Edge‐enabled IoT gateway criteria selection and evaluation

Papcun, Peter; Kajáti, Erik; Cupkova, Dominika; Miškuf, Martin; Zolotová, Iveta

doi:10.1002/cpe.5219

Cited by 22 publications

(9 citation statements)

References 30 publications

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“…This context supported the rise of predictive maintenance strategies, which is backed up by some recent works [ 5 , 13 , 14 , 15 , 16 , 17 ] in the literature proposing Internet of Things (IoT) solutions to address such challenges. In this way, edge computing is also emerging as a technology in several aspects of IIoT [ 18 ].…”

Section: Introductionmentioning

confidence: 79%

TIP4.0: Industrial Internet of Things Platform for Predictive Maintenance

Resende

Folgado

Oliveira

et al. 2021

Sensors

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Industry 4.0, allied with the growth and democratization of Artificial Intelligence (AI) and the advent of IoT, is paving the way for the complete digitization and automation of industrial processes. Maintenance is one of these processes, where the introduction of a predictive approach, as opposed to the traditional techniques, is expected to considerably improve the industry maintenance strategies with gains such as reduced downtime, improved equipment effectiveness, lower maintenance costs, increased return on assets, risk mitigation, and, ultimately, profitable growth. With predictive maintenance, dedicated sensors monitor the critical points of assets. The sensor data then feed into machine learning algorithms that can infer the asset health status and inform operators and decision-makers. With this in mind, in this paper, we present TIP4.0, a platform for predictive maintenance based on a modular software solution for edge computing gateways. TIP4.0 is built around Yocto, which makes it readily available and compliant with Commercial Off-the-Shelf (COTS) or proprietary hardware. TIP4.0 was conceived with an industry mindset with communication interfaces that allow it to serve sensor networks in the shop floor and modular software architecture that allows it to be easily adjusted to new deployment scenarios. To showcase its potential, the TIP4.0 platform was validated over COTS hardware, and we considered a public data-set for the simulation of predictive maintenance scenarios. We used a Convolution Neural Network (CNN) architecture, which provided competitive performance over the state-of-the-art approaches, while being approximately four-times and two-times faster than the uncompressed model inference on the Central Processing Unit (CPU) and Graphical Processing Unit, respectively. These results highlight the capabilities of distributed large-scale edge computing over industrial scenarios.

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Section: Introductionmentioning

confidence: 79%

TIP4.0: Industrial Internet of Things Platform for Predictive Maintenance

Resende

Folgado

Oliveira

et al. 2021

Sensors

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“…Experimental resutls showed that control is possible in many solutions, but these solutions will not be depending just on the cloud services. The intelligence on the edge of the network will play a significant role [26]. The computing capacities of end devices are increasing;…”

Section: Discussionmentioning

confidence: 99%

Cloud based cyber-physical systems: Network evaluation study

Kajáti

Papcun

Liu

et al. 2019

Advanced Engineering Informatics

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In recent years, the Industry 4.0 concept brings new demands and trends in different areas; one of them is distributing computational power to the cloud. This concept also introduced the Reference Architectural Model for Industry 4.0 (RAMI 4.0). The efficiency of data communications within the RAMI 4.0 model is a critical issue. Aiming to evaluate the efficiency of data communication in the Cloud Based Cyber-Physical Systems (CB-CPS), this study analyzes the periods and data amount required to communicate with individual hierarchy levels of the RAMI 4.0 model. The evaluation of the network properties of the communication protocols eligible for CB-CPS is presented. The network properties to different cloud providers and data centers' locations have been measured and interpreted. To test the findings, an architecture for cloud control of laboratory model was proposed. It was found that the time of the day; the day of the week; and data center utilization have a negligible impact on latency.

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“…Most of the sensors and devices are not able to connect to the internet for data sharing purposes. To overcome this issue local gateways are designed which act as a mediator among all sensors and devices for controllability, security, and connectivity [36]. Deployment of gateways in livestock farms improves the automation process and controls real-time livestock monitoring systems.…”

Section: ) Connection Gatewaymentioning

confidence: 99%

A Survey on the Role of IoT in Agriculture for the Implementation of Smart Livestock Environment

et al. 2022

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The Internet of Things (IoT) is an emerging paradigm that is transforming real-world things (objects) into smarter devices. IoT is applicable to a variety of application domains including healthcare, smart grid, and agriculture. This domain has started revolutionizing the agriculture industry by providing smart solutions for precision farming, greenhouse management, and livestock monitoring. This article aims to present a comprehensive survey on the role of IoT in the Livestock field by categorizing and synthesizing existing research work in this area. To this end, a detailed discussion has been provided on IoT network infrastructure, topologies and platforms employed for livestock management. In addition, a list of communication protocols and connections of IoT-based livestock systems with relevant technologies have also been explored. Furthermore, numerous IoT-based livestock monitoring, controlling, and tracking applications have been discussed. Apart from this, it also analyses distinct security issues in IoT-based livestock field and developed a collaborative security model to detect and minimize the security risk. Lastly, pertinent open research challenges in the domain of IoT-based livestock management have been presented with future research directions.

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Edge‐enabled IoT gateway criteria selection and evaluation

Cited by 22 publications

References 30 publications

TIP4.0: Industrial Internet of Things Platform for Predictive Maintenance

TIP4.0: Industrial Internet of Things Platform for Predictive Maintenance

Cloud based cyber-physical systems: Network evaluation study

A Survey on the Role of IoT in Agriculture for the Implementation of Smart Livestock Environment

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