as well identify important components such an operationalization evaluate whether only large businesses have access technological opportunities given financial complexities adoption. is premised notion that, setting cyber-physical production systems, gap between massive corporations may result disadvantages for latter, leading market exclusion by former. aim achieved secondary data analysis, where previously gathered were assessed analyzed. need investigate topic originates fact require more than corporations, which are typically focus mainstream debates. findings validated 4.0′s critical role process planning provided deep learning virtual simulation algorithms, especially industrial production. also discussed connection options a means enhancing business efficiency through machine intelligence autonomous robotic technologies. interaction 4.0 economic management organizations viewed possible source added value.

Language: Английский

Citations

66

The impact of artificial intelligence (AI) on employees’ skills and well-being in global labor markets: A systematic review DOI Creative Commons
Romana Emilia Cramarenco, Monica Ioana Burcă-Voicu, Dan‐Cristian Dabija

et al.

Oeconomia Copernicana, Journal Year: 2023, Volume and Issue: 14(3), P. 731 - 767

Published: Sept. 30, 2023

Research background: This article discusses how artificial intelligence (AI) is affecting workers' personal and professional lives, because of many technological disruptions driven by the recent pandemic that are redefining global labor markets. Purpose article: The objective this paper to develop a systematic review relevant literature identify effects change, especially adoption AI in organizations, on employees’ skills (professional dimension) well-being (personal dimension). Methods: To implement research scope, authors relied Khan's five-step methodology, which included PRISMA flowchart with embedded keywords for selecting appropriate quantitative data study. Firstly, 639 scientific papers published between March 2020 2023 (the end COVID-19 according WHO) from Scopus Web Science (WoS) databases were selected. After applying procedures techniques, 103 articles retained, focused dimension, while 35 component. Findings & value added: Evidence has been presented highlighting difficulties associated ongoing requirement upskilling or reskilling as an adaptive reaction changes. efforts counterbalance skill mismatch impacted employees' challenging times. Although emphasis digital widely accepted, our investigation shows topic still not properly developed. paper's most significant contributions found thorough analysis affects well-being, representative aspects researched academic due paradigm changes generated continuous disruptions.

Language: Английский

Citations

63

An Enhanced Energy Optimization Model for Industrial Wireless Sensor Networks Using Machine Learning DOI Creative Commons
Ashish Bagwari, J. Logeshwaran,

K. Usha

et al.

IEEE Access, Journal Year: 2023, Volume and Issue: 11, P. 96343 - 96362

Published: Jan. 1, 2023

Industrial Wireless Sensor Networks (WSNs) are becoming increasingly popular due to their enhanced scalability and low cost of deployment. However, they also present new challenges, such as energy optimization network maintenance, which industrial users must address. In order meet the Machine Learning techniques have been used create an model for WSNs. This utilizes knowledge-based learning identify optimize consumption nodes, allowing WSNs consume least amount given tasks. addition, evaluates effectiveness feedback control schemes predicts best possible outcomes its application in ensure higher efficiency longer lifetime. The enables exploration potential trade-offs between power communication performance a better energy-efficient solution. proposed EEOM obtained 64.72% transmission consumption, 35.28% saving, 67.27% received 32.73% storage, 52.16% idle-mode 47.84% 66.31% sleep-mode 33.69% storage. It 90.44% prevalence threshold, 90.33% critical success index, 93.93% Delta-P, 90.06% MCC 92.17% FMI rates. provides ability selection nodes paths data reduce traffic. When applied conjunction with manual intervention, these automated will make more reliable, efficient, energy-cost effective.

Language: Английский

Citations

56

Big data management algorithms in artificial Internet of Things-based fintech DOI Creative Commons
Mihai Andronie, Mariana Iatagan, Cristian Uţă

et al.

Oeconomia Copernicana, Journal Year: 2023, Volume and Issue: 14(3), P. 769 - 793

Published: Sept. 30, 2023

Research background: Fintech companies should optimize banking sector performance in assisting enterprise financing as a result of firm digitalization. Artificial IoT-based fintech-based digital transformation can relevantly reverse credit resource misdistribution brought about by corrupt relationship chains. Purpose the article: We aim to show that fintech decrease transaction expenses and consolidates stock liquidity, enabling excess leverage cutting down information asymmetry across capital markets. AI- fintechs enable immersive collaborative financial transactions, purchases, investments relation payment tokens metaverse wallets, managing data, infrastructure, value exchange shared interactive virtual 3D simulated environments. Methods: AMSTAR is comprehensive critical measurement tool harnessed systematic review methodological quality evaluation, DistillerSR producing accurate transparent evidence-based research through literature stage automation, MMAT appraises describes study checklist mixed studies reviews terms content validity predictors, Rayyan responsive intuitive knowledge synthesis cloud-based architecture for article inclusion exclusion suggestions, ROBIS bias risk relevance concerns. As reporting assessment tool, PRISMA flow diagram, generated Shiny App, was used. bibliometric visualization construction tools large datasets networks, Dimensions VOSviewer were leveraged. Search “fintech” + “artificial intelligence”, “big data management algorithms”, “Internet Things”, search period June 2023, published inspected selected sources 35 out 188. Findings & added: The growing volume products optimized operational industries provide firms with multifarious options quickly. Big data-driven innovations are pivotal markets institution efficiency. Through technological process innovation capabilities, AI system-based businesses further automated services.

