Integration of IoT and Edge Computing in Industrial Systems

Mohammad Yazdi ()
Additional contact information
Mohammad Yazdi: Macquarie University

Chapter Chapter 7 in Advances in Computational Mathematics for Industrial System Reliability and Maintainability, 2024, pp 121-137 from Springer

Abstract: Abstract The ever-increasing demand for real-time processing, low latency, and seamless connectivity in industrial systems has paved the way for integrating the Internet of Things (IoT) and Edge Computing. This chapter goes into the revolutionary amalgamation of these two domains and how their convergence fosters significant improvements in industrial processes and operations. IoT, characterized by its myriad of interconnected devices, sensors, and actuators, has been pivotal in transforming the industrial landscape by enabling continuous monitoring, predictive maintenance, and real-time data acquisition. However, the vast amount of data generated by these devices necessitates efficient processing and analytics capabilities, which, when performed on distant cloud servers, could introduce latencies detrimental to real-time industrial applications. This is where Edge Computing plays a crucial role. By positioning data processing closer to the data source, that is, on the edge of the network, it mitigates the latency issues, reduces the load on bandwidth, and ensures faster decision-making processes. Integrating Edge Computing with IoT devices in industrial systems allows for real-time analytics, local data processing, and swift actuation, crucial for applications like autonomous robotic operations, safety systems, and instantaneous quality checks. Furthermore, this chapter discusses the architectural frameworks, benefits, and challenges accompanying this integration. It elaborates on use cases demonstrating significant enhancements in efficiency, reliability, and productivity in various industrial sectors. The findings suggest that the fusion of IoT and Edge Computing is not merely a technological advancement, but a paradigm shift poised to redefine the future of industrial automation and digital transformation.

Keywords: IoT; Edge computing; Real-time processing; Latency; Connectivity; Industrial systems; Data analytics; Predictive maintenance; Network; Autonomous robotics; Safety systems; Digital transformation; Automation (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ssrchp:978-3-031-53514-7_7

Ordering information: This item can be ordered from
http://www.springer.com/9783031535147

DOI: 10.1007/978-3-031-53514-7_7

Access Statistics for this chapter

More chapters in Springer Series in Reliability Engineering from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().