IoT Experimental Classroom Project under the Mode of Industry-University-Research Collaboration

Lin, Rong

doi:10.1109/icsgea51094.2020.00099

Cited by 1 publication

(1 citation statement)

References 3 publications

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“…The work presented the sensor and hardware basis, also the application which is running on mobile platform. Lin showed that such methods can improve the teaching and reduce the burden of management and logistics of a laboratory class [5]. Tokarz et al [6] also showed an IoT network infrastructure for remote learning (or in other words, distant laboratory classes), where the physical hardware and student interaction is enhanced with IoT approach.…”

Section: Introduction (Heading 1)mentioning

confidence: 99%

Sensor-based IoT monitoring of Electronics Manufacturing in University Lab Environment

Géczy

Kuglics

Megyeri

et al. 2021

2021 IEEE 27th International Symposium for Design and Technology in Electronic Packaging (SIITME)

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We present a sensor-based IoT monitoring of an electronics manufacturing laboratory in a university environment. The project focuses on the possibilities of retrofitting the current electronics manufacturing equipment (e.g., surface mount technology apparatus) with sensors to gather extensive in-situ information about the critical parameters of the machines and their ambient surroundings. The project is based on two different sensor nodes functioning as fixed and mobile measurement devices around the given points of the laboratory located at our university. The demonstration presents a cost-effective solution of retrofitting machines with IoT-based sensor nodes, enabling new data acquisition functionalities. Also, the demonstration shows an example of a system from where the students can learn about IoT and Industry 4.0 requirements in their educational environment and from remote access. The project also highlights the importance of operational safety and health (OSH) in such workplaces. The paper presents the block diagrams and the functionalities of the sensor nodes. Also, it presents the frontend and backend setup. The user interface layers are also presented, one, which is available through web access, and the other is a proprietary app for clear visualization of the recorded data. The two approaches share the same SQL database, which is stored on the server.

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Section: Introduction (Heading 1)mentioning

confidence: 99%