IoT Based Intelligent Transportation System (IoT-ITS) for Global Perspective: A Case Study

Muthuramalingam, S.; Bharathi, A.; Kumar, Sachin; Gayathri, N.; Sathiyaraj, R.; Balamurugan, B.

doi:10.1007/978-3-030-04203-5_13

Cited by 98 publications

(48 citation statements)

References 22 publications

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“…IoT applications such as the toll and reservation ticketing system, navigation tracking and GIS mapping, control and guidance systems, supply chain management solution systems, and smart vehicle applications can tackle some problems during the pandemic to limit crowded areas and help the process of importing and exporting goods. IoT-based Intelligent transportation systems can provide automation in roadways, railways, marine, and airways [44], which help in limiting human-to-human interaction to reduce the infection risk, while enabling continuation of the workflow.…”

Section: Iot In the Transportation Sectormentioning

confidence: 99%

IoT Technologies during and Beyond COVID-19: A Comprehensive Review

2021

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The COVID-19 pandemic provided a much-needed sanity check for IoT-inspired frameworks and solutions. IoT solutions such as remote health monitoring and contact tracing provided support for authorities to successfully manage the spread of the coronavirus. This article provides the first comprehensive review of key IoT solutions that have had an impact on COVID-19 in healthcare, contact tracing, and transportation during the pandemic. Each sector is investigated in depth; and potential applications, social and economic impact, and barriers for mass adaptation are discussed in detail. Furthermore, it elaborates on the challenges and opportunities for IoT framework solutions in the immediate post-COVID-19 era. To this end, privacy and security concerns of IoT applications are analyzed in depth and emerging standards and code of practices for mass adaptation are also discussed. The main contribution of this review paper is the in-depth analysis and categorization of sector-wise IoT technologies, which have the potential to be prominent applications in the new normal. IoT applications in each selected sector are rated for their potential economic and social impact, timeline for mass adaptation, and Technology Readiness Level (TRL). In addition, this article outlines potential research directions for next-generation IoT applications that would facilitate improved performance with preserved privacy and security, as well as wider adaptation by the population at large.

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Section: Iot In the Transportation Sectormentioning

confidence: 99%

IoT Technologies during and Beyond COVID-19: A Comprehensive Review

2021

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“…[22] combined IoT with logistic regression to detect and predict acute stress in patients. Devi and Neetha combined logistic regression with IoT to predict traffic congestion in smart city environments [23,24].…”

Section: Related Workmentioning

confidence: 99%

Multi-Party Privacy-Preserving Logistic Regression with Poor Quality Data Filtering for IoT Contributors

Edemacu

Kim

2021

Electronics

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Nowadays, the internet of things (IoT) is used to generate data in several application domains. A logistic regression, which is a standard machine learning algorithm with a wide application range, is built on such data. Nevertheless, building a powerful and effective logistic regression model requires large amounts of data. Thus, collaboration between multiple IoT participants has often been the go-to approach. However, privacy concerns and poor data quality are two challenges that threaten the success of such a setting. Several studies have proposed different methods to address the privacy concern but to the best of our knowledge, little attention has been paid towards addressing the poor data quality problems in the multi-party logistic regression model. Thus, in this study, we propose a multi-party privacy-preserving logistic regression framework with poor quality data filtering for IoT data contributors to address both problems. Specifically, we propose a new metric gradient similarity in a distributed setting that we employ to filter out parameters from data contributors with poor quality data. To solve the privacy challenge, we employ homomorphic encryption. Theoretical analysis and experimental evaluations using real-world datasets demonstrate that our proposed framework is privacy-preserving and robust against poor quality data.

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“…The second group was focused on its potential application motivated by growing concern about climate change [36] and the optimization of energy consumption through the transfer of energy that exists in the hull, the propeller, and the main engine, demonstrating the efficient reduction of energy consumption and CO 2 emissions [37]. The third group focused on the improvement of intelligent systems, such as the case of a tool to analyze data obtained through the Internet of Things (IoT) [38]. Moreover, other publications showed guidance for implementation [39] and sector analysis [40].…”

Section: Analysis Of the Key Enabling Technologiesmentioning

confidence: 99%

Assessing Sustainability in the Shipbuilding Supply Chain 4.0: A Systematic Review

Ramírez-Peña

Fraga²,

Salguero

et al. 2020

Sustainability

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The supply chain is currently taking on a very important role in organizations seeking to improve the competitiveness and profitability of the company. Its transversal character mainly places it in an unbeatable position to achieve this role. This article, through a study of each of the key enabling technologies of Industry 4.0, aims to obtain a general overview of the current state of the art in shipbuilding adapted to these technologies. To do so, a systematic review of what the scientific community says is carried out, dividing each of the technologies into different categories. In addition, the global vision of countries interested in each of the enabling technologies is also studied. Both studies present a general vision to the companies of the concerns of the scientific community, thus encouraging research on the subject that is focused on the sustainability of the shipbuilding supply chain.

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IoT Based Intelligent Transportation System (IoT-ITS) for Global Perspective: A Case Study

Cited by 98 publications

References 22 publications

IoT Technologies during and Beyond COVID-19: A Comprehensive Review

IoT Technologies during and Beyond COVID-19: A Comprehensive Review

Multi-Party Privacy-Preserving Logistic Regression with Poor Quality Data Filtering for IoT Contributors

Assessing Sustainability in the Shipbuilding Supply Chain 4.0: A Systematic Review

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