Social change: A comparative analysis of the impact of the IoT in Japan, Germany and Australia

Shenkoya, Temitayo

doi:10.1016/j.iot.2020.100250

Cited by 10 publications

(7 citation statements)

References 36 publications

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“…IoT is increasingly used and studied worldwide, and it is applied in the industry and at home [26]. From the research results of Shenkoya [26], it is clear that IoT positively influences the society and companies of countries studied in that research. Some examples of IoT applications in logistics are briefly presented as follows.…”

Section: Introductionmentioning

confidence: 89%

Exploring technology opportunities and evolution of IoT-related logistics services with text mining

Chen

2021

Complex Intell. Syst.

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Many IoT technologies have been applied in the logistics industry in recent years, and they have had a substantial impact on many sectors such as shipping, air freight, warehousing, inventory, etc. Exploring technology opportunities and carrying out technological trend analysis are essential for IoT’s evolution, and there are many techniques or methods for doing so. In this paper, data analysis and text mining techniques, technology opportunity analysis (TOA) and technology-service evolution analysis (TSEA) have been applied to analyze and observe IoT technologies’ and services’ evolution. Academic journals, market reports, and patents have been collected and reviewed on the topic of IoT in the logistics field in this paper. Moreover, by using TOA, technology opportunities have been analyzed to explore IoT-related logistics services. The results of TOA, for example, show that cloud technology is essential to develop smart logistics services, and communication RFID technologies are key to developing information logistics services. Finally, TSEA enables the observation of IoT technology and logistics service evolution by combining unstructured and semi-structured data from text documents. Observing the results of TSEA, the evolution of IoT in logistics is identified, and the results of TSEA also confirm those of TOA using unstructured or semi-structured text data from documents only. The results of this paper are discussed and compared with those of some previous review studies. In summary, the results of this paper provide methodological guidelines on this topic for a comprehensive understanding of IoT-related logistics services.

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Section: Introductionmentioning

confidence: 89%

Exploring technology opportunities and evolution of IoT-related logistics services with text mining

Chen

2021

Complex Intell. Syst.

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“…[53][54][55][56] Fog, edge, and cloud technologies, big data analysis tools, and sensor devices further IoRT networks and assist in processing, sharing, networking, and storing data. [57][58][59][60] Decision-making and assessment support of data networks, tools, and modeling determine internal states of real-time data processes across IoRT networks. [61][62][63][64] IoRT sensor and module networking and operating embedded control systems advance scalable data computation and efficient processes across industrial environments.…”

Section: Methodsmentioning

confidence: 99%

“…IoT and robotic systems can be optimized with knowledge-based tools and smart connected devices, by integrating semantic layers and context awareness. The actuality and novelty of this paper are configured by addressing how big data processing systems [49][50][51][52] develop data mining techniques [53][54][55][56], IoRT sensors and devices [57][58][59][60], and deep neural networks. Real-time data tracking and monitoring [61][62][63][64], machine vision technology, sensor data processing algorithms [65][66][67][68], and big geospatial data analytics [69][70][71][72] configure smart product innovation and manufacturing system modeling.…”

Section: Introductionmentioning

confidence: 99%

Big Data Management Algorithms, Deep Learning-Based Object Detection Technologies, and Geospatial Simulation and Sensor Fusion Tools in the Internet of Robotic Things

Andronie

Lăzăroiu

Iatagan

et al. 2023

IJGI

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

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“…IoMT information strategies promote the government’s modification of digital healthcare-related laws and regulations to facilitate the development of the IoMT. Shenkoya ( 2020 ) mentioned that Europe and the United States are actively revising digital medical regulations to regulate the privacy of medical information and the network security issues arising from the use of connected medical devices. Regulation reform is an important success factor in the development of connected medical devices and the IoMT.…”

Section: Literature Reviewmentioning

confidence: 99%

National IoMT platform strategy portfolio decision model under the COVID-19 environment: based on the financial and non-financial value view

et al. 2022

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The Internet of Medical Things (IoMT) is an emerging technology in the healthcare revolution which provides real-time healthcare information communication and reasonable medical resource allocation. The COVID-19 pandemic has had a significant effect on people’s lives and has affected healthcare capacities. It is important for integrated IoMT platform development to overcome the global pandemic challenges. This study proposed the national IoMT platform strategy portfolio decision-making model from the non-financial (technology, organization, environment) and financial perspectives. As a solution to the decision problem, initially, the decision-making trial and evaluation laboratory (DEMATEL) technology were employed to capture the cause-effect relationship based on the perspectives and criteria obtained from the insight of an expert team. The analytic network process (ANP) and pairwise comparisons were then used to determine the weights for the strategy. Simultaneously, this study incorporated IoMT platform resource limitations into the zero–one goal programming (ZOGP) method to obtain an optimal portfolio selection for IoMT platform strategy planning. The results showed that the integrated MCDM method produced reasonable results for selecting the most appropriate IoMT platform strategy portfolio when considering resource constraints such as system installation costs, consultant fees, infrastructure costs, reduction of medical staff demand, and improvement rates for diagnosis efficiency. The decision-making model of the IoMT platform in this study was conclusive and significantly compelling to aid government decision makers in concentrating their efforts on planning IoMT strategies in response to various pandemic and medical resource allocations.

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Social change: A comparative analysis of the impact of the IoT in Japan, Germany and Australia

Cited by 10 publications

References 36 publications

Exploring technology opportunities and evolution of IoT-related logistics services with text mining

Exploring technology opportunities and evolution of IoT-related logistics services with text mining

Big Data Management Algorithms, Deep Learning-Based Object Detection Technologies, and Geospatial Simulation and Sensor Fusion Tools in the Internet of Robotic Things

National IoMT platform strategy portfolio decision model under the COVID-19 environment: based on the financial and non-financial value view

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