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ZENODO
Article . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
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IoT IN B2B INDUSTRIAL OPERATIONS

Authors: Sivakumar R D, Assistant Professor, Department of Computer Science; Brindha S, Former Assistant Professor of Business Administration;

IoT IN B2B INDUSTRIAL OPERATIONS

Abstract

The development of the Internet of Things (IoT) is a transforming element for industries and it is changing B2B relationships matrices along different sectors. In this paper, the implementation of IoT technologies within B2B industrial processes is evaluated in terms of such aspects as the consequences, challenges and opportunities. IoT provides continuous connection and data share across all the machines, devices and systems that permit real time tracking, predictive maintenance and streamlining of processes. In addition, through the use of IoT analytics, which provide tangible decisions, managers are able to maximize throughput, improve productivity and leverage cost savings. On the one hand, IoT in B2B industrial environments face challenges of interoperability, cybersecurity issues and also data privacy concerns. This article analyzes ways of dealing with the problem and the main potential of IoT enabled devices by the means of coordination, standardization, and diversity of cyber protection. Furthermore, it considers future trends and directions towards adopting of IoT by means of edge computing, AI integration, and blockchain technology-enabled solutions. The IoT technologies can be used to maximum in a way that B2B industrial operations can achieve a higher degree of agility, robustness and competitiveness in the digital market.

Keywords

Data Exchange, Cybersecurity, Blockchain, Process Optimization, Real-time Monitoring, Internet of Things, B2B Industrial Operations, Predictive Maintenance, Edge Computing, IoT-driven Analytics, Artificial Intelligence (AI), Digital Transformation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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