Language: Английский

Citations

44

Digital Twin Simulation Tools, Spatial Cognition Algorithms, and Multi-Sensor Fusion Technology in Sustainable Urban Governance Networks DOI Creative Commons
Elvira Nica, Gheorghe H. Popescu, Miloš Poliak

et al.

Mathematics, Journal Year: 2023, Volume and Issue: 11(9), P. 1981 - 1981

Published: April 22, 2023

Relevant research has investigated how predictive modeling algorithms, deep-learning-based sensing technologies, and big urban data configure immersive hyperconnected virtual spaces in digital twin cities: tools, monitoring Internet-of-Things-based decision support systems articulate big-data-driven geopolitics. This systematic review aims to inspect the recently published literature on simulation spatial cognition multi-sensor fusion technology sustainable governance networks. We integrate developing blockchain-based twins, smart infrastructure sensors, real-time Internet of Things assist computing technologies. The problems are whether: data-driven urbanism requires visual recognition simulation-based twins; environment perception mechanisms cities; modeling, optimize city environments. Our analyses particularly prove that navigation geospatial mapping connected sensors enable governance. Digital simulation, visualization ambient sound software Virtual deep learning neural network architectures, cyber-physical cognitive networked cities. Throughout January March 2023, a quantitative was carried out across ProQuest, Scopus, Web Science databases, with search terms comprising “sustainable networks” + “digital tools”, “spatial algorithms”, “multi-sensor technology”. A Preferred Reporting Items for Systematic Reviews Meta-analysis (PRISMA) flow diagram generated using Shiny App. AXIS (Appraisal tool Cross-Sectional Studies), Dedoose, MMAT (Mixed Methods Appraisal Tool), Review Data Repository (SRDR) were used assess quality identified scholarly sources. Dimensions VOSviewer employed bibliometric through layout algorithms. findings gathered from our clarify environments 3D technology, intelligent devices, modeling.

Language: Английский

Citations

41

Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review DOI Creative Commons
Yazeed Yasin Ghadi, Tehseen Mazhar, Tamara Al Shloul

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 12699 - 12719

Published: Jan. 1, 2024

Energy efficiency and safety are two essential factors that play a significant role in operating wireless sensor network. However, it is claimed these naturally conflicting. The level of electrical consumption required by security system directly proportional to its degree complexity. Wireless networks require additional measures above the capabilities conventional network protocols, such as encryption key management. potential application machine learning techniques address concerns frequently discussed. These devices will have complete artificial intelligence capabilities, enabling them understand their environment respond. During training phase, machine-learning systems may face challenges due large amount data complex nature procedure. This article focuses on algorithms used solve issues networks. also different types attacks layers Moreover, this study addresses several unsolved issues, including adapting accommodate sensors' functionalities configuration. Furthermore, open field must be solved.

Language: Английский

Citations

28

Frontier in dark fermentative biohydrogen production from lignocellulosic biomass: Challenges and future prospects DOI

Pushpa Rani,

Deepak Kumar Yadav, Arti Yadav

et al.

Fuel, Journal Year: 2024, Volume and Issue: 366, P. 131187 - 131187

Published: March 1, 2024

Language: Английский

Citations

23

Industry 4.0 Wireless Networks and Cyber-Physical Smart Manufacturing Systems as Accelerators of Value-Added Growth in Slovak Exports DOI Creative Commons
Katarína Valašková, Marek Nagy, Stanislav Zábojník

et al.

Mathematics, Journal Year: 2022, Volume and Issue: 10(14), P. 2452 - 2452

Published: July 14, 2022

Industry 4.0 integrates smart and connected production systems that are pivotal in predicting supporting real-time, leading to sustainable organizational performance. In manufacturing, it may increase productivity, sustainability, energy efficiency, while optimizing competitiveness. The main purpose of this paper is determine the impact on Slovak economy through a secondary data analysis automotive industry, which sector country. aims provide comprehensive various opportunities available value-added growth car exports Slovakia. It also explores case study PSA Group Slovakia, highlights importance concept boosting country’s export growth. proposes series recommendations steps improve Slovakia’s innovation environment.

Language: Английский

Citations

63