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Article

A Model for Working Environment Monitoring in Smart Manufacturing

1
Technical Faculty “Mihajlo Pupin”, University of Novi Sad, 23000 Zrenjanin, Serbia
2
Faculty of Transport and Traffic Engineering, University of East Sarajevo, 74000 Doboj, Bosnia and Herzegovina
3
Faculty of Transport and Traffic Sciences, University of Zagreb, 10000 Zagreb, Croatia
*
Author to whom correspondence should be addressed.
Academic Editor: Przemysław Zawadzki 
Appl. Sci. 2021, 11(6), 2850; https://doi.org/10.3390/app11062850
Received: 27 February 2021 / Revised: 17 March 2021 / Accepted: 17 March 2021 / Published: 23 March 2021
(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)
The growing application of smart manufacturing systems and the expansion of the Industry 4.0 model have created a need for new teaching platforms for education, rapid application development, and testing. This research addresses this need with a proposal for a model of working environment monitoring in smart manufacturing, based on emerging wireless sensor technologies and the message queuing telemetry transport (MQTT) protocol. In accordance with the proposed model, a testing platform was developed. The testing platform was built on open-source hardware and software components. The testing platform was used for the validation of the model within the presented experimental environment. The results showed that the proposed model could be developed by mainly using open-source components, which can then be used to simulate different scenarios, applications, and target systems. Furthermore, the presented stable and functional platform proved to be applicable in the process of rapid prototyping, and software development for the targeted systems, as well as for student teaching as part of the engineering education process. View Full-Text
Keywords: cyber-physical systems; working environment; MQTT; IoT; open-source hardware; open-source-software; smart manufacturing; convolutional neural networks cyber-physical systems; working environment; MQTT; IoT; open-source hardware; open-source-software; smart manufacturing; convolutional neural networks
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Figure 1

  • Externally hosted supplementary file 1
    Doi: 10.3390/app11062850
    Link: https://github.com/ddobrilo/WEMModel
    Description: The Wireshark traffic captures for Scenario 3 and Scenario 4, data needed for analyses in presented in tables and Figure 7 are available online at https://github.com/ddobrilo/WEMModel, Figure 7: Deployment and connectivity of testing platform components, Table S1: Server MQTT packet load per second in 10 nodes scenario, Table S2: Server MQTT packet load per minute in 10 sensor node scenario, Table S3: Packet load and statistics per packet type for four different scenarios (partial data). CNN training and test images are also available.
MDPI and ACS Style

Dobrilovic, D.; Brtka, V.; Stojanov, Z.; Jotanovic, G.; Perakovic, D.; Jausevac, G. A Model for Working Environment Monitoring in Smart Manufacturing. Appl. Sci. 2021, 11, 2850. https://doi.org/10.3390/app11062850

AMA Style

Dobrilovic D, Brtka V, Stojanov Z, Jotanovic G, Perakovic D, Jausevac G. A Model for Working Environment Monitoring in Smart Manufacturing. Applied Sciences. 2021; 11(6):2850. https://doi.org/10.3390/app11062850

Chicago/Turabian Style

Dobrilovic, Dalibor, Vladimir Brtka, Zeljko Stojanov, Gordana Jotanovic, Dragan Perakovic, and Goran Jausevac. 2021. "A Model for Working Environment Monitoring in Smart Manufacturing" Applied Sciences 11, no. 6: 2850. https://doi.org/10.3390/app11062850

